Quick Answer: Apple M3 Pro offers 36GB VRAM and starts around current market pricing. It delivers approximately 26 tokens/sec on unsloth/gemma-3-1b-it. It typically draws 30W under load.
This GPU offers reliable throughput for local AI workloads. Pair it with the right model quantization to hit your desired tokens/sec, and monitor prices below to catch the best deal.
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| Model | Quantization | Tokens/sec | VRAM used |
|---|---|---|---|
| unsloth/gemma-3-1b-it | Q4 | 26.39 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 26.28 tok/sEstimated Auto-generated benchmark | 2GB |
| deepseek-ai/DeepSeek-OCR | Q4 | 26.22 tok/sEstimated Auto-generated benchmark | 2GB |
| inference-net/Schematron-3B | Q4 | 26.22 tok/sEstimated Auto-generated benchmark | 2GB |
| google/embeddinggemma-300m | Q4 | 26.21 tok/sEstimated Auto-generated benchmark | 1GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 26.04 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 26.02 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-3-1b-it | Q4 | 25.92 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 25.89 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-research/PowerMoE-3b | Q4 | 25.48 tok/sEstimated Auto-generated benchmark | 2GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 25.12 tok/sEstimated Auto-generated benchmark | 1GB |
| allenai/OLMo-2-0425-1B | Q4 | 25.08 tok/sEstimated Auto-generated benchmark | 1GB |
| LiquidAI/LFM2-1.2B | Q4 | 24.90 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2b | Q4 | 24.83 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B | Q4 | 24.63 tok/sEstimated Auto-generated benchmark | 2GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 24.43 tok/sEstimated Auto-generated benchmark | 1GB |
| nari-labs/Dia2-2B | Q4 | 24.41 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 24.31 tok/sEstimated Auto-generated benchmark | 2GB |
| facebook/sam3 | Q4 | 24.30 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B | Q4 | 24.08 tok/sEstimated Auto-generated benchmark | 2GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 23.83 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 23.80 tok/sEstimated Auto-generated benchmark | 1GB |
| google-t5/t5-3b | Q4 | 23.55 tok/sEstimated Auto-generated benchmark | 2GB |
| google-bert/bert-base-uncased | Q4 | 23.54 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 22.83 tok/sEstimated Auto-generated benchmark | 2GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 22.83 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 22.81 tok/sEstimated Auto-generated benchmark | 1GB |
| tencent/HunyuanOCR | Q4 | 22.74 tok/sEstimated Auto-generated benchmark | 1GB |
| bigcode/starcoder2-3b | Q4 | 22.47 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B | Q4 | 22.31 tok/sEstimated Auto-generated benchmark | 1GB |
| black-forest-labs/FLUX.1-dev | Q4 | 22.13 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/Phi-3.5-mini-instruct | Q4 | 22.12 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-R1-Distill-Llama-8B | Q4 | 22.02 tok/sEstimated Auto-generated benchmark | 4GB |
| tencent/HunyuanVideo-1.5 | Q4 | 21.99 tok/sEstimated Auto-generated benchmark | 4GB |
| google/gemma-2-2b-it | Q4 | 21.93 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen3-8B-Base | Q4 | 21.91 tok/sEstimated Auto-generated benchmark | 4GB |
| unsloth/Meta-Llama-3.1-8B-Instruct | Q4 | 21.84 tok/sEstimated Auto-generated benchmark | 4GB |
| trl-internal-testing/tiny-LlamaForCausalLM-3.2 | Q4 | 21.82 tok/sEstimated Auto-generated benchmark | 4GB |
| Tongyi-MAI/Z-Image-Turbo | Q4 | 21.82 tok/sEstimated Auto-generated benchmark | 4GB |
| EleutherAI/gpt-neo-125m | Q4 | 21.77 tok/sEstimated Auto-generated benchmark | 4GB |
| black-forest-labs/FLUX.2-dev | Q4 | 21.77 tok/sEstimated Auto-generated benchmark | 4GB |
| distilbert/distilgpt2 | Q4 | 21.77 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-R1 | Q4 | 21.74 tok/sEstimated Auto-generated benchmark | 4GB |
| mistralai/Mistral-7B-Instruct-v0.1 | Q4 | 21.73 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-V3-0324 | Q4 | 21.66 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-V3.1 | Q4 | 21.63 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-7B-Instruct | Q4 | 21.62 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-0.6B | Q4 | 21.61 tok/sEstimated Auto-generated benchmark | 3GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 21.60 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-Math-1.5B | Q4 | 21.53 tok/sEstimated Auto-generated benchmark | 3GB |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
| Model | Quantization | Verdict | Estimated speed | VRAM needed |
|---|---|---|---|---|
| baichuan-inc/Baichuan-M2-32B | Q8 | Fits comfortably | 4.59 tok/sEstimated | 33GB (have 36GB) |
| baichuan-inc/Baichuan-M2-32B | FP16 | Not supported | 2.53 tok/sEstimated | 66GB (have 36GB) |
| unsloth/Llama-3.2-1B-Instruct | Q8 | Fits comfortably | 15.99 tok/sEstimated | 1GB (have 36GB) |
| mistralai/Mistral-Large-3-675B-Instruct-2512 | Q4 | Not supported | 2.37 tok/sEstimated | 378GB (have 36GB) |
| mistralai/Mistral-Large-3-675B-Instruct-2512 | Q8 | Not supported | 1.64 tok/sEstimated | 755GB (have 36GB) |
| mistralai/Mistral-Large-3-675B-Instruct-2512 | FP16 | Not supported | 0.91 tok/sEstimated | 1509GB (have 36GB) |
| EssentialAI/rnj-1 | Q4 | Fits comfortably | 13.61 tok/sEstimated | 5GB (have 36GB) |
| EssentialAI/rnj-1 | Q8 | Fits comfortably | 10.25 tok/sEstimated | 10GB (have 36GB) |
| EssentialAI/rnj-1 | FP16 | Fits comfortably | 5.68 tok/sEstimated | 19GB (have 36GB) |
| Qwen/Qwen2.5-7B-Instruct | Q4 | Fits comfortably | 21.49 tok/sEstimated | 4GB (have 36GB) |
| Qwen/Qwen3-0.6B | Q4 | Fits comfortably | 21.61 tok/sEstimated | 3GB (have 36GB) |
| Qwen/Qwen3-0.6B | Q8 | Fits comfortably | 13.18 tok/sEstimated | 6GB (have 36GB) |
| openai/gpt-oss-20b | FP16 | Not supported | 3.90 tok/sEstimated | 41GB (have 36GB) |
| google/gemma-3-1b-it | Q4 | Fits comfortably | 25.92 tok/sEstimated | 1GB (have 36GB) |
| Qwen/Qwen2.5-1.5B-Instruct | Q8 | Fits comfortably | 13.36 tok/sEstimated | 5GB (have 36GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | Fits comfortably | 25.12 tok/sEstimated | 1GB (have 36GB) |
| mistralai/Mistral-7B-Instruct-v0.2 | FP16 | Fits comfortably | 8.32 tok/sEstimated | 15GB (have 36GB) |
| petals-team/StableBeluga2 | Q4 | Fits comfortably | 18.97 tok/sEstimated | 4GB (have 36GB) |
| petals-team/StableBeluga2 | Q8 | Fits comfortably | 13.89 tok/sEstimated | 7GB (have 36GB) |
| petals-team/StableBeluga2 | FP16 | Fits comfortably | 7.00 tok/sEstimated | 15GB (have 36GB) |
| meta-llama/Llama-3.2-1B | Q4 | Fits comfortably | 22.31 tok/sEstimated | 1GB (have 36GB) |
| Qwen/Qwen2.5-7B | Q4 | Fits comfortably | 20.23 tok/sEstimated | 4GB (have 36GB) |
| Qwen/Qwen2.5-7B | Q8 | Fits comfortably | 13.27 tok/sEstimated | 7GB (have 36GB) |
| Qwen/Qwen2.5-7B | FP16 | Fits comfortably | 8.31 tok/sEstimated | 15GB (have 36GB) |
| Qwen/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 19.34 tok/sEstimated | 3GB (have 36GB) |
| Qwen/Qwen2.5-0.5B-Instruct | Q8 | Fits comfortably | 12.99 tok/sEstimated | 5GB (have 36GB) |
| kaitchup/Phi-3-mini-4k-instruct-gptq-4bit | Q8 | Fits comfortably | 15.39 tok/sEstimated | 4GB (have 36GB) |
| MiniMaxAI/MiniMax-M2 | Q4 | Fits comfortably | 19.00 tok/sEstimated | 4GB (have 36GB) |
| Qwen/Qwen3-0.6B-Base | Q4 | Fits comfortably | 19.72 tok/sEstimated | 3GB (have 36GB) |
| Qwen/Qwen3-0.6B-Base | Q8 | Fits comfortably | 14.10 tok/sEstimated | 6GB (have 36GB) |
| Qwen/Qwen3-8B-Base | Q4 | Fits comfortably | 21.91 tok/sEstimated | 4GB (have 36GB) |
| Qwen/Qwen3-8B-Base | Q8 | Fits comfortably | 13.68 tok/sEstimated | 9GB (have 36GB) |
| Qwen/Qwen3-8B-Base | FP16 | Fits comfortably | 7.47 tok/sEstimated | 17GB (have 36GB) |
| Qwen/Qwen3-Embedding-4B | FP16 | Fits comfortably | 8.01 tok/sEstimated | 9GB (have 36GB) |
| Qwen/Qwen3-Coder-30B-A3B-Instruct | Q4 | Fits comfortably | 11.78 tok/sEstimated | 15GB (have 36GB) |
| Qwen/Qwen3-Coder-30B-A3B-Instruct | Q8 | Fits comfortably | 8.37 tok/sEstimated | 31GB (have 36GB) |
| Qwen/Qwen3-Coder-30B-A3B-Instruct | FP16 | Not supported | 4.53 tok/sEstimated | 61GB (have 36GB) |
| Qwen/Qwen3-8B-FP8 | Q4 | Fits comfortably | 19.29 tok/sEstimated | 4GB (have 36GB) |
| Qwen/Qwen3-8B-FP8 | Q8 | Fits comfortably | 13.56 tok/sEstimated | 9GB (have 36GB) |
| IlyaGusev/saiga_llama3_8b | FP16 | Fits comfortably | 8.20 tok/sEstimated | 17GB (have 36GB) |
| Qwen/Qwen2.5-Coder-1.5B | Q4 | Fits comfortably | 19.21 tok/sEstimated | 3GB (have 36GB) |
| rinna/japanese-gpt-neox-small | FP16 | Fits comfortably | 8.26 tok/sEstimated | 15GB (have 36GB) |
| unsloth/mistral-7b-v0.3-bnb-4bit | Q4 | Fits comfortably | 20.85 tok/sEstimated | 4GB (have 36GB) |
| unsloth/mistral-7b-v0.3-bnb-4bit | Q8 | Fits comfortably | 14.20 tok/sEstimated | 7GB (have 36GB) |
| unsloth/mistral-7b-v0.3-bnb-4bit | FP16 | Fits comfortably | 7.88 tok/sEstimated | 15GB (have 36GB) |
| microsoft/Phi-3.5-vision-instruct | Q4 | Fits comfortably | 21.14 tok/sEstimated | 4GB (have 36GB) |
| microsoft/Phi-3.5-vision-instruct | Q8 | Fits comfortably | 14.47 tok/sEstimated | 7GB (have 36GB) |
| microsoft/Phi-3.5-vision-instruct | FP16 | Fits comfortably | 8.35 tok/sEstimated | 15GB (have 36GB) |
| swiss-ai/Apertus-8B-Instruct-2509 | Q4 | Fits comfortably | 19.96 tok/sEstimated | 4GB (have 36GB) |
| microsoft/Phi-4-multimodal-instruct | Q4 | Fits comfortably | 20.75 tok/sEstimated | 4GB (have 36GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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