Repository: ggml-org/llama.cpp
Pull request: compare-commits.sh: support both llama-bench and test-backend-ops

*Make sure to read the [contributing guidelines](https://github.com/ggml-org/llama.cpp/blob/master/CONTRIBUTING.md) before submitting a PR*

This is a follow-up to https://github.com/ggml-org/llama.cpp/pull/14368, adding support for comparing `test-backend-ops` performance results between two commits.

### Testing Done

#### Generated Tables

```
❯ cd /Users/yexiaodong/go/src/github.com/ggerganov/llama.cpp && python3 scripts/compare-llama-bench.py -b 1d5f25c53 -c ecd7fdb4c --tool test-backend-ops -i ./test-backend-ops.sqlite
| Backend   | Operation   | Parameters                              |   Bandwidth (GB/s) 1d5f25c53 |   Bandwidth (GB/s) xd/compare |   Speedup |
|:----------|:------------|:----------------------------------------|-----------------------------:|------------------------------:|----------:|
| Metal     | ADD         | type=f32,ne=[4096,1,1,1],nr=[1,1,1,1]   |                        28.42 |                         28.45 |      1.00 |
| Metal     | ADD         | type=f32,ne=[4096,1,1,1],nr=[1,512,1,1] |                        86.60 |                         97.14 |      1.12 |

❯ cd /Users/yexiaodong/go/src/github.com/ggerganov/llama.cpp && python3 scripts/compare-llama-bench.py -b ecd7fdb4c -c ecd7fdb4c --tool test-backend-ops -i ./test-backend-ops.sqlite                 
| Backend   | Operation   | Parameters                                                                       |   GFLOPS xd/test-backend-ops_sql |   GFLOPS xd/test-backend-ops_sql |   Speedup |
|:----------|:------------|:---------------------------------------------------------------------------------|---------------------------------:|---------------------------------:|----------:|
| Metal     | MUL_MAT     | type_a=f16,type_b=f32,m=128,n=1,k=16416,bs=[8,1],nr=[4,1],per=[0,1,2,3],v=1      |                           127.90 |                           127.90 |      1.00 |
| Metal     | MUL_MAT     | type_a=f16,type_b=f32,m=16416,n=1,k=128,bs=[8,1],nr=[4,1],per=[0,2,1,3],v=0      |                            33.98 |                            33.98 |      1.00 |
| Metal     | MUL_MAT     | type_a=f16,type_b=f32,m=4096,n=1,k=14336,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0     |                            57.91 |                            57.91 |      1.00 |
| Metal     | MUL_MAT     | type_a=f16,type_b=f32,m=4096,n=2,k=14336,bs=[1,1],nr=[1,1],per=[0,1,2,3],v=0     |                           115.00 |                           115.00 |      1.00 |
```

#### Generated Plot

![plot](https://github.com/user-attachments/assets/55489198-a672-453a-b568-fd11fa3086d6)

#### Full Logs

test-backend-ops:

```bash
root@deccddc39743:/ws# CMAKE_OPTS="-DGGML_MUSA=ON -DMUSA_ARCHITECTURES=21" ./scripts/compare-commits.sh 40a6430eb 3ad0161af test-backend-ops -o ADD
+ commit1=40a6430eb
+ commit2=3ad0161af
+ tool=test-backend-ops
+ additional_args='-o ADD'
+ '[' test-backend-ops '!=' llama-bench ']'
+ '[' test-backend-ops '!=' test-backend-ops ']'
+ ./scripts/compare-llama-bench.py --check
+ '[' test-backend-ops = llama-bench ']'
+ db_file=test-backend-ops.sqlite
+ target=test-backend-ops
+ run_args='perf --output sql -o ADD'
+ rm -f test-backend-ops.sqlite
+ '[' -n '' ']'
+ dir=build-bench
+ git checkout 40a6430eb
Note: switching to '40a6430eb'.

You are in 'detached HEAD' state. You can look around, make experimental
changes and commit them, and you can discard any commits you make in this
state without impacting any branches by switching back to a branch.

If you want to create a new branch to retain commits you create, you may
do so (now or later) by using -c with the switch command. Example:

  git switch -c <new-branch-name>

Or undo this operation with:

  git switch -

Turn off this advice by setting config variable advice.detachedHead to false

HEAD is now at 40a6430eb Update README.md
+ run
+ rm -fr build-bench
+ cmake -B build-bench -S . -DGGML_MUSA=ON -DMUSA_ARCHITECTURES=21
++ nproc
+ cmake --build build-bench -t test-backend-ops -j 12
+ build-bench/bin/test-backend-ops perf --output sql -o ADD
+ sqlite3 test-backend-ops.sqlite
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 MUSA devices:
  Device 0: MTT S80, compute capability 2.1, VMM: yes
+ git checkout 3ad0161af
Previous HEAD position was 40a6430eb Update README.md
HEAD is now at 3ad0161af musa: apply mublas API changes
+ run
+ rm -fr build-bench
+ cmake -B build-bench -S . -DGGML_MUSA=ON -DMUSA_ARCHITECTURES=21
++ nproc
+ cmake --build build-bench -t test-backend-ops -j 12
+ build-bench/bin/test-backend-ops perf --output sql -o ADD
+ sqlite3 test-backend-ops.sqlite
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 MUSA devices:
  Device 0: MTT S80, compute capability 2.1, VMM: yes
+ ./scripts/compare-llama-bench.py -b 40a6430eb -c 3ad0161af --tool test-backend-ops -i test-backend-ops.sqlite
| Backend   | Operation   | Parameters                              |   Bandwidth (GB/s) xd/compare-commits |   Bandwidth (GB/s) 3ad0161af |   Speedup |
|:----------|:------------|:----------------------------------------|--------------------------------------:|-----------------------------:|----------:|
| MUSA0     | ADD         | type=f32,ne=[4096,1,1,1],nr=[1,1,1,1]   |                                  4.53 |                         4.53 |      1.00 |
| MUSA0     | ADD         | type=f32,ne=[4096,1,1,1],nr=[1,512,1,1] |                                246.99 |                       247.09 |      1.00 |
```

