llama.cpp with Clover support (clover_moe)
Prebuilt Clover runtime by IsValorum
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Prebuilt Linux and Windows x86_64 binaries for Diffuspace/Clover-35B-A3B-Preview, built from llama.cpp PR #31306 at commit 4838ffb0c8ade92f34d9157deea38d92758ab824.
Mainline llama.cpp does not load clover_moe. This build adds the converter, the runtime graph and the draft-self speculative mode. The PR is not merged upstream; pin this repository for reproducibility.
Clover artifacts for this runtime
| Artifact | Size | Link |
|---|---|---|
| BF16 source | 69.38 GB | Clover-35B-A3B-Preview-BF16-GGUF |
| Q8_0 | 36.91 GB | Clover-35B-A3B-Preview-Q8_0-GGUF |
| 1.25M I-Matrix | 383,689,280 bytes | Clover-35B-A3B-Preview-VAL-1.25M-I-Matrix-GGUF |
| APEX-I NanoPlus V2.1 | 12.56 GB / 11.70 GiB | Clover-35B-A3B-Preview-APEX-I-NanoPlus-V2.1-GGUF |
| APEX-I MiniPlus V2.1 | 14.75 GB / 13.74 GiB | Clover-35B-A3B-Preview-APEX-I-MiniPlus-V2.1-GGUF |
Files
| File | Description |
|---|---|
llama-clover-4838ffb-linux-x86_64-cpu.tar.gz |
Linux CPU build, GGML_NATIVE=OFF |
llama-clover-4838ffb-linux-x86_64-nvidia-cuda12.tar.gz |
CUDA 12 build, archs 80;86;89;90 |
llama-clover-4838ffb-converter-python.tar.gz |
HF-to-GGUF converter, conversion code and gguf-py |
llama-clover-4838ffb-windows-x86_64-nvidia-amd-universal-cuda12.8-vulkan-cpu.zip |
Windows x86_64 universal: Nvidia CUDA 12.8 sm_50-120, AMD/Intel Vulkan, any CPU |
BUILD_INFO.json |
Compiler, flags and SHA256 per archive |
SHA256SUMS |
Checksums |
config.json |
Machine-readable build descriptor used by Hub download tracking |
Coverage
| Platform | Target | Backend | Status |
|---|---|---|---|
| Linux x86_64 | Any x86-64 CPU | CPU, GGML_NATIVE=OFF |
shipped |
| Linux x86_64 | NVIDIA sm_80 / 86 / 89 / 90 (A100, A10G, L40S, RTX 4090, H100/H200) | CUDA 12.0 | shipped |
| Linux x86_64 | NVIDIA Blackwell sm_100/120, AMD, Intel | none | not in this build |
| Windows x86_64 | NVIDIA sm_50 through sm_120 (Maxwell to Blackwell) | CUDA 12.8 | shipped |
| Windows x86_64 | AMD and Intel GPUs | Vulkan 1.4.363 | shipped |
| Windows x86_64 | Any x86-64 CPU | per-CPU DLLs, AVX-512 off | shipped |
| macOS, ARM64, ROCm on any OS | - | none | not published |
Windows is native. The ZIP carries its CUDA 12.8 libraries and uses the Vulkan loader from the GPU driver; extract it and run set PATH=%~dp0bin;%PATH% from the archive root. It ships the same tool set as the Linux archives, including llama-speculative-simple, llama-quantize and llama-imatrix.
The Linux x86_64 archives require GLIBC_2.38 or newer, so Ubuntu 24.04 or equivalent is the safe baseline; older distributions need their own build. Anything outside the table above, including macOS and ARM64, needs a build from the same branch and commit.
Compatibility
- Model:
Diffuspace/Clover-35B-A3B-Preview(clover_moe). Works with the BF16 and Q8_0 GGUFs and with third-partyclover_moeGGUFs such as the IQ4_XS. It does not load the original safetensors. - Frontends: not LM Studio or Ollama. Clover needs this
clover_moeruntime until the PR merges upstream.
Usage
All runtime archives are dynamically linked and ship llama-cli, llama-server, llama-diffusion-cli, llama-quantize, llama-imatrix, and llama-perplexity. Point the loader at the bundled libraries before running. The archive names changed in this build; the extract directories kept their old names.
CPU:
tar -xzf llama-clover-4838ffb-linux-x86_64-cpu.tar.gz
cd llama-clover-b4838ffb-linux-x64-cpu
export LD_LIBRARY_PATH=$PWD/bin:$LD_LIBRARY_PATH
./bin/llama-cli -m clover-bf16.gguf -c 4096 -p "Hello"
CUDA 12:
tar -xzf llama-clover-4838ffb-linux-x86_64-nvidia-cuda12.tar.gz
cd llama-clover-b4838ffb-linux-x64-cuda12
export LD_LIBRARY_PATH=$PWD/bin:$LD_LIBRARY_PATH
./bin/llama-cli -m clover-bf16.gguf -ngl 99 -fa on -c 4096 -p "Hello"
./bin/llama-speculative-simple -m clover-bf16.gguf --spec-type draft-self --spec-draft-n-max 15 -ctk bf16 -ctv bf16 -n 128 -c 2048 -b 256 -ub 256 -ngl 99
Windows x86_64 (universal ZIP, no separate runtime install):
set PATH=%~dp0bin;%PATH%
llama-completion.exe -m Clover-35B-A3B-Preview.APEX-I-NanoPlus-V2.1.gguf -p "hi" -n 1 -c 128 -b 16 -ub 16 -ngl 8 -no-cnv
Run both lines from the extracted archive root. Drop -ngl 8 for CPU or Vulkan-only use; raise it to offload more layers on a large NVIDIA card.
Conversion
tar -xzf llama-clover-4838ffb-converter-python.tar.gz
python llama-clover-converter/llama.cpp/convert_hf_to_gguf.py Diffuspace/Clover-35B-A3B-Preview --outtype bf16 --outfile clover-bf16.gguf
Quantization and importance matrix
./bin/llama-quantize --allow-requantize clover-bf16.gguf clover-q8_0.gguf Q8_0
./bin/llama-imatrix -m clover-q8_0.gguf -f calibration.raw -o clover.imatrix.gguf --output-format gguf --process-output --no-ppl --no-escape -c 2048 -b 2048 -ub 2048 --chunks 611 -ngl 99
The APEX-I V2.1 releases were produced with this build: llama-quantize --imatrix Clover-VAL-1.25M-I-Matrix.gguf --tensor-type-file <recipe> clover-bf16.gguf <output> Q4_0 64. The recipes carry 853 lines, including the 120 block-diffusion tensors that must stay in F32.
Notes
The CUDA packages require a compatible NVIDIA driver and CUDA 12.x runtime; the Windows package bundles its CUDA 12.8 libraries and uses the Vulkan loader from the GPU driver. llama.cpp is MIT licensed; the Clover support is PR #31306 by Maphist0; the Clover weights are Apache-2.0, Copyright DiffuSpace and the Qwen team.
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Model tree for IsValorum/llama.cpp-clover-moe
Base model
Qwen/Qwen3.6-35B-A3B