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 Pro 64GB
Compare setup details (1 active)

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

Qwen3.8 27B

M5 Pro 64GB · Inco Splash · 4,096 ctx

Tone: positiveApple hardware
generation:
35.3 tokens/s
prompt processing (prefill):
528.9 tokens/s
quant:
Q8_0 (GGUF)

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 Qwen3.8 27B at 35.28 t/s decode and 528.91 t/s prefill on an M5 Pro 64GB Mac Mini. Setup is Splash with Q8_0 GGUF weights and 4k input prompts. User also compares llama.cpp, MLX, and Splash across several quants, and reports an M1 Max 64GB Splash run at 135.96 t/s decode and 915.01 t/s prefill. User settled on Splash with Q8_0 and is happy with the results.

Oct 6, 2026

Qwen3.8 27B

M5 Pro 64GB · Inco Splash

Tone: positiveApple hardware
generation:
50.0 tokens/s
quant:
UD-Q4_K_XL (GGUF)

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.

agentic

User reports Qwen3.8 27B at 50 t/s on an M5 Pro 64GB. Setup is Inco Splash with Unsloth UD-Q4_K_XL GGUF weights, run in an agentic setup. The user credits Splash's optimized kernels, speculative decoding, prefix cache and mixed-weight support, and calls it a breakthrough in local inference on Apple Silicon.

Sep 26, 2026

Qwen3.8 27B Splash-HQ

M5 Pro 64GB · Inco Splash · 262,144 ctx

Tone: positiveApple hardware
generation:
36.9 tokens/s
quant:
Q8 (Splash)

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.

mathcodinglong-context

User reports Qwen3.8 27B at 36.9 t/s average on an M5 Pro 64GB using the Splash engine with native 8-bit weights. Setup is Splash with speculative decoding, 27 GB native 8-bit model, evaluated at temperature 0.0 across five task domains; speeds range from 21.9 to 54.8 t/s. Context scaling tested to 190,016 tokens with decode speed staying between 21 and 33 t/s; cold prefill at 180k+ tokens takes 4-5 minutes.

Sep 21, 2026
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Community benchmarks snapshot

Records by GPU

AMD Strix Halo 128GB294NVIDIA RTX 3090190NVIDIA RTX 5090134NVIDIA DGX Spark77M5 Max 48GB65NVIDIA RTX Pro 6000 Blackwell62NVIDIA RTX 5060 Ti 16GB58NVIDIA RTX 3060 12GB54AMD Radeon AI PRO R9700 32GB50M4 Max 128GB49

Records by model

2211 total
Qwen3.81021
Qwen3.6238
DeepSeek V4 Flash147
Gemma 4144
Qwen3.597
Qwen353
other511

Records by engine

1645 total
llama.cpp875
vLLM189
MLX100
Strata70
Ollama62
other349

Use cases

coding 556agentic 357long-context 272tool-use 153vision 109summarization 53math 43creative-writing 37multilingual 23text-generation 9rp 8reasoning 3
coding556agentic357long-context272tool-use153vision109summarization53math43creative-writing37

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 309036RTX 5090 Laptop 24GB34RTX 409032V100 32GB31Radeon AI PRO R9700 32GB30RX 7800 XT 16GB30

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 27B566Qwen3.8 125B · 6B active371DeepSeek V4 Flash 284B · 13B active130Qwen3.6 35B · 3B active129Qwen3.6 27B72Gemma 4 26B · 4B active36GLM-5.3 320B · 18B active33DeepSeek V4.1 Flash 552B · 16B active28

Quants

Q4_K_M290UD-Q4_K_XL140NVFP4120Q8_0984-bit79Q4_K_XL71IQ4_XS70MXFP458IQ3_XXS52Q450