llama-bench:

```bash
❯ ./scripts/compare-commits.sh 7ae027c03 7736d6426 llama-bench -m /Users/yexiaodong/models/DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf -ngl 999
+ commit1=7ae027c03
+ commit2=7736d6426
+ tool=llama-bench
+ additional_args='-m /Users/yexiaodong/models/DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf -ngl 999'
+ '[' llama-bench '!=' llama-bench ']'
+ ./scripts/compare-llama-bench.py --check
+ '[' llama-bench = llama-bench ']'
+ db_file=llama-bench.sqlite
+ target=llama-bench
+ run_args='-o sql -oe md -m /Users/yexiaodong/models/DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf -ngl 999'
+ rm -f llama-bench.sqlite
+ '[' -n '' ']'
+ dir=build-bench
+ git checkout 7ae027c03
Previous HEAD position was 7736d6426 Apply suggestion from @JohannesGaessler
HEAD is now at 7ae027c03 Update README.md
+ run
+ rm -fr build-bench
+ cmake -B build-bench -S .
CMake Warning at ggml/src/ggml-cpu/CMakeLists.txt:77 (message):
  OpenMP not found
Call Stack (most recent call first):
  ggml/src/CMakeLists.txt:361 (ggml_add_cpu_backend_variant_impl)


++ nproc
+ cmake --build build-bench -t llama-bench -j 8
+ build-bench/bin/llama-bench -o sql -oe md -m /Users/yexiaodong/models/DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf -ngl 999
+ sqlite3 llama-bench.sqlite
| model                          |       size |     params | backend    | threads |            test |                  t/s |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | --------------: | -------------------: |
| qwen2 7B Q4_K - Medium         |   4.36 GiB |     7.62 B | Metal,BLAS |       4 |           pp512 |        105.58 ± 1.85 |
| qwen2 7B Q4_K - Medium         |   4.36 GiB |     7.62 B | Metal,BLAS |       4 |           tg128 |          9.32 ± 1.50 |

build: 7ae027c03 (5844)
+ git checkout 7736d6426
Previous HEAD position was 7ae027c03 Update README.md
HEAD is now at 7736d6426 Apply suggestion from @JohannesGaessler
+ run
+ rm -fr build-bench
+ cmake -B build-bench -S .
CMake Warning at ggml/src/ggml-cpu/CMakeLists.txt:77 (message):
  OpenMP not found
Call Stack (most recent call first):
  ggml/src/CMakeLists.txt:361 (ggml_add_cpu_backend_variant_impl)


++ nproc
+ cmake --build build-bench -t llama-bench -j 8
+ sqlite3 llama-bench.sqlite
+ build-bench/bin/llama-bench -o sql -oe md -m /Users/yexiaodong/models/DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf -ngl 999
| model                          |       size |     params | backend    | threads |            test |                  t/s |
| ------------------------------ | ---------: | ---------: | ---------- | ------: | --------------: | -------------------: |
| qwen2 7B Q4_K - Medium         |   4.36 GiB |     7.62 B | Metal,BLAS |       4 |           pp512 |        101.41 ± 9.71 |
| qwen2 7B Q4_K - Medium         |   4.36 GiB |     7.62 B | Metal,BLAS |       4 |           tg128 |         11.11 ± 0.99 |

build: 7736d6426 (5843)
+ ./scripts/compare-llama-bench.py -b 7ae027c03 -c 7736d6426 --tool llama-bench -i llama-bench.sqlite
| CPU                  | Model           | Test   |   t/s xd/compare-commits |   t/s 7736d6426 |   Speedup |
|:---------------------|:----------------|:-------|-------------------------:|----------------:|----------:|
| Accelerate, Apple M1 | qwen2 7B Q4_K_M | pp512  |                   105.58 |          101.41 |      0.96 |
| Accelerate, Apple M1 | qwen2 7B Q4_K_M | tg128  |                     9.32 |           11.11 |      1.19 |
```

Changed files:
filename: scripts/compare-commits.sh
patch: @@ -1,19 +1,41 @@
 #!/usr/bin/env bash
 
 if [ $# -lt 2 ]; then
-    echo "usage: ./scripts/compare-commits.sh <commit1> <commit2> [additional llama-bench arguments]"
+    echo "usage: ./scripts/compare-commits.sh <commit1> <commit2> [tool] [additional arguments]"
+    echo "  tool: 'llama-bench' (default) or 'test-backend-ops'"
+    echo "  additional arguments: passed to the selected tool"
     exit 1
 fi
 
 set -e
 set -x
 
+# Parse arguments
+commit1=$1
+commit2=$2
+tool=${3:-llama-bench}
+additional_args="${@:4}"
+
+# Validate tool argument
+if [ "$tool" != "llama-bench" ] && [ "$tool" != "test-backend-ops" ]; then
+    echo "Error: tool must be 'llama-bench' or 'test-backend-ops'"
+    exit 1
+fi
+
 # verify at the start that the compare script has all the necessary dependencies installed
 ./scripts/compare-llama-bench.py --check
 
-bench_args="${@:3}"
+if [ "$tool" = "llama-bench" ]; then
+    db_file="llama-bench.sqlite"
+    target="llama-bench"
+    run_args="-o sql -oe md $additional_args"
+else  # test-backend-ops
+    db_file="test-backend-ops.sqlite"
+    target="test-backend-ops"
+    run_args="perf --output sql $additional_args"
+fi
 
-rm -f llama-bench.sqlite > /dev/null
+rm -f "$db_file" > /dev/null
 
 # to test a backend, call the script with the corresponding environment variable (e.g. GGML_CUDA=1 ./scripts/compare-commits.sh ...)
 if [ -n "$GGML_CUDA" ]; then
@@ -25,14 +47,14 @@ dir="build-bench"
 function run {
     rm -fr ${dir} > /dev/null
     cmake -B ${dir} -S . ${CMAKE_OPTS} > /dev/null
-    cmake --build ${dir} -t llama-bench > /dev/null
-    ${dir}/bin/llama-bench -o sql -oe md $bench_args | sqlite3 llama-bench.sqlite
+    cmake --build ${dir} -t $target -j $(nproc) > /dev/null
+    ${dir}/bin/$target $run_args | sqlite3 "$db_file"
 }
 
-git checkout $1 > /dev/null
+git checkout $commit1 > /dev/null
 run
 
-git checkout $2 > /dev/null
+git checkout $commit2 > /dev/null
 run
 
-./scripts/compare-llama-bench.py -b $1 -c $2
+./scripts/compare-llama-bench.py -b $commit1 -c $commit2 --tool $tool -i "$db_file"

filename: scripts/compare-llama-bench.py
patch: @@ -1,16 +1,16 @@
 #!/usr/bin/env python3
 
-import logging
 import argparse
+import csv
 import heapq
-import sys
+import json
+import logging
 import os
-from glob import glob
 import sqlite3
-import json
-import csv
-from typing import Optional, Union
+import sys
 from collections.abc import Iterator, Sequence
+from glob import glob
+from typing import Any, Optional, Union
 
 try:
     import git
@@ -23,7 +23,7 @@
 logger = logging.getLogger("compare-llama-bench")
 
 # All llama-bench SQL fields
-DB_FIELDS = [
+LLAMA_BENCH_DB_FIELDS = [
     "build_commit", "build_number", "cpu_info",       "gpu_info",   "backends",     "model_filename",
     "model_type",   "model_size",   "model_n_params", "n_batch",    "n_ubatch",     "n_threads",
     "cpu_mask",     "cpu_strict",   "poll",           "type_k",     "type_v",       "n_gpu_layers",
@@ -33,7 +33,7 @@
     "test_time",    "avg_ns",       "stddev_ns",      "avg_ts",     "stddev_ts",
 ]
 
