- generation:
- 16.1 tokens/s
- quant:
- Q8_K_XL (GGUF)
User reports all experts on CPU with only 15.8 GB of 40 GB VRAM used.
Local model performance on your hardware
Find which open-weight LLMs fit in your GPU or Mac and compare the speeds people report on setups like yours.
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Local model performance reports from the community
These are individual setups, not a controlled benchmark. Compare GPU count, quantization, context and offloading before comparing speeds. How to read a report →
GPU: NVIDIA A100 40GB
Compare setup details (1 active)
Exact recorded values. Context may be a configured limit; matching filters does not establish identical prompts, offloading or concurrency.
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Community benchmarks snapshot
Records by GPU
Records by model
Qwen3.81272
Qwen3.6284
Gemma 4168
DeepSeek V4 Flash149
Qwen3.5121
Qwen375
other629
Records by engine
llama.cpp1008
vLLM205
Strata150
MLX106
Ollama83
other428
Use cases
coding 737agentic 466long-context 342tool-use 207vision 137summarization 61math 57creative-writing 46multilingual 29rp 13text-generation 9reasoning 3
Median generation t/s by GPU
On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking