Quick Answer: Apple M4 Pro offers 64GB VRAM and starts around current market pricing. It delivers approximately 48 tokens/sec on bigcode/starcoder2-3b. 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 |
|---|---|---|---|
| bigcode/starcoder2-3b | Q4 | 48.24 tok/sEstimated Auto-generated benchmark | 2GB |
| facebook/sam3 | Q4 | 48.18 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-research/PowerMoE-3b | Q4 | 47.97 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 47.67 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B | Q4 | 47.51 tok/sEstimated Auto-generated benchmark | 2GB |
| nari-labs/Dia2-2B | Q4 | 47.47 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-3-1b-it | Q4 | 47.46 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2-2b-it | Q4 | 46.59 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B | Q4 | 46.31 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/DeepSeek-OCR | Q4 | 45.30 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 45.20 tok/sEstimated Auto-generated benchmark | 2GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 45.04 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-2b | Q4 | 44.79 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 44.78 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 44.71 tok/sEstimated Auto-generated benchmark | 1GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 44.58 tok/sEstimated Auto-generated benchmark | 1GB |
| LiquidAI/LFM2-1.2B | Q4 | 44.58 tok/sEstimated Auto-generated benchmark | 1GB |
| allenai/OLMo-2-0425-1B | Q4 | 44.29 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 43.77 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 43.77 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/gemma-3-1b-it | Q4 | 43.07 tok/sEstimated Auto-generated benchmark | 1GB |
| google-bert/bert-base-uncased | Q4 | 41.84 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 41.51 tok/sEstimated Auto-generated benchmark | 1GB |
| google-t5/t5-3b | Q4 | 41.50 tok/sEstimated Auto-generated benchmark | 2GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 41.45 tok/sEstimated Auto-generated benchmark | 1GB |
| inference-net/Schematron-3B | Q4 | 41.13 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 41.08 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 40.97 tok/sEstimated Auto-generated benchmark | 2GB |
| google/embeddinggemma-300m | Q4 | 40.36 tok/sEstimated Auto-generated benchmark | 1GB |
| numind/NuExtract-1.5 | Q4 | 40.27 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Meta-Llama-3-8B | Q4 | 40.23 tok/sEstimated Auto-generated benchmark | 4GB |
| openai-community/gpt2-large | Q4 | 40.12 tok/sEstimated Auto-generated benchmark | 4GB |
| ibm-granite/granite-3.3-8b-instruct | Q4 | 40.11 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-3B | Q4 | 40.04 tok/sEstimated Auto-generated benchmark | 2GB |
| deepseek-ai/DeepSeek-R1-0528 | Q4 | 40.02 tok/sEstimated Auto-generated benchmark | 4GB |
| tencent/HunyuanOCR | Q4 | 40.01 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/DeepSeek-V3-0324 | Q4 | 39.97 tok/sEstimated Auto-generated benchmark | 4GB |
| BSC-LT/salamandraTA-7b-instruct | Q4 | 39.77 tok/sEstimated Auto-generated benchmark | 4GB |
| parler-tts/parler-tts-large-v1 | Q4 | 39.70 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2-0.5B | Q4 | 39.60 tok/sEstimated Auto-generated benchmark | 3GB |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-8bit | Q4 | 39.50 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-R1 | Q4 | 39.46 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-Coder-1.5B | Q4 | 39.44 tok/sEstimated Auto-generated benchmark | 3GB |
| Qwen/Qwen2.5-0.5B | Q4 | 39.41 tok/sEstimated Auto-generated benchmark | 3GB |
| unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit | Q4 | 39.39 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/DialoGPT-small | Q4 | 39.16 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Llama-2-7b-hf | Q4 | 38.66 tok/sEstimated Auto-generated benchmark | 4GB |
| trl-internal-testing/tiny-LlamaForCausalLM-3.2 | Q4 | 38.59 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-7B-Instruct | Q4 | 38.58 tok/sEstimated Auto-generated benchmark | 4GB |
| bigscience/bloomz-560m | Q4 | 38.46 tok/sEstimated Auto-generated benchmark | 4GB |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
| Model | Quantization | Verdict | Estimated speed | VRAM needed |
|---|---|---|---|---|
| facebook/opt-125m | Q8 | Fits comfortably | 25.17 tok/sEstimated | 7GB (have 64GB) |
| meta-llama/Llama-3.2-1B-Instruct | Q8 | Fits comfortably | 31.49 tok/sEstimated | 1GB (have 64GB) |
| meta-llama/Llama-3.2-1B-Instruct | FP16 | Fits comfortably | 18.02 tok/sEstimated | 2GB (have 64GB) |