-DB_TYPES = [
+LLAMA_BENCH_DB_TYPES = [
     "TEXT",    "INTEGER", "TEXT",    "TEXT",    "TEXT",    "TEXT",
     "TEXT",    "INTEGER", "INTEGER", "INTEGER", "INTEGER", "INTEGER",
     "TEXT",    "INTEGER", "INTEGER", "TEXT",    "TEXT",    "INTEGER",
@@ -42,20 +42,41 @@
     "INTEGER", "INTEGER", "INTEGER", "INTEGER", "INTEGER", "INTEGER",
     "TEXT",    "INTEGER", "INTEGER", "REAL",    "REAL",
 ]
-assert len(DB_FIELDS) == len(DB_TYPES)
 
-# Properties by which to differentiate results per commit:
-KEY_PROPERTIES = [
+# All test-backend-ops SQL fields
+TEST_BACKEND_OPS_DB_FIELDS = [
+    "test_time", "build_commit", "backend_name",  "op_name", "op_params", "test_mode",
+    "supported", "passed",       "error_message", "time_us", "flops",     "bandwidth_gb_s",
+    "memory_kb", "n_runs"
+]
+
+TEST_BACKEND_OPS_DB_TYPES = [
+    "TEXT",    "TEXT",    "TEXT", "TEXT", "TEXT", "TEXT",
+    "INTEGER", "INTEGER", "TEXT", "REAL", "REAL", "REAL",
+    "INTEGER", "INTEGER"
+]
+
+assert len(LLAMA_BENCH_DB_FIELDS) == len(LLAMA_BENCH_DB_TYPES)
+assert len(TEST_BACKEND_OPS_DB_FIELDS) == len(TEST_BACKEND_OPS_DB_TYPES)
+
+# Properties by which to differentiate results per commit for llama-bench:
+LLAMA_BENCH_KEY_PROPERTIES = [
     "cpu_info", "gpu_info", "backends", "n_gpu_layers", "tensor_buft_overrides", "model_filename", "model_type",
     "n_batch", "n_ubatch", "embeddings", "cpu_mask", "cpu_strict", "poll", "n_threads", "type_k", "type_v",
     "use_mmap", "no_kv_offload", "split_mode", "main_gpu", "tensor_split", "flash_attn", "n_prompt", "n_gen", "n_depth"
 ]
 
+# Properties by which to differentiate results per commit for test-backend-ops:
+TEST_BACKEND_OPS_KEY_PROPERTIES = [
+    "backend_name", "op_name", "op_params", "test_mode"
+]
+
 # Properties that are boolean and are converted to Yes/No for the table:
-BOOL_PROPERTIES = ["embeddings", "cpu_strict", "use_mmap", "no_kv_offload", "flash_attn"]
+LLAMA_BENCH_BOOL_PROPERTIES = ["embeddings", "cpu_strict", "use_mmap", "no_kv_offload", "flash_attn"]
+TEST_BACKEND_OPS_BOOL_PROPERTIES = ["supported", "passed"]
 
-# Header names for the table:
-PRETTY_NAMES = {
+# Header names for the table (llama-bench):
+LLAMA_BENCH_PRETTY_NAMES = {
     "cpu_info": "CPU", "gpu_info": "GPU", "backends": "Backends", "n_gpu_layers": "GPU layers",
     "tensor_buft_overrides": "Tensor overrides", "model_filename": "File", "model_type": "Model", "model_size": "Model size [GiB]",
     "model_n_params": "Num. of par.", "n_batch": "Batch size", "n_ubatch": "Microbatch size", "embeddings": "Embeddings",
@@ -64,21 +85,42 @@
     "flash_attn": "FlashAttention",
 }
 
-DEFAULT_SHOW = ["model_type"]  # Always show these properties by default.
-DEFAULT_HIDE = ["model_filename"]  # Always hide these properties by default.
+# Header names for the table (test-backend-ops):
+TEST_BACKEND_OPS_PRETTY_NAMES = {
+    "backend_name": "Backend", "op_name": "GGML op", "op_params": "Op parameters", "test_mode": "Mode",
+    "supported": "Supported", "passed": "Passed", "error_message": "Error",
+    "flops": "FLOPS", "bandwidth_gb_s": "Bandwidth (GB/s)", "memory_kb": "Memory (KB)", "n_runs": "Runs"
+}
+
+DEFAULT_SHOW_LLAMA_BENCH = ["model_type"]  # Always show these properties by default.
+DEFAULT_HIDE_LLAMA_BENCH = ["model_filename"]  # Always hide these properties by default.
+
+DEFAULT_SHOW_TEST_BACKEND_OPS = ["backend_name", "op_name"]  # Always show these properties by default.
+DEFAULT_HIDE_TEST_BACKEND_OPS = ["error_message"]  # Always hide these properties by default.
+
 GPU_NAME_STRIP = ["NVIDIA GeForce ", "Tesla ", "AMD Radeon "]  # Strip prefixes for smaller tables.
 MODEL_SUFFIX_REPLACE = {" - Small": "_S", " - Medium": "_M", " - Large": "_L"}
 
-DESCRIPTION = """Creates tables from llama-bench data written to multiple JSON/CSV files, a single JSONL file or SQLite database. Example usage (Linux):
+DESCRIPTION = """Creates tables from llama-bench or test-backend-ops data written to multiple JSON/CSV files, a single JSONL file or SQLite database. Example usage (Linux):
 
+For llama-bench:
 $ git checkout master
-$ make clean && make llama-bench
+$ cmake -B ${BUILD_DIR} ${CMAKE_OPTS} && cmake --build ${BUILD_DIR} -t llama-bench -j $(nproc)
 $ ./llama-bench -o sql | sqlite3 llama-bench.sqlite
 $ git checkout some_branch
-$ make clean && make llama-bench
+$ cmake -B ${BUILD_DIR} ${CMAKE_OPTS} && cmake --build ${BUILD_DIR} -t llama-bench -j $(nproc)
 $ ./llama-bench -o sql | sqlite3 llama-bench.sqlite
 $ ./scripts/compare-llama-bench.py
 
+For test-backend-ops:
+$ git checkout master
+$ cmake -B ${BUILD_DIR} ${CMAKE_OPTS} && cmake --build ${BUILD_DIR} -t test-backend-ops -j $(nproc)
+$ ./test-backend-ops perf --output sql | sqlite3 test-backend-ops.sqlite
+$ git checkout some_branch
+$ cmake -B ${BUILD_DIR} ${CMAKE_OPTS} && cmake --build ${BUILD_DIR} -t test-backend-ops -j $(nproc)
+$ ./test-backend-ops perf --output sql | sqlite3 test-backend-ops.sqlite
+$ ./scripts/compare-llama-bench.py --tool test-backend-ops -i test-backend-ops.sqlite
+
 Performance numbers from multiple runs per commit are averaged WITHOUT being weighted by the --repetitions parameter of llama-bench.
 """
 
@@ -96,6 +138,13 @@
     "Defaults to the non-master commit for which llama-bench was run most recently."
 )
 parser.add_argument("-c", "--compare", help=help_c)
+help_t = (
+    "The tool whose data is being compared. "
+    "Either 'llama-bench' or 'test-backend-ops'. "
+    "This determines the database schema and comparison logic used. "
+    "If left unspecified, try to determine from the input file."
+)
+parser.add_argument("-t", "--tool", help=help_t, default=None, choices=[None, "llama-bench", "test-backend-ops"])
 help_i = (
     "JSON/JSONL/SQLite/CSV files for comparing commits. "
     "Specify multiple times to use multiple input files (JSON/CSV only). "
@@ -114,7 +163,8 @@
 help_s = (
     "Columns to add to the table. "
     "Accepts a comma-separated list of values. "
-    f"Legal values: {', '.join(KEY_PROPERTIES[:-3])}. "
+    f"Legal values for test-backend-ops: {', '.join(TEST_BACKEND_OPS_KEY_PROPERTIES)}. "
+    f"Legal values for llama-bench: {', '.join(LLAMA_BENCH_KEY_PROPERTIES[:-3])}. "
     "Defaults to model name (model_type) and CPU and/or GPU name (cpu_info, gpu_info) "
     "plus any column where not all data points are the same. "
     "If the columns are manually specified, then the results for each unique combination of the "
@@ -142,8 +192,14 @@
     sys.exit(1)
 
 input_file = known_args.input
-if not input_file and os.path.exists("./llama-bench.sqlite"):
-    input_file = ["llama-bench.sqlite"]
+tool = known_args.tool
+
+if not input_file:
+    if tool == "llama-bench" and os.path.exists("./llama-bench.sqlite"):
+        input_file = ["llama-bench.sqlite"]
+    elif tool == "test-backend-ops" and os.path.exists("./test-backend-ops.sqlite"):
+        input_file = ["test-backend-ops.sqlite"]
+
 if not input_file:
     sqlite_files = glob("*.sqlite")
     if len(sqlite_files) == 1:
@@ -161,14 +217,23 @@ class LlamaBenchData:
     build_len_max: int
     build_len: int = 8
     builds: list[str] = []
-    check_keys = set(KEY_PROPERTIES + ["build_commit", "test_time", "avg_ts"])
+    tool: str = "llama-bench"  # Tool type: "llama-bench" or "test-backend-ops"
 
-    def __init__(self):
+    def __init__(self, tool: str = "llama-bench"):
+        self.tool = tool
         try:
             self.repo = git.Repo(".", search_parent_directories=True)
         except git.InvalidGitRepositoryError:
             self.repo = None
 
+        # Set schema-specific properties based on tool
+        if self.tool == "llama-bench":
+            self.check_keys = set(LLAMA_BENCH_KEY_PROPERTIES + ["build_commit", "test_time", "avg_ts"])
+        elif self.tool == "test-backend-ops":
+            self.check_keys = set(TEST_BACKEND_OPS_KEY_PROPERTIES + ["build_commit", "test_time"])
+        else:
+            assert False
+
     def _builds_init(self):
         self.build_len = self.build_len_min
 
@@ -252,52 +317,121 @@ def get_rows(self, properties: list[str], hexsha8_baseline: str, hexsha8_compare
 class LlamaBenchDataSQLite3(LlamaBenchData):
     connection: sqlite3.Connection
     cursor: sqlite3.Cursor
+    table_name: str
 
-    def __init__(self):
-        super().__init__()
+    def __init__(self, tool: str = "llama-bench"):
+        super().__init__(tool)
         self.connection = sqlite3.connect(":memory:")
         self.cursor = self.connection.cursor()
-        self.cursor.execute(f"CREATE TABLE test({', '.join(' '.join(x) for x in zip(DB_FIELDS, DB_TYPES))});")
+
+        # Set table name and schema based on tool
+        if self.tool == "llama-bench":
+            self.table_name = "test"
+            db_fields = LLAMA_BENCH_DB_FIELDS
+            db_types = LLAMA_BENCH_DB_TYPES
+        elif self.tool == "test-backend-ops":
+            self.table_name = "test_backend_ops"
+            db_fields = TEST_BACKEND_OPS_DB_FIELDS
+            db_types = TEST_BACKEND_OPS_DB_TYPES
+        else:
+            assert False
+
+        self.cursor.execute(f"CREATE TABLE {self.table_name}({', '.join(' '.join(x) for x in zip(db_fields, db_types))});")
 
     def _builds_init(self):
         if self.connection:
-            self.build_len_min = self.cursor.execute("SELECT MIN(LENGTH(build_commit)) from test;").fetchone()[0]
-            self.build_len_max = self.cursor.execute("SELECT MAX(LENGTH(build_commit)) from test;").fetchone()[0]
+            self.build_len_min = self.cursor.execute(f"SELECT MIN(LENGTH(build_commit)) from {self.table_name};").fetchone()[0]
+            self.build_len_max = self.cursor.execute(f"SELECT MAX(LENGTH(build_commit)) from {self.table_name};").fetchone()[0]
 
             if self.build_len_min != self.build_len_max:
                 logger.warning("Data contains commit hashes of differing lengths. It's possible that the wrong commits will be compared. "
                                "Try purging the the database of old commits.")
-                self.cursor.execute(f"UPDATE test SET build_commit = SUBSTRING(build_commit, 1, {self.build_len_min});")
+                self.cursor.execute(f"UPDATE {self.table_name} SET build_commit = SUBSTRING(build_commit, 1, {self.build_len_min});")
 
