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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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 L40S
Compare setup details (1 active)

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

DeepSeek

NVIDIA L40S · Strata

Tone: mixedNVIDIA hardware
prompt processing (prefill):
2200.0 tokens/s
quant:
IQ2_XS (GGUF)
codingagentic

User reports prefill reaching 2,200 tokens/s on a local DeepSeek deployment (DeepSeek 1017 IQ2_XS) on an L40S 48GB with 1TB RAM. Setup is a Sol-hacked custom engine built on Strata and Maya, with IQ2_XS weights. User says cold prefill was fast but short incremental prefill passes between agent tool calls were slow in Codex; adding those to the optimization metrics cut end-to-end task time by around 15% with decode speed unchanged.

Oct 27, 2026
Tone: positiveNVIDIA hardware
generation:
73.7 tokens/s
prompt processing (prefill):
1974.7 tokens/s
quant:
IQ1_M (GGUF)

User reports DeepSeek V4 Flash at 1974.7 t/s prefill and 73.7 t/s decode at 510K input on a single L40S 48GB, up from 1147.2 t/s prefill and 26.1 t/s decode with the official engine's auto settings. Setup is a modified Strata v0.2.6 build with IQ1_M weights, CPU experts kept on NUMA0 of dual EPYC 9754 with about 1TB system RAM, 16384-token prefill chunks, a 384MiB reconstructed-weight cache, and DSpark/MTP speculative decoding at a 0.15 confidence threshold. Decode peaks at 76.9 t/s at 32K input; the official engine with DSpark forced on reached 1278.4 t/s prefill and 22.9 t/s decode at 510K.

Oct 26, 2026
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Community benchmarks snapshot

Records by GPU

AMD Strix Halo 128GB317NVIDIA RTX 3090218NVIDIA RTX 5090168NVIDIA DGX Spark89NVIDIA RTX Pro 6000 Blackwell70NVIDIA RTX 5060 Ti 16GB69M5 Max 48GB67NVIDIA RTX 3060 12GB65AMD Radeon AI PRO R9700 32GB61NVIDIA RTX 409057

Records by model

2650 total
Qwen3.81249
Qwen3.6277
Gemma 4168
DeepSeek V4 Flash149
Qwen3.5118
Qwen375
other614

Records by engine

1952 total
llama.cpp999
vLLM203
Strata142
MLX106
Ollama82
other420

Use cases

coding 718agentic 456long-context 336tool-use 201vision 134summarization 61math 54creative-writing 46multilingual 28rp 13text-generation 9reasoning 3
coding718agentic456long-context336tool-use201vision134summarization61math54creative-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 27B702Qwen3.8 125B · 6B active486Qwen3.6 35B · 3B active187DeepSeek V4 Flash 284B · 13B active132Qwen3.6 27B79Gemma 4 26B · 4B active59DeepSeek V4.1 Flash 552B · 16B active47GLM-5.3 320B · 18B active44

Quants

Q4_K_M338UD-Q4_K_XL155NVFP4148Q8_01074-bit90IQ4_XS75Q4_K_XL74MXFP465IQ3_XXS62Q456