| openai/gpt-oss-120b | Q4 | Fits comfortably | 7.51 tok/sEstimated | 59GB (have 64GB) |
| Qwen/Qwen3-8B | Q4 | Fits comfortably | 37.32 tok/sEstimated | 4GB (have 64GB) |
| google-t5/t5-3b | Q8 | Fits comfortably | 31.25 tok/sEstimated | 3GB (have 64GB) |
| google-t5/t5-3b | FP16 | Fits comfortably | 17.93 tok/sEstimated | 6GB (have 64GB) |
| meta-llama/Meta-Llama-3-8B-Instruct | Q8 | Fits comfortably | 27.45 tok/sEstimated | 9GB (have 64GB) |
| meta-llama/Meta-Llama-3-8B-Instruct | FP16 | Fits comfortably | 13.64 tok/sEstimated | 17GB (have 64GB) |
| Qwen/Qwen2.5-14B-Instruct | Q8 | Fits comfortably | 17.48 tok/sEstimated | 14GB (have 64GB) |
| Qwen/Qwen2.5-14B-Instruct | FP16 | Fits comfortably | 10.08 tok/sEstimated | 29GB (have 64GB) |
| unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit | Q4 | Fits comfortably | 39.39 tok/sEstimated | 4GB (have 64GB) |
| meta-llama/Llama-3.1-70B-Instruct | FP16 | Not supported | 5.29 tok/sEstimated | 137GB (have 64GB) |
| deepseek-ai/DeepSeek-V3.1 | FP16 | Fits comfortably | 14.89 tok/sEstimated | 15GB (have 64GB) |
| meta-llama/Llama-3.1-8B | Q4 | Fits comfortably | 38.16 tok/sEstimated | 4GB (have 64GB) |
| meta-llama/Llama-3.1-8B | Q8 | Fits comfortably | 27.38 tok/sEstimated | 9GB (have 64GB) |
| Qwen/Qwen2.5-32B-Instruct | FP16 | Not supported | 4.95 tok/sEstimated | 66GB (have 64GB) |
| mistralai/Mistral-7B-v0.1 | Q4 | Fits comfortably | 34.54 tok/sEstimated | 4GB (have 64GB) |
| mistralai/Mistral-7B-v0.1 | Q8 | Fits comfortably | 27.45 tok/sEstimated | 7GB (have 64GB) |
| mistralai/Mistral-7B-v0.1 | FP16 | Fits comfortably | 12.84 tok/sEstimated | 15GB (have 64GB) |
| unsloth/Meta-Llama-3.1-8B-Instruct | Q8 | Fits comfortably | 24.23 tok/sEstimated | 9GB (have 64GB) |
| unsloth/Meta-Llama-3.1-8B-Instruct | FP16 | Fits comfortably | 13.36 tok/sEstimated | 17GB (have 64GB) |
| meta-llama/Meta-Llama-3-70B-Instruct | Q4 | Fits comfortably | 12.89 tok/sEstimated | 34GB (have 64GB) |
| meta-llama/Meta-Llama-3-70B-Instruct | Q8 | Not supported | 8.89 tok/sEstimated | 68GB (have 64GB) |
| Qwen/Qwen3-0.6B-Base | Q4 | Fits comfortably | 38.01 tok/sEstimated | 3GB (have 64GB) |
| microsoft/DialoGPT-small | Q4 | Fits comfortably | 39.16 tok/sEstimated | 4GB (have 64GB) |
| microsoft/DialoGPT-small | Q8 | Fits comfortably | 25.78 tok/sEstimated | 7GB (have 64GB) |
| microsoft/DialoGPT-small | FP16 | Fits comfortably | 13.07 tok/sEstimated | 15GB (have 64GB) |
| Qwen/Qwen2-1.5B-Instruct | Q4 | Fits comfortably | 33.31 tok/sEstimated | 3GB (have 64GB) |
| Qwen/Qwen2-1.5B-Instruct | Q8 | Fits comfortably | 27.26 tok/sEstimated | 5GB (have 64GB) |
| Qwen/Qwen2-1.5B-Instruct | FP16 | Fits comfortably | 13.05 tok/sEstimated | 11GB (have 64GB) |
| meta-llama/Llama-Guard-3-1B | Q4 | Fits comfortably | 43.77 tok/sEstimated | 1GB (have 64GB) |
| EleutherAI/gpt-neo-125m | FP16 | Fits comfortably | 14.17 tok/sEstimated | 15GB (have 64GB) |
| meta-llama/Llama-3.2-3B | Q4 | Fits comfortably | 47.51 tok/sEstimated | 2GB (have 64GB) |
| meta-llama/Llama-3.2-3B | Q8 | Fits comfortably | 29.12 tok/sEstimated | 3GB (have 64GB) |
| meta-llama/Llama-3.2-3B | FP16 | Fits comfortably | 16.63 tok/sEstimated | 6GB (have 64GB) |
| deepseek-ai/DeepSeek-V3-0324 | FP16 | Fits comfortably | 13.86 tok/sEstimated | 15GB (have 64GB) |
| huggyllama/llama-7b | Q4 | Fits comfortably | 36.81 tok/sEstimated | 4GB (have 64GB) |
| huggyllama/llama-7b | Q8 | Fits comfortably | 23.93 tok/sEstimated | 7GB (have 64GB) |
| huggyllama/llama-7b | FP16 | Fits comfortably | 14.45 tok/sEstimated | 15GB (have 64GB) |
| deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct | Q4 | Fits comfortably | 37.28 tok/sEstimated | 4GB (have 64GB) |
| microsoft/Phi-4-mini-instruct | Q8 | Fits comfortably | 24.08 tok/sEstimated | 7GB (have 64GB) |
| microsoft/Phi-4-mini-instruct | FP16 | Fits comfortably | 15.29 tok/sEstimated | 15GB (have 64GB) |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-8bit | Q4 | Fits comfortably | 39.50 tok/sEstimated | 4GB (have 64GB) |
| NousResearch/Meta-Llama-3.1-8B-Instruct | Q4 | Fits comfortably | 37.04 tok/sEstimated | 4GB (have 64GB) |
| NousResearch/Meta-Llama-3.1-8B-Instruct | Q8 | Fits comfortably | 25.96 tok/sEstimated | 9GB (have 64GB) |
| NousResearch/Meta-Llama-3.1-8B-Instruct | FP16 | Fits comfortably | 13.73 tok/sEstimated | 17GB (have 64GB) |
| apple/OpenELM-1_1B-Instruct | Q4 | Fits comfortably | 41.45 tok/sEstimated | 1GB (have 64GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-5bit | Q8 | Fits comfortably | 14.52 tok/sEstimated | 31GB (have 64GB) |
| facebook/opt-125m | Q4 | Fits comfortably | 37.50 tok/sEstimated | 4GB (have 64GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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