-            builds = self.cursor.execute("SELECT DISTINCT build_commit FROM test;").fetchall()
+            builds = self.cursor.execute(f"SELECT DISTINCT build_commit FROM {self.table_name};").fetchall()
             self.builds = list(map(lambda b: b[0], builds))  # list[tuple[str]] -> list[str]
         super()._builds_init()
 
     def builds_timestamp(self, reverse: bool = False) -> Union[Iterator[tuple], Sequence[tuple]]:
         data = self.cursor.execute(
-            "SELECT build_commit, test_time FROM test ORDER BY test_time;").fetchall()
+            f"SELECT build_commit, test_time FROM {self.table_name} ORDER BY test_time;").fetchall()
         return reversed(data) if reverse else data
 
     def get_rows(self, properties: list[str], hexsha8_baseline: str, hexsha8_compare: str) -> Sequence[tuple]:
+        if self.tool == "llama-bench":
+            return self._get_rows_llama_bench(properties, hexsha8_baseline, hexsha8_compare)
+        elif self.tool == "test-backend-ops":
+            return self._get_rows_test_backend_ops(properties, hexsha8_baseline, hexsha8_compare)
+        else:
+            assert False
+
+    def _get_rows_llama_bench(self, properties: list[str], hexsha8_baseline: str, hexsha8_compare: str) -> Sequence[tuple]:
         select_string = ", ".join(
             [f"tb.{p}" for p in properties] + ["tb.n_prompt", "tb.n_gen", "tb.n_depth", "AVG(tb.avg_ts)", "AVG(tc.avg_ts)"])
         equal_string = " AND ".join(
-            [f"tb.{p} = tc.{p}" for p in KEY_PROPERTIES] + [
+            [f"tb.{p} = tc.{p}" for p in LLAMA_BENCH_KEY_PROPERTIES] + [
                 f"tb.build_commit = '{hexsha8_baseline}'", f"tc.build_commit = '{hexsha8_compare}'"]
         )
         group_order_string = ", ".join([f"tb.{p}" for p in properties] + ["tb.n_gen", "tb.n_prompt", "tb.n_depth"])
-        query = (f"SELECT {select_string} FROM test tb JOIN test tc ON {equal_string} "
+        query = (f"SELECT {select_string} FROM {self.table_name} tb JOIN {self.table_name} tc ON {equal_string} "
+                 f"GROUP BY {group_order_string} ORDER BY {group_order_string};")
+        return self.cursor.execute(query).fetchall()
+
+    def _get_rows_test_backend_ops(self, properties: list[str], hexsha8_baseline: str, hexsha8_compare: str) -> Sequence[tuple]:
+        # For test-backend-ops, we compare FLOPS and bandwidth metrics (prioritizing FLOPS over bandwidth)
+        select_string = ", ".join(
+            [f"tb.{p}" for p in properties] + [
+                "AVG(tb.flops)", "AVG(tc.flops)",
+                "AVG(tb.bandwidth_gb_s)", "AVG(tc.bandwidth_gb_s)"
+            ])
+        equal_string = " AND ".join(
+            [f"tb.{p} = tc.{p}" for p in TEST_BACKEND_OPS_KEY_PROPERTIES] + [
+                f"tb.build_commit = '{hexsha8_baseline}'", f"tc.build_commit = '{hexsha8_compare}'",
+                "tb.supported = 1", "tc.supported = 1", "tb.passed = 1", "tc.passed = 1"]  # Only compare successful tests
+        )
+        group_order_string = ", ".join([f"tb.{p}" for p in properties])
+        query = (f"SELECT {select_string} FROM {self.table_name} tb JOIN {self.table_name} tc ON {equal_string} "
                  f"GROUP BY {group_order_string} ORDER BY {group_order_string};")
         return self.cursor.execute(query).fetchall()
 
 
 class LlamaBenchDataSQLite3File(LlamaBenchDataSQLite3):
-    def __init__(self, data_file: str):
-        super().__init__()
+    def __init__(self, data_file: str, tool: Any):
+        super().__init__(tool)
 
         self.connection.close()
         self.connection = sqlite3.connect(data_file)
         self.cursor = self.connection.cursor()
+
+        # Check which table exists in the database
+        tables = self.cursor.execute("SELECT name FROM sqlite_master WHERE type='table';").fetchall()
+        table_names = [table[0] for table in tables]
+
+        # Tool selection logic
+        if tool is None:
+            if "test" in table_names:
+                self.table_name = "test"
+                self.tool = "llama-bench"
+            elif "test_backend_ops" in table_names:
+                self.table_name = "test_backend_ops"
+                self.tool = "test-backend-ops"
+            else:
+                raise RuntimeError(f"No suitable table found in database. Available tables: {table_names}")
+        elif tool == "llama-bench":
+            if "test" in table_names:
+                self.table_name = "test"
+                self.tool = "llama-bench"
+            else:
+                raise RuntimeError(f"Table 'test' not found for tool 'llama-bench'. Available tables: {table_names}")
+        elif tool == "test-backend-ops":
+            if "test_backend_ops" in table_names:
+                self.table_name = "test_backend_ops"
+                self.tool = "test-backend-ops"
+            else:
+                raise RuntimeError(f"Table 'test_backend_ops' not found for tool 'test-backend-ops'. Available tables: {table_names}")
+        else:
+            raise RuntimeError(f"Unknown tool: {tool}")
+
         self._builds_init()
 
     @staticmethod
@@ -317,20 +451,23 @@ def valid_format(data_file: str) -> bool:
 
 
 class LlamaBenchDataJSONL(LlamaBenchDataSQLite3):
-    def __init__(self, data_file: str):
-        super().__init__()
+    def __init__(self, data_file: str, tool: str = "llama-bench"):
+        super().__init__(tool)
+
+        # Get the appropriate field list based on tool
+        db_fields = LLAMA_BENCH_DB_FIELDS if tool == "llama-bench" else TEST_BACKEND_OPS_DB_FIELDS
 
         with open(data_file, "r", encoding="utf-8") as fp:
             for i, line in enumerate(fp):
                 parsed = json.loads(line)
 
-                for k in parsed.keys() - set(DB_FIELDS):
+                for k in parsed.keys() - set(db_fields):
                     del parsed[k]
 
                 if (missing_keys := self._check_keys(parsed.keys())):
                     raise RuntimeError(f"Missing required data key(s) at line {i + 1}: {', '.join(missing_keys)}")
 
-                self.cursor.execute(f"INSERT INTO test({', '.join(parsed.keys())}) VALUES({', '.join('?' * len(parsed))});", tuple(parsed.values()))
+                self.cursor.execute(f"INSERT INTO {self.table_name}({', '.join(parsed.keys())}) VALUES({', '.join('?' * len(parsed))});", tuple(parsed.values()))
 
         self._builds_init()
 
@@ -349,21 +486,24 @@ def valid_format(data_file: str) -> bool:
 
 
 class LlamaBenchDataJSON(LlamaBenchDataSQLite3):
-    def __init__(self, data_files: list[str]):
-        super().__init__()
+    def __init__(self, data_files: list[str], tool: str = "llama-bench"):
+        super().__init__(tool)
+
+        # Get the appropriate field list based on tool
+        db_fields = LLAMA_BENCH_DB_FIELDS if tool == "llama-bench" else TEST_BACKEND_OPS_DB_FIELDS
 
         for data_file in data_files:
             with open(data_file, "r", encoding="utf-8") as fp:
                 parsed = json.load(fp)
 
                 for i, entry in enumerate(parsed):
-                    for k in entry.keys() - set(DB_FIELDS):
+                    for k in entry.keys() - set(db_fields):
                         del entry[k]
 
                     if (missing_keys := self._check_keys(entry.keys())):
                         raise RuntimeError(f"Missing required data key(s) at entry {i + 1}: {', '.join(missing_keys)}")
 
