llamaperf

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: M2 Max 96GB
Compare setup details (1 active)

Exact recorded values. Context may be a configured limit; matching filters does not establish identical prompts, offloading or concurrency.

Tone: mixedApple hardware
generation:
20.1 tokens/s
quant:
4bit (MLX)

User benchmarks Qwen3.8 27B 4-bit on an M2 Max 96GB, comparing mlx-serve with MTP speculative decoding against LM Studio. With the MTP head correctly loaded, mlx-serve reaches 20.1 t/s decode on long prompts and 13.0 t/s on short, versus 11.2 and 8.0 t/s without speculation. Setup is mlx-serve 26.9.5 with MLX 0.32.2 on macOS 26.6.2, using the mlx-community Qwen3.8-27B-MTP-4bit sidecar. Prefill measured 49/145 tok/s with MTP loaded and 47/112 tok/s without. LM Studio on the same weights reached 11.8 t/s decode short and 11.6 t/s long, with 59/101 tok/s prefill. The user reports that mlx-serve silently falls back to Prompt Lookup Decoding when the MTP sidecar tensors lack the required mtp. prefix, and that MoE MTP heads fail to load entirely, so Qwen3.6-35B-A3B got no speedup. Numbers are client-side medians of 5 runs with unique prefixes to avoid prefix caching.

Sep 23, 2026
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Community benchmarks snapshot

Records by GPU

AMD Strix Halo 128GB318NVIDIA RTX 3090219NVIDIA RTX 5090170NVIDIA DGX Spark91NVIDIA RTX 5060 Ti 16GB72NVIDIA RTX Pro 6000 Blackwell70M5 Max 48GB67NVIDIA RTX 3060 12GB65AMD Radeon AI PRO R9700 32GB63NVIDIA RTX 409057

Records by model

2692 total
Qwen3.81270
Qwen3.6282
Gemma 4168
DeepSeek V4 Flash149
Qwen3.5121
Qwen375
other627

Records by engine

1976 total
llama.cpp1007
vLLM205
Strata149
MLX106
Ollama83
other426

Use cases

coding 733agentic 466long-context 341tool-use 207vision 134summarization 61math 57creative-writing 46multilingual 29rp 13text-generation 9reasoning 3
coding733agentic466long-context341tool-use207vision134summarization61math57creative-writing46

Median generation t/s by GPU

On Qwen3.8 27B at 4-bit, plain single-GPU runs. Full ranking

RTX 509080RTX Pro 600067M5 Ultra 256GB50RX 7900 XTX43RTX 409040RTX 309038RX 7800 XT 16GB35RTX 5090 Laptop 24GB34M3 Ultra 512GB32V100 32GB31

Prompt processing, same model

M5 Ultra 256GB1800RX 7900 XTX640RTX 40901949RTX 3090561M3 Ultra 512GB391V100 32GB941Radeon AI PRO R9700 32GB1287RTX 3080 20GB997Arc Pro B70512M1 Ultra 128GB153

Reports by model size

Qwen3.8 27B709Qwen3.8 125B · 6B active498Qwen3.6 35B · 3B active192DeepSeek V4 Flash 284B · 13B active132Qwen3.6 27B79Gemma 4 26B · 4B active59DeepSeek V4.1 Flash 552B · 16B active48GLM-5.3 320B · 18B active45

Quants

Q4_K_M341UD-Q4_K_XL156NVFP4148Q8_01074-bit91IQ4_XS76Q4_K_XL74MXFP466IQ3_XXS65IQ3_S59