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.

Free to use. No account needed. Memory estimates and community measurements are labelled separately.

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Search for a model to see its reported speeds across GPUs and Macs.

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 RTX 4070
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: negativeNVIDIA hardware
generation:
28.7 tokens/s
quant:
Q3_K_P (GGUF)
kv:
q8_0

User reports Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive at 28.74 t/s generation on an RTX 4070 with a Ryzen 7 7700X and 32GB DDR5, roughly half the speed they get from llama.cpp. Setup is ik_llama.cpp with a Q3_K_P GGUF, q8_0 KV cache, 131072 context, and 12 threads; the same command under llama.cpp gave 63.82 t/s generation and 70.52 t/s prompt eval. The user is asking what could be done about the shortfall.

Oct 4, 2026
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Community benchmarks snapshot

Records by GPU

AMD Strix Halo 128GB320NVIDIA RTX 3090219NVIDIA RTX 5090170NVIDIA DGX Spark91NVIDIA RTX 5060 Ti 16GB72NVIDIA RTX Pro 6000 Blackwell71M5 Max 48GB67NVIDIA RTX 3060 12GB65AMD Radeon AI PRO R9700 32GB63NVIDIA RTX 409057

Records by model

2704 total
Qwen3.81276
Qwen3.6284
Gemma 4168
DeepSeek V4 Flash149
Qwen3.5121
Qwen375
other631

Records by engine

1985 total
llama.cpp1009
vLLM206
Strata151
MLX107
Ollama84
other428

Use cases

coding 739agentic 468long-context 343tool-use 208vision 140summarization 61math 58creative-writing 46multilingual 29rp 13text-generation 9reasoning 3
coding739agentic468long-context343tool-use208vision140summarization61math58creative-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 27B710Qwen3.8 125B · 6B active502Qwen3.6 35B · 3B active193DeepSeek V4 Flash 284B · 13B active132Qwen3.6 27B80Gemma 4 26B · 4B active59DeepSeek V4.1 Flash 552B · 16B active50GLM-5.3 320B · 18B active45

Quants

Q4_K_M342UD-Q4_K_XL157NVFP4149Q8_01074-bit92IQ4_XS76Q4_K_XL74IQ3_XXS66MXFP466IQ3_S59