-                    self.cursor.execute(f"INSERT INTO test({', '.join(entry.keys())}) VALUES({', '.join('?' * len(entry))});", tuple(entry.values()))
+                    self.cursor.execute(f"INSERT INTO {self.table_name}({', '.join(entry.keys())}) VALUES({', '.join('?' * len(entry))});", tuple(entry.values()))
 
         self._builds_init()
 
@@ -384,21 +524,24 @@ def valid_format(data_files: list[str]) -> bool:
 
 
 class LlamaBenchDataCSV(LlamaBenchDataSQLite3):
-    def __init__(self, data_files: list[str]):
-        super().__init__()
+    def __init__(self, data_files: list[str], tool: str = "llama-bench"):
+        super().__init__(tool)
+
+        # Get the appropriate field list based on tool
+        db_fields = LLAMA_BENCH_DB_FIELDS if tool == "llama-bench" else TEST_BACKEND_OPS_DB_FIELDS
 
         for data_file in data_files:
             with open(data_file, "r", encoding="utf-8") as fp:
                 for i, parsed in enumerate(csv.DictReader(fp)):
                     keys = set(parsed.keys())
 
-                    for k in keys - set(DB_FIELDS):
+                    for k in keys - set(db_fields):
                         del parsed[k]
 
                     if (missing_keys := self._check_keys(keys)):
                         raise RuntimeError(f"Missing required data key(s) at line {i + 1}: {', '.join(missing_keys)}")
 
-                    self.cursor.execute(f"INSERT INTO test({', '.join(parsed.keys())}) VALUES({', '.join('?' * len(parsed))});", tuple(parsed.values()))
+                    self.cursor.execute(f"INSERT INTO {self.table_name}({', '.join(parsed.keys())}) VALUES({', '.join('?' * len(parsed))});", tuple(parsed.values()))
 
         self._builds_init()
 
@@ -419,21 +562,90 @@ def valid_format(data_files: list[str]) -> bool:
         return True
 
 
+def format_flops(flops_value: float) -> str:
+    """Format FLOPS values with appropriate units for better readability."""
+    if flops_value == 0:
+        return "0.00"
+
+    # Define unit thresholds and names
+    units = [
+        (1e12, "T"),   # TeraFLOPS
+        (1e9, "G"),    # GigaFLOPS
+        (1e6, "M"),    # MegaFLOPS
+        (1e3, "k"),    # kiloFLOPS
+        (1, "")        # FLOPS
+    ]
+
+    for threshold, unit in units:
+        if abs(flops_value) >= threshold:
+            formatted_value = flops_value / threshold
+            if formatted_value >= 100:
+                return f"{formatted_value:.1f}{unit}"
+            else:
+                return f"{formatted_value:.2f}{unit}"
+
+    # Fallback for very small values
+    return f"{flops_value:.2f}"
+
+
+def format_flops_for_table(flops_value: float, target_unit: str) -> str:
+    """Format FLOPS values for table display without unit suffix (since unit is in header)."""
+    if flops_value == 0:
+        return "0.00"
+
+    # Define unit thresholds based on target unit
+    unit_divisors = {
+        "TFLOPS": 1e12,
+        "GFLOPS": 1e9,
+        "MFLOPS": 1e6,
+        "kFLOPS": 1e3,
+        "FLOPS": 1
+    }
+
+    divisor = unit_divisors.get(target_unit, 1)
+    formatted_value = flops_value / divisor
+
+    if formatted_value >= 100:
+        return f"{formatted_value:.1f}"
+    else:
+        return f"{formatted_value:.2f}"
+
+
+def get_flops_unit_name(flops_values: list) -> str:
+    """Determine the best FLOPS unit name based on the magnitude of values."""
+    if not flops_values or all(v == 0 for v in flops_values):
+        return "FLOPS"
+
+    # Find the maximum absolute value to determine appropriate unit
+    max_flops = max(abs(v) for v in flops_values if v != 0)
+
+    if max_flops >= 1e12:
+        return "TFLOPS"
+    elif max_flops >= 1e9:
+        return "GFLOPS"
+    elif max_flops >= 1e6:
+        return "MFLOPS"
+    elif max_flops >= 1e3:
+        return "kFLOPS"
+    else:
+        return "FLOPS"
+
+
 bench_data = None
 if len(input_file) == 1:
     if LlamaBenchDataSQLite3File.valid_format(input_file[0]):
-        bench_data = LlamaBenchDataSQLite3File(input_file[0])
+        bench_data = LlamaBenchDataSQLite3File(input_file[0], tool)
     elif LlamaBenchDataJSON.valid_format(input_file):
-        bench_data = LlamaBenchDataJSON(input_file)
+        bench_data = LlamaBenchDataJSON(input_file, tool)
     elif LlamaBenchDataJSONL.valid_format(input_file[0]):
-        bench_data = LlamaBenchDataJSONL(input_file[0])
+        bench_data = LlamaBenchDataJSONL(input_file[0], tool)
     elif LlamaBenchDataCSV.valid_format(input_file):
-        bench_data = LlamaBenchDataCSV(input_file)
+        bench_data = LlamaBenchDataCSV(input_file, tool)
 else:
     if LlamaBenchDataJSON.valid_format(input_file):
-        bench_data = LlamaBenchDataJSON(input_file)
+        bench_data = LlamaBenchDataJSON(input_file, tool)
     elif LlamaBenchDataCSV.valid_format(input_file):
-        bench_data = LlamaBenchDataCSV(input_file)
+        bench_data = LlamaBenchDataCSV(input_file, tool)
 
 if not bench_data:
     raise RuntimeError("No valid (or some invalid) input files found.")
@@ -504,12 +716,29 @@ def valid_format(data_files: list[str]) -> bool:
 
 name_compare = bench_data.get_commit_name(hexsha8_compare)
 
