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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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 32GB
Compare setup details

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

LLaMA family 7B / Q4_0 / Mac mini M4 Metal b1550 / PP512 TG128 / exact base and artifact unknown

M4 32GB · llama.cpp b1550 (8e672efe) / Metal

Apple hardware
generation:
24.1 tokens/s
prompt processing (prefill):
221.3 tokens/s
quant:
Q4_0 (GGUF)

User reports LLaMA-family 7B at 24.1 t/s generation and 221.3 t/s prompt processing on a Mac mini M4 with 32 GB unified RAM. Setup is llama.cpp build 1550 with Q4_0 and F16 KV cache, Metal backend at ngl 99 on one GPU. The figures are llama-bench PP512 and TG128 synthetic tests, not a 512-token prompt followed by a 128-token answer; exact source rates are 221.29 and 24.11 t/s.

Oct 13, 2026

LLaMA family 7B / Q8_0 / Mac mini M4 Metal b1550 / PP512 TG128 / exact base and artifact unknown

M4 32GB · llama.cpp b1550 (8e672efe) / Metal

Apple hardware
generation:
13.5 tokens/s
prompt processing (prefill):
223.6 tokens/s
quant:
Q8_0 (GGUF)

User reports LLaMA-family 7B mostly Q8_0 at 13.5 t/s generation and 223.6 t/s prompt processing on a Mac mini M4 with 32 GB unified RAM. Setup is llama.cpp build 1550 with Q8_0 and F16 KV cache, Metal backend at ngl 99, one GPU. The figures are llama-bench PP512 and TG128, independent synthetic prompt and generation tests rather than a 512-token prompt followed by a 128-token answer.

Oct 13, 2026

LLaMA family 7B / F16 / Mac mini M4 Metal b1550 / PP512 TG128 / exact base and artifact unknown

M4 32GB · llama.cpp b1550 (8e672efe) / Metal

Apple hardware
generation:
7.4 tokens/s
prompt processing (prefill):
230.2 tokens/s
quant:
F16 (GGUF)

User reports a LLaMA-family 7B model at 7.4 t/s generation and 230.2 t/s prompt processing on a Mac mini M4 with 32 GB unified RAM. Setup is llama.cpp build 1550 with F16 quantization and F16 KV cache, Metal backend at ngl 99, one GPU. The figures are llama-bench PP512 and TG128 results, independent synthetic prompt and generation tests rather than a 512-token prompt followed by a 128-token answer; exact source rates are 230.18 ± 0.16 t/s and 7.43 ± 0.02 t/s.

Oct 13, 2026

Qwen3 8B

M4 32GB · llama.cpp

Apple hardware
generation:
19.7 tokens/s
prompt processing (prefill):
223.8 tokens/s
quant:
Q4_K_M (GGUF)

User reports Qwen3 8B at 19.7 t/s generation and 223.8 t/s prompt processing on a Mac mini M4 with 32 GB unified memory. Setup is llama.cpp b10929 with the Q4_K_M GGUF and Metal, all layers on the GPU, four CPU threads. The figures are separate llama-bench tests (pp512 and tg128), each the mean of three repetitions at zero initial depth, not one 512-input/128-output request; at 8192 prefill depth generation is 16.1 t/s.

Oct 13, 2026

Qwen3 4B

M4 32GB · llama.cpp

Apple hardware
generation:
36.2 tokens/s
prompt processing (prefill):
416.6 tokens/s
quant:
Q4_K_M (GGUF)

User reports Qwen3 4B at 36.2 t/s generation and 416.6 t/s prompt processing on a Mac mini M4 with 32 GB unified memory. Setup is llama.cpp b10929 with the Q4_K_M GGUF and Metal, all layers on the 10-core integrated GPU. The figures are separate llama-bench tests, pp512 and tg128, each the mean of three repetitions at zero initial depth, not one 512-input/128-output request.

Oct 13, 2026

Gemma 4 31B

M4 32GB · Ollama · 4,096 ctx

Apple hardware
generation:
5.3 tokens/s
prompt processing (prefill):
90.0 tokens/s
quant:
Q4_K_M (GGUF)

User reports Gemma 4 31B at 5.3 t/s generation and 90 t/s prompt processing on an M4 32GB Mac mini. Setup is Ollama 0.30.5 with GGUF Q4_K_M and num_ctx=4096, 100% GPU offload, 20.29 GB loaded memory including KV cache. The figures are three-run averages from a fixed Chinese long-form prompt; 4096 is the configured context, not measured input length, and per-run counters are unpublished.

Oct 13, 2026

Gemma 4 26B (4B active)

M4 32GB · Ollama · 4,096 ctx

Apple hardware
generation:
32.0 tokens/s
prompt processing (prefill):
657.0 tokens/s
quant:
Q4_K_M (GGUF)

User reports Gemma 4 26B-A4B at 32 t/s generation and 657 t/s prompt processing on an M4 32GB Mac mini. Setup is Ollama 0.30.5 with GGUF Q4_K_M and num_ctx=4096, 100% GPU offload, 17.37 GB loaded memory including KV cache. Both figures are three-run averages; the 400-character prompt instruction is not an output-token count, and 4096 is the configured context, not measured input length.

