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: M4 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.

Tone: mixedApple hardware
generation:
43.0 tokens/s

User reports Qwen3.8 27B (abliterated) at ~43 tok/s on an M4 Max 128GB. Setup is mlx-serve 26.10.2 with MTP enabled; the 27B build is 16GB. The user also lists other abliterated models in their picker: Smart 35B at ~106 tok/s (24GB), Vision 27B at ~22 tok/s (15GB), Coder 80B at ~78 tok/s (49GB), DeepSeek-V4-Flash 284B at ~26 tok/s (75GB), and Flash-Next 125B at ~90 tok/s (77GB). They ask for suggestions on better packs and MTP or mlx-serve settings for this hardware.

Oct 17, 2026
Apple hardware
generation:
60.0 tokens/s
prompt processing (prefill):
730.0 tokens/s
quant:
mixed 4-8bit (MLX)
codingvisionlong-context

User reports Qwen3.8-Flash-Next at ~60 tok/s serial decode and ~730 tok/s prefill on an M4 Max 128GB. Setup is mlx-serve 26.8.11 with a mixed 4-bit/8-bit MLX pack, ~75 GB resident, prefix cache on, images included. With MTP enabled decode reaches 78 tok/s (+41% on code, a few percent slower on prose). A needle at 24.8k tokens was recovered with sparse attention engaged. The pack includes the MTP head and vision tower; the 51B n-gram table ships as a 32 GB mmapped file that is not resident. The author recommends a re-quantized iQ-MLX-4.7bpw version instead.

Oct 7, 2026
Tone: positiveApple hardware
generation:
73.8 tokens/s
quant:
Q4 (MLX)
codinglong-contextvision

User reports Qwen3.8 Flash-Next at 73.8 tok/s on an M4 Max with 128 GB unified memory. Setup is mlx-serve with Q4 affine routed experts, BF16 core and verification head, native MTP at depth 4, and the full 262,144-token context; the 51.2 GB n-gram lookup table streams from SSD. Matched warm workloads measured 71-74 tok/s for code and technical prose, with serial decode at 33.2 tok/s and a 2.22x MTP speedup. Long-context prefill reached 280.7 prompt tok/s at 248,445 tokens.

Oct 7, 2026
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Community benchmarks snapshot

Records by GPU

AMD Strix Halo 128GB305NVIDIA RTX 3090201NVIDIA RTX 5090144NVIDIA DGX Spark82M5 Max 48GB66NVIDIA RTX Pro 6000 Blackwell64NVIDIA RTX 5060 Ti 16GB63NVIDIA RTX 3060 12GB58AMD Radeon AI PRO R9700 32GB56M4 Max 128GB52

Records by model

2376 total
Qwen3.81101
Qwen3.6249
Gemma 4159
DeepSeek V4 Flash148
Qwen3.5106
Qwen370
other543

Records by engine

1760 total
llama.cpp925
vLLM191
MLX104
Strata100
Ollama69
other371

Use cases

coding 610agentic 385long-context 295tool-use 168vision 116summarization 57math 47creative-writing 40multilingual 26rp 10text-generation 9reasoning 3
coding610agentic385long-context295tool-use168vision116summarization57math47creative-writing40

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 27B592Qwen3.8 125B · 6B active423Qwen3.6 35B · 3B active140DeepSeek V4 Flash 284B · 13B active131Qwen3.6 27B72Gemma 4 26B · 4B active39GLM-5.3 320B · 18B active36DeepSeek V4.1 Flash 552B · 16B active30

Quants

Q4_K_M307UD-Q4_K_XL146NVFP4130Q8_01004-bit84IQ4_XS72Q4_K_XL71MXFP462IQ3_XXS58Q453