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tribunus-benchmarks

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Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
model: string
quantization: string
hardware: string
compile: struct<layers: int64, tensors: int64, compile_time_seconds: double, compiler_version: string>
  child 0, layers: int64
  child 1, tensors: int64
  child 2, compile_time_seconds: double
  child 3, compiler_version: string
backends: struct<primary: string, fallback: string, rejected: string>
  child 0, primary: string
  child 1, fallback: string
  child 2, rejected: string
benchmarks: struct<baseline: struct<tokens_per_second: int64, description: string>, arena_residency: struct<toke (... 244 chars omitted)
  child 0, baseline: struct<tokens_per_second: int64, description: string>
      child 0, tokens_per_second: int64
      child 1, description: string
  child 1, arena_residency: struct<tokens_per_second_range: list<item: int64>, description: string>
      child 0, tokens_per_second_range: list<item: int64>
          child 0, item: int64
      child 1, description: string
  child 2, speculation: struct<tokens_per_second_range: list<item: int64>, description: string>
      child 0, tokens_per_second_range: list<item: int64>
          child 0, item: int64
      child 1, description: string
  child 3, full_stack: struct<tokens_per_second: int64, min_tokens_per_second: int64, description: string>
      child 0, tokens_per_second: int64
      child 1, min_tokens_per_second: int64
      child 2, description: string
test_date: timestamp[s]
comparisons: list<item: struct<backend: string, status: string, per_op_latency_ms: double, fallback: bool, notes: (... 36 chars omitted)
  child 0, item: struct<backend: string, status: string, per_op_latency_ms: double, fallback: bool, notes: string, to (... 24 chars omitted)
      child 0, backend: string
      child 1, status: string
      child 2, per_op_latency_ms: double
      child 3, fallback: bool
      child 4, notes: string
      child 5, tokens_per_second: double
to
{'model': Value('string'), 'test_date': Value('timestamp[s]'), 'hardware': Value('string'), 'comparisons': List({'backend': Value('string'), 'status': Value('string'), 'per_op_latency_ms': Value('float64'), 'fallback': Value('bool'), 'notes': Value('string'), 'tokens_per_second': Value('float64')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              model: string
              quantization: string
              hardware: string
              compile: struct<layers: int64, tensors: int64, compile_time_seconds: double, compiler_version: string>
                child 0, layers: int64
                child 1, tensors: int64
                child 2, compile_time_seconds: double
                child 3, compiler_version: string
              backends: struct<primary: string, fallback: string, rejected: string>
                child 0, primary: string
                child 1, fallback: string
                child 2, rejected: string
              benchmarks: struct<baseline: struct<tokens_per_second: int64, description: string>, arena_residency: struct<toke (... 244 chars omitted)
                child 0, baseline: struct<tokens_per_second: int64, description: string>
                    child 0, tokens_per_second: int64
                    child 1, description: string
                child 1, arena_residency: struct<tokens_per_second_range: list<item: int64>, description: string>
                    child 0, tokens_per_second_range: list<item: int64>
                        child 0, item: int64
                    child 1, description: string
                child 2, speculation: struct<tokens_per_second_range: list<item: int64>, description: string>
                    child 0, tokens_per_second_range: list<item: int64>
                        child 0, item: int64
                    child 1, description: string
                child 3, full_stack: struct<tokens_per_second: int64, min_tokens_per_second: int64, description: string>
                    child 0, tokens_per_second: int64
                    child 1, min_tokens_per_second: int64
                    child 2, description: string
              test_date: timestamp[s]
              comparisons: list<item: struct<backend: string, status: string, per_op_latency_ms: double, fallback: bool, notes: (... 36 chars omitted)
                child 0, item: struct<backend: string, status: string, per_op_latency_ms: double, fallback: bool, notes: string, to (... 24 chars omitted)
                    child 0, backend: string
                    child 1, status: string
                    child 2, per_op_latency_ms: double
                    child 3, fallback: bool
                    child 4, notes: string
                    child 5, tokens_per_second: double
              to
              {'model': Value('string'), 'test_date': Value('timestamp[s]'), 'hardware': Value('string'), 'comparisons': List({'backend': Value('string'), 'status': Value('string'), 'per_op_latency_ms': Value('float64'), 'fallback': Value('bool'), 'notes': Value('string'), 'tokens_per_second': Value('float64')})}
              because column names don't match

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Tribunus Benchmarks

Research data from the Tribunus Compute inference engine. Includes benchmark results, backend comparison data, TurboQuant KV cache compression analysis, ComputeImage compile manifests, and evidence receipts.

Methodology

All benchmarks run on Apple Silicon (M1 Max, 64GB) running macOS 26.5.

Model: Qwen2.5 0.5B Instruct (NF4 quantized)
Temperature: 0.0 (greedy)
Tokens: variable (50-512 per run)
Warm-up: 3 runs before measurement
Report: throughput (tok/s), time-to-first-token (TTFT), latency distribution

Hardware

Component	Detail
SoC	Apple M1 Max
RAM	64GB unified
GPU	32-core Metal GPU
ANE	16-core Neural Engine
OS	macOS 26.5
MLX	0.31.2 (tribunus fork)

Datasets

benchmarks/qwen2.5-0.5b.json — Throughput, TTFT, latency distribution
benchmarks/backend-comparison.json — MLX GPU vs Accelerate CPU vs Core ML ANE
compute-images/manifest-qwen2.5-0.5b.json — NF4 quantized, 24 layers, 556 tensors
evidence/receipt-samples.json — Sample receipt data from inference runs

Results Summary

Phase	tok/s	Notes
Baseline	65	Custom MLX-heavy runtime with heterogeneous scaffolding
Arena/residency	100-160	Zero-copy arena, paged residency
Speculation active	180-280	Speculative decode with ANE draft
Full stack	300+	Draft model, verifier batching, KV transactions

Citation

@software{tribunus_compute_2025,
  author = {Julian Torr},
  title = {Tribunus Compute Benchmarks},
  year = {2025},
  url = {https://huggingface.co/datasets/Tribunus-dev/tribunus-benchmarks}
}

License

AGPL-3.0

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