+# Get tool-specific configuration
+if tool == "llama-bench":
+    key_properties = LLAMA_BENCH_KEY_PROPERTIES
+    bool_properties = LLAMA_BENCH_BOOL_PROPERTIES
+    pretty_names = LLAMA_BENCH_PRETTY_NAMES
+    default_show = DEFAULT_SHOW_LLAMA_BENCH
+    default_hide = DEFAULT_HIDE_LLAMA_BENCH
+elif tool == "test-backend-ops":
+    key_properties = TEST_BACKEND_OPS_KEY_PROPERTIES
+    bool_properties = TEST_BACKEND_OPS_BOOL_PROPERTIES
+    pretty_names = TEST_BACKEND_OPS_PRETTY_NAMES
+    default_show = DEFAULT_SHOW_TEST_BACKEND_OPS
+    default_hide = DEFAULT_HIDE_TEST_BACKEND_OPS
+else:
+    assert False
+
 # If the user provided columns to group the results by, use them:
 if known_args.show is not None:
     show = known_args.show.split(",")
     unknown_cols = []
     for prop in show:
-        if prop not in KEY_PROPERTIES[:-3]:  # Last three values are n_prompt, n_gen, n_depth.
+        valid_props = key_properties if tool == "test-backend-ops" else key_properties[:-3]  # Exclude n_prompt, n_gen, n_depth for llama-bench
+        if prop not in valid_props:
             unknown_cols.append(prop)
     if unknown_cols:
         logger.error(f"Unknown values for --show: {', '.join(unknown_cols)}")
@@ -518,40 +747,62 @@ def valid_format(data_files: list[str]) -> bool:
     rows_show = bench_data.get_rows(show, hexsha8_baseline, hexsha8_compare)
 # Otherwise, select those columns where the values are not all the same:
 else:
-    rows_full = bench_data.get_rows(KEY_PROPERTIES, hexsha8_baseline, hexsha8_compare)
+    rows_full = bench_data.get_rows(key_properties, hexsha8_baseline, hexsha8_compare)
     properties_different = []
-    for i, kp_i in enumerate(KEY_PROPERTIES):
-        if kp_i in DEFAULT_SHOW or kp_i in ["n_prompt", "n_gen", "n_depth"]:
-            continue
-        for row_full in rows_full:
-            if row_full[i] != rows_full[0][i]:
-                properties_different.append(kp_i)
-                break
+
+    if tool == "llama-bench":
+        # For llama-bench, skip n_prompt, n_gen, n_depth from differentiation logic
+        check_properties = [kp for kp in key_properties if kp not in ["n_prompt", "n_gen", "n_depth"]]
+        for i, kp_i in enumerate(key_properties):
+            if kp_i in default_show or kp_i in ["n_prompt", "n_gen", "n_depth"]:
+                continue
+            for row_full in rows_full:
+                if row_full[i] != rows_full[0][i]:
+                    properties_different.append(kp_i)
+                    break
+    elif tool == "test-backend-ops":
+        # For test-backend-ops, check all key properties
+        for i, kp_i in enumerate(key_properties):
+            if kp_i in default_show:
+                continue
+            for row_full in rows_full:
+                if row_full[i] != rows_full[0][i]:
+                    properties_different.append(kp_i)
+                    break
+    else:
+        assert False
 
     show = []
-    # Show CPU and/or GPU by default even if the hardware for all results is the same:
-    if rows_full and "n_gpu_layers" not in properties_different:
-        ngl = int(rows_full[0][KEY_PROPERTIES.index("n_gpu_layers")])
 
-        if ngl != 99 and "cpu_info" not in properties_different:
-            show.append("cpu_info")
+    if tool == "llama-bench":
+        # Show CPU and/or GPU by default even if the hardware for all results is the same:
+        if rows_full and "n_gpu_layers" not in properties_different:
+            ngl = int(rows_full[0][key_properties.index("n_gpu_layers")])
 
-    show += properties_different
+            if ngl != 99 and "cpu_info" not in properties_different:
+                show.append("cpu_info")
 
-    index_default = 0
-    for prop in ["cpu_info", "gpu_info", "n_gpu_layers", "main_gpu"]:
-        if prop in show:
-            index_default += 1
-    show = show[:index_default] + DEFAULT_SHOW + show[index_default:]
-    for prop in DEFAULT_HIDE:
+        show += properties_different
+
+        index_default = 0
+        for prop in ["cpu_info", "gpu_info", "n_gpu_layers", "main_gpu"]:
+            if prop in show:
+                index_default += 1
+        show = show[:index_default] + default_show + show[index_default:]
+    elif tool == "test-backend-ops":
+        show = default_show + properties_different
+    else:
+        assert False
+
+    for prop in default_hide:
         try:
             show.remove(prop)
         except ValueError:
             pass
 
     # Add plot_x parameter to parameters to show if it's not already present:
     if known_args.plot:
-        for k, v in PRETTY_NAMES.items():
+        for k, v in pretty_names.items():
             if v == known_args.plot_x and k not in show:
                 show.append(k)
                 break
@@ -563,60 +814,120 @@ def valid_format(data_files: list[str]) -> bool:
     sys.exit(1)
 
 table = []
-for row in rows_show:
-    n_prompt = int(row[-5])
-    n_gen    = int(row[-4])
-    n_depth  = int(row[-3])
-    if n_prompt != 0 and n_gen == 0:
-        test_name = f"pp{n_prompt}"
-    elif n_prompt == 0 and n_gen != 0:
-        test_name = f"tg{n_gen}"
-    else:
-        test_name = f"pp{n_prompt}+tg{n_gen}"
-    if n_depth != 0:
-        test_name = f"{test_name}@d{n_depth}"
-    #           Regular columns    test name    avg t/s values              Speedup
-    #            VVVVVVVVVVVVV     VVVVVVVVV    VVVVVVVVVVVVVV              VVVVVVV
-    table.append(list(row[:-5]) + [test_name] + list(row[-2:]) + [float(row[-1]) / float(row[-2])])
+primary_metric = "FLOPS"  # Default to FLOPS for test-backend-ops
+
+if tool == "llama-bench":
+    # For llama-bench, create test names and compare avg_ts values
+    for row in rows_show:
+        n_prompt = int(row[-5])
+        n_gen    = int(row[-4])
+        n_depth  = int(row[-3])
+        if n_prompt != 0 and n_gen == 0:
+            test_name = f"pp{n_prompt}"
+        elif n_prompt == 0 and n_gen != 0:
+            test_name = f"tg{n_gen}"
+        else:
+            test_name = f"pp{n_prompt}+tg{n_gen}"
+        if n_depth != 0:
+            test_name = f"{test_name}@d{n_depth}"
+        #           Regular columns    test name    avg t/s values              Speedup
+        #            VVVVVVVVVVVVV     VVVVVVVVV    VVVVVVVVVVVVVV              VVVVVVV
+        table.append(list(row[:-5]) + [test_name] + list(row[-2:]) + [float(row[-1]) / float(row[-2])])
+elif tool == "test-backend-ops":
+    # Determine the primary metric by checking rows until we find one with valid data
+    if rows_show:
+        primary_metric = "FLOPS"  # Default to FLOPS
+        flops_values = []
+
+        # Collect all FLOPS values to determine the best unit
+        for sample_row in rows_show:
+            baseline_flops = float(sample_row[-4])
+            compare_flops = float(sample_row[-3])
+            baseline_bandwidth = float(sample_row[-2])
+
+            if baseline_flops > 0:
+                flops_values.extend([baseline_flops, compare_flops])
+            elif baseline_bandwidth > 0 and not flops_values:
+                primary_metric = "Bandwidth (GB/s)"
+
+        # If we have FLOPS data, determine the appropriate unit
+        if flops_values:
+            primary_metric = get_flops_unit_name(flops_values)
+
+    # For test-backend-ops, prioritize FLOPS > bandwidth for comparison
+    for row in rows_show:
+        # Extract metrics: flops, bandwidth_gb_s (baseline and compare)
+        baseline_flops = float(row[-4])
+        compare_flops = float(row[-3])
+        baseline_bandwidth = float(row[-2])
+        compare_bandwidth = float(row[-1])
+
+        # Determine which metric to use for comparison (prioritize FLOPS > bandwidth)
+        if baseline_flops > 0 and compare_flops > 0:
+            # Use FLOPS comparison (higher is better)
+            speedup = compare_flops / baseline_flops
+            baseline_str = format_flops_for_table(baseline_flops, primary_metric)
+            compare_str = format_flops_for_table(compare_flops, primary_metric)
+        elif baseline_bandwidth > 0 and compare_bandwidth > 0:
+            # Use bandwidth comparison (higher is better)
+            speedup = compare_bandwidth / baseline_bandwidth
+            baseline_str = f"{baseline_bandwidth:.2f}"
+            compare_str = f"{compare_bandwidth:.2f}"
+        else:
+            # Fallback if no valid data is available
+            baseline_str = "N/A"
+            compare_str = "N/A"
+            from math import nan
+            speedup = nan
+
+        table.append(list(row[:-4]) + [baseline_str, compare_str, speedup])
+else:
+    assert False
 
 # Some a-posteriori fixes to make the table contents prettier:
-for bool_property in BOOL_PROPERTIES:
+for bool_property in bool_properties:
     if bool_property in show:
         ip = show.index(bool_property)
         for row_table in table:
             row_table[ip] = "Yes" if int(row_table[ip]) == 1 else "No"
 
-if "model_type" in show:
-    ip = show.index("model_type")
-    for (old, new) in MODEL_SUFFIX_REPLACE.items():
-        for row_table in table:
-            row_table[ip] = row_table[ip].replace(old, new)
-
-if "model_size" in show:
-    ip = show.index("model_size")
-    for row_table in table:
-        row_table[ip] = float(row_table[ip]) / 1024 ** 3
-
-if "gpu_info" in show:
-    ip = show.index("gpu_info")
-    for row_table in table:
-        for gns in GPU_NAME_STRIP:
-            row_table[ip] = row_table[ip].replace(gns, "")
+if tool == "llama-bench":
+    if "model_type" in show:
+        ip = show.index("model_type")
+        for (old, new) in MODEL_SUFFIX_REPLACE.items():
+            for row_table in table:
+                row_table[ip] = row_table[ip].replace(old, new)
 
-        gpu_names = row_table[ip].split(", ")
-        num_gpus = len(gpu_names)
-        all_names_the_same = len(set(gpu_names)) == 1
-        if len(gpu_names) >= 2 and all_names_the_same:
-            row_table[ip] = f"{num_gpus}x {gpu_names[0]}"
+    if "model_size" in show:
+        ip = show.index("model_size")
+        for row_table in table:
+            row_table[ip] = float(row_table[ip]) / 1024 ** 3
 
-headers  = [PRETTY_NAMES[p] for p in show]
-headers += ["Test", f"t/s {name_baseline}", f"t/s {name_compare}", "Speedup"]
+    if "gpu_info" in show:
+        ip = show.index("gpu_info")
+        for row_table in table:
+            for gns in GPU_NAME_STRIP:
+                row_table[ip] = row_table[ip].replace(gns, "")
+
+            gpu_names = row_table[ip].split(", ")
+            num_gpus = len(gpu_names)
+            all_names_the_same = len(set(gpu_names)) == 1
+            if len(gpu_names) >= 2 and all_names_the_same:
+                row_table[ip] = f"{num_gpus}x {gpu_names[0]}"
+
+headers  = [pretty_names.get(p, p) for p in show]
+if tool == "llama-bench":
+    headers += ["Test", f"t/s {name_baseline}", f"t/s {name_compare}", "Speedup"]
+elif tool == "test-backend-ops":
+    headers += [f"{primary_metric} {name_baseline}", f"{primary_metric} {name_compare}", "Speedup"]
+else:
+    assert False
 
 if known_args.plot:
-    def create_performance_plot(table_data: list[list[str]], headers: list[str], baseline_name: str, compare_name: str, output_file: str, plot_x_param: str, log_scale: bool = False):
+    def create_performance_plot(table_data: list[list[str]], headers: list[str], baseline_name: str, compare_name: str, output_file: str, plot_x_param: str, log_scale: bool = False, tool_type: str = "llama-bench", metric_name: str = "t/s"):
         try:
-            import matplotlib.pyplot as plt
             import matplotlib
+            import matplotlib.pyplot as plt
             matplotlib.use('Agg')
         except ImportError as e:
             logger.error("matplotlib is required for --plot.")
@@ -627,7 +938,7 @@ def create_performance_plot(table_data: list[list[str]], headers: list[str], bas
         plot_x_label = plot_x_param
 
         if plot_x_param not in ["n_prompt", "n_gen", "n_depth"]:
-            pretty_name = PRETTY_NAMES.get(plot_x_param, plot_x_param)
+            pretty_name = LLAMA_BENCH_PRETTY_NAMES.get(plot_x_param, plot_x_param)
             if pretty_name in data_headers:
                 plot_x_index = data_headers.index(pretty_name)
                 plot_x_label = pretty_name
@@ -746,8 +1057,16 @@ def make_axes(num_groups, max_cols=2, base_size=(8, 4)):
 
             title = ', '.join(title_parts) if title_parts else "Performance comparison"
 
+            # Determine y-axis label based on tool type
+            if tool_type == "llama-bench":
+                y_label = "Tokens per second (t/s)"
+            elif tool_type == "test-backend-ops":
+                y_label = metric_name
+            else:
+                assert False
+
             ax.set_xlabel(plot_x_label, fontsize=12, fontweight='bold')
-            ax.set_ylabel('Tokens per second (t/s)', fontsize=12, fontweight='bold')
+            ax.set_ylabel(y_label, fontsize=12, fontweight='bold')
             ax.set_title(title, fontsize=12, fontweight='bold')
             ax.legend(loc='best', fontsize=10)
             ax.grid(True, alpha=0.3)
@@ -765,7 +1084,7 @@ def make_axes(num_groups, max_cols=2, base_size=(8, 4)):
         plt.savefig(output_file, dpi=300, bbox_inches='tight')
         plt.close()
 
-    create_performance_plot(table, headers, name_baseline, name_compare, known_args.plot, known_args.plot_x, known_args.plot_log_scale)
+    create_performance_plot(table, headers, name_baseline, name_compare, known_args.plot, known_args.plot_x, known_args.plot_log_scale, tool, primary_metric)
 
 print(tabulate( # noqa: NP100
     table,