Oct 13, 2026

Gemma 4 12B

M4 32GB · Ollama · 4,096 ctx

Apple hardware
generation:
12.5 tokens/s
prompt processing (prefill):
236.0 tokens/s
quant:
Q4_K_M (GGUF)

User reports Gemma 4 12B at 12.5 t/s generation and 236 t/s prompt processing on an Apple Mac mini M4 with 32 GB unified memory. Setup is Ollama 0.30.5 with GGUF Q4_K_M and num_ctx=4096, reporting 100% GPU offload and 8.05 GB loaded memory including KV cache. Both figures are three-run averages; the 4096 is the configured context, not measured input length, and the prompt asks for at least 400 Chinese characters.

Oct 13, 2026

Gemma 4 8B E4B

M4 32GB · Ollama · 4,096 ctx

Apple hardware
generation:
29.9 tokens/s
prompt processing (prefill):
566.0 tokens/s
quant:
Q4_K_M (GGUF)

User reports Gemma 4 E4B at 29.9 t/s generation and 566 t/s prompt processing on an Apple Mac mini M4 with 32 GB unified memory. Setup is Ollama 0.30.5 with GGUF Q4_K_M at num_ctx=4096, with 100% GPU offload and 9.55 GB loaded memory including KV cache. The figures are source-reported three-run averages, with decode from eval_count/eval_duration and prompt processing from prompt_eval_count/prompt_eval_duration, excluding client and model-loading overhead.

Oct 13, 2026

Gemma 4 5.1B E2B

M4 32GB · Ollama · 4,096 ctx

Apple hardware
generation:
55.0 tokens/s
prompt processing (prefill):
1089.0 tokens/s
quant:
Q4_K_M (GGUF)

User reports Gemma 4 E2B at 55 t/s generation and 1089 t/s prompt processing on an Apple Mac mini M4 with 32 GB unified memory. Setup is Ollama 0.30.5 with GGUF Q4_K_M at num_ctx=4096 and 100% GPU offload, using the Ollama library gemma4:e2b tag. The figures are a three-run average (54.97 t/s decode, 1089 t/s prompt) from a fixed Chinese long-form prompt; reported loaded memory is 7.06 GB including KV cache.

Oct 13, 2026

Gemma 4 12B

M4 32GB · Ollama · 8,192 ctx

Apple hardware
generation:
8.7 tokens/s
prompt processing (prefill):
110.4 tokens/s
quant:
Q4_K_M (GGUF)
kv:
Q8
flash attention:
on

User reports Gemma 4 12B at 8.7 t/s generation and 110.4 t/s prompt processing on an M4 32GB Mac mini. Setup is Ollama 0.30.5 with Q4_K_M and q8_0 KV cache, num_ctx=8192, flash attention enabled, one card. The row is the first long-context tier: 5713 actual input tokens and 512 actual output tokens, not a full 8192-token prompt or an average. The source TTFT estimate is 64.5 s and request wall time 123.4 s.

Oct 13, 2026

Gemma 4 8B E4B

M4 32GB · Ollama · 8,192 ctx

Apple hardware
generation:
16.7 tokens/s
prompt processing (prefill):
245.5 tokens/s
quant:
Q4_K_M (GGUF)
kv:
Q8
flash attention:
on

User reports Gemma 4 E4B at 16.7 t/s generation and 245.5 t/s prompt processing on an M4 32GB Mac mini. Setup is Ollama 0.30.5 with Q4_K_M and q8_0 KV cache at 8192 context, one Mac mini M4 with 32 GB unified memory. The figure is a single long-context row with 5709 actual input and 505 actual output tokens, not an average or a full 8192-token prompt; the source TTFT estimate is 23.53 s.

Oct 13, 2026
Tone: positiveApple hardware
generation:
8.0 tokens/s

User asks about an MTP or DFlash head for Qwen 3.8 27B, and mentions 35B-A3B as a daily driver. User reports about 8 tok/s for Qwen 3.6 27B with MTP on 32 GB of unified memory.

Sep 7, 2026
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Community benchmarks snapshot

Records by GPU

AMD Strix Halo 128GB318NVIDIA RTX 3090219NVIDIA RTX 5090169NVIDIA DGX Spark91NVIDIA RTX 5060 Ti 16GB72NVIDIA RTX Pro 6000 Blackwell70M5 Max 48GB67NVIDIA RTX 3060 12GB65AMD Radeon AI PRO R9700 32GB63NVIDIA RTX 409057

Records by model

2687 total
Qwen3.81268
Qwen3.6282
Gemma 4168
DeepSeek V4 Flash149
Qwen3.5121
Qwen375
other624

Records by engine

1974 total
llama.cpp1007
vLLM205
Strata148
MLX106
Ollama83
other425

Use cases

coding 731agentic 465long-context 340tool-use 207vision 134summarization 61math 57creative-writing 46multilingual 29rp 13text-generation 9reasoning 3
coding731agentic465long-context340tool-use207vision134summarization61math57creative-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 27B709Qwen3.8 125B · 6B active496Qwen3.6 35B · 3B active192DeepSeek V4 Flash 284B · 13B active132Qwen3.6 27B79Gemma 4 26B · 4B active59DeepSeek V4.1 Flash 552B · 16B active48GLM-5.3 320B · 18B active45

Quants

Q4_K_M341UD-Q4_K_XL156NVFP4148Q8_01074-bit91IQ4_XS76Q4_K_XL74MXFP466IQ3_XXS65IQ3_S58