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.

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.

Looking for a particular model?

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: M5 Max 128GB
Compare setup details (1 active)

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

Apple hardware
generation:
198.6 tokens/s
prompt processing (prefill):
3657.8 tokens/s
quant:
oQ5e

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is input throughput, not time to first token. Check the full setup before comparing.

User benchmarks Qwen3.6-35B-A3B at 198.6 tok/s generation and 3657.8 tok/s prompt processing on an M5 Max 128GB. Setup is oMLX 0.7.1dev2 with oQ5e quant, Lightning MTP speculative decoding, and TurboQuant off, at 1024-token prompt and 128-token generation. Splash engine reaches 182.0 tok/s generation and 6040.8 tok/s prompt processing on the same test; continuous batching at 4x reaches 275.2 tok/s aggregate generation. A second model, Qwen3.7-27B, is also benchmarked.

Oct 16, 2026
Apple hardware
generation:
8.4 tokens/s
quant:
oQ4e
mtp (multi-token prediction):
on

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is shown only when the source reports it; generation speed cannot tell us time to first token. Check the full setup before comparing.

User reports Qwen3.8 oQ4e-mtp restored-prefix B3 / PR1 61bd8a06 at 8.4 t/s on an M5 Max 128GB. Setup is oMLX with oQ4e 4-bit weights and TurboQuant 4-bit KV cache, three greedy requests batched at roughly 20k / 45k / 135k prompt tokens with SSD prefix cache enabled. The 8.4 t/s is the per-row rate at the 20k row, measured at 8.35 t/s; the other rows ran 8.83 and 7.84 t/s per row, and the batch phase took 66 seconds.

Oct 13, 2026
Apple hardware
generation:
36.1 tokens/s
prompt processing (prefill):
498.3 tokens/s
quant:
2.44bit-mixed (MLX)

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is input throughput, not time to first token. Check the full setup before comparing.

User reports DeepSeek V4 Flash 0731 at 36.1 t/s generation and 498.3 t/s prefill on a MacBook Pro M5 Max 128GB 40 GPU. Setup is oMLX 0.5.7 with a 2.44 bpw mixed MLX quantization (92.8 GB on disk) at 1k prompt, single request, 128 generated tokens, speculative decoding off. Generation holds 33.8 t/s at 4k and 31.5 t/s at 32k, with peak memory rising 1.03 GB across an 8x context jump; prefill at 32k takes 97 seconds to first token. Continuous batching reaches 83.2 t/s at batch 8 (2.30x).

Oct 9, 2026
Tone: negativeApple hardware
generation:
50-70 tokens/s
quant:
oQ5e (MLX)

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is shown only when the source reports it; generation speed cannot tell us time to first token. Check the full setup before comparing.

User reports Qwen3.8-Flash-Next at 50-70 t/s on an M5 Max 128GB after upgrading to macOS 27, down from 60-90 t/s on macOS 26. Setup is oMLX with oQ5e quantization. The user reports roughly 20% slower token generation after the OS upgrade and asks whether others see the same.

Sep 29, 2026
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Community benchmarks snapshot

Records by GPU

AMD Strix Halo 128GB303NVIDIA RTX 3090195NVIDIA RTX 5090140NVIDIA DGX Spark80M5 Max 48GB66NVIDIA RTX Pro 6000 Blackwell64NVIDIA RTX 5060 Ti 16GB61NVIDIA RTX 3060 12GB57AMD Radeon AI PRO R9700 32GB56M4 Max 128GB49

Records by model

2326 total
Qwen3.81081
Qwen3.6244
Gemma 4154
DeepSeek V4 Flash148
Qwen3.5102
Qwen370
other527

Records by engine

1730 total
llama.cpp910
vLLM189
MLX102
Strata93
Ollama68
other368

Use cases

coding 593agentic 378long-context 291tool-use 164vision 114summarization 55math 46creative-writing 39multilingual 25text-generation 9rp 9reasoning 3
coding593agentic378long-context291tool-use164vision114summarization55math46creative-writing39

Median generation t/s by GPU

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

RTX 509082RTX Pro 600067M5 Ultra 256GB50RX 7900 XTX48RTX 309036RX 7800 XT 16GB35RTX 5090 Laptop 24GB34RTX 409032V100 32GB31Radeon AI PRO R9700 32GB30

Prompt processing, same model

M5 Ultra 256GB1800RX 7900 XTX530RTX 3090561RTX 40901949V100 32GB941RTX 3080 20GB997Arc Pro B70512M1 Ultra 128GB153Arc Pro B60 24GB380M1 Max 32GB82

Reports by model size

Qwen3.8 27B586Qwen3.8 125B · 6B active411Qwen3.6 35B · 3B active135DeepSeek V4 Flash 284B · 13B active131Qwen3.6 27B72Gemma 4 26B · 4B active37GLM-5.3 320B · 18B active36DeepSeek V4.1 Flash 552B · 16B active29

Quants

Q4_K_M304UD-Q4_K_XL145NVFP4126Q8_0994-bit83IQ4_XS71Q4_K_XL71MXFP461IQ3_XXS58Q452