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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What runs on your hardware?

Pick your GPU or Mac, then read the speeds people reported on it, or estimate which models fit and how fast they run.

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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 V100 32GB
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: positiveNVIDIA hardware
generation:
201.0 tokens/s
quant:
AWQ (AWQ)
kv:
FP8
coding

User reports Qwen3.8 Flash-Next at 201 tok/s on 4x V100 32GB PCIe cards with no NVLink, for a single request of English code. Setup is ReVolta 0.1.2, a vLLM fork, with an AWQ quant, 512K context, FP8 KV cache with CPU offload, TP4 plus DCP2, and DFlash2 speculative decoding drafting 8-token blocks from incoai's DFlash2 checkpoint. The user says this may be the first DFlash run on Volta (SM70); the table also lists a 163 figure beside the 201 tok/s row.

Oct 23, 2026
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Community benchmarks snapshot

Records by GPU

AMD Strix Halo 128GB313NVIDIA RTX 3090217NVIDIA RTX 5090161NVIDIA DGX Spark87NVIDIA RTX Pro 6000 Blackwell70NVIDIA RTX 5060 Ti 16GB67M5 Max 48GB67NVIDIA RTX 3060 12GB63AMD Radeon AI PRO R9700 32GB61NVIDIA RTX 409054

Records by model

2583 total
Qwen3.81215
Qwen3.6274
Gemma 4165
DeepSeek V4 Flash148
Qwen3.5116
Qwen371
other594

Records by engine

1907 total
llama.cpp983
vLLM201
Strata131
MLX106
Ollama79
other407

Use cases

coding 685agentic 434long-context 323tool-use 189vision 126summarization 61math 51creative-writing 43multilingual 26rp 12text-generation 9reasoning 3
coding685agentic434long-context323tool-use189vision126summarization61math51creative-writing43

Median generation t/s by GPU

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

RTX 509073RTX 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 27B682Qwen3.8 125B · 6B active472Qwen3.6 35B · 3B active184DeepSeek V4 Flash 284B · 13B active131Qwen3.6 27B79Gemma 4 26B · 4B active59GLM-5.3 320B · 18B active42DeepSeek V4.1 Flash 552B · 16B active41

Quants

Q4_K_M332UD-Q4_K_XL153NVFP4144Q8_01054-bit87IQ4_XS75Q4_K_XL74MXFP465IQ3_XXS61Q454