Quick Answer: Apple M4 Max offers 128GB VRAM and starts around current market pricing. It delivers approximately 98 tokens/sec on deepseek-ai/DeepSeek-OCR. It typically draws 45W 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.
With 128GB VRAM, Apple M4 Max can run models up to approximately 320B parameters using 4-bit quantization. This handles most popular models including Llama 3 70B, Mistral 7B, and larger.
Consider H100 or MI300X — Maximum VRAM for enterprise workloads.
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| Model | Quantization | Tokens/sec | VRAM used |
|---|---|---|---|
| deepseek-ai/DeepSeek-OCR | Q4 | 98.27 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 96.02 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 95.43 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B | Q4 | 95.08 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-2-2b-it | Q4 | 94.96 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 94.79 tok/sEstimated Auto-generated benchmark | 2GB |
| bigcode/starcoder2-3b | Q4 | 93.98 tok/sEstimated Auto-generated benchmark | 2GB |
| google-t5/t5-3b | Q4 | 92.03 tok/sEstimated Auto-generated benchmark | 2GB |
| tencent/HunyuanOCR | Q4 | 91.77 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 91.71 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 91.63 tok/sEstimated Auto-generated benchmark | 1GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 91.09 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2b | Q4 | 90.84 tok/sEstimated Auto-generated benchmark | 1GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 90.71 tok/sEstimated Auto-generated benchmark | 1GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 90.37 tok/sEstimated Auto-generated benchmark | 2GB |
| inference-net/Schematron-3B | Q4 | 90.35 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 89.14 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/gemma-3-1b-it | Q4 | 89.08 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B | Q4 | 87.90 tok/sEstimated Auto-generated benchmark | 2GB |
| google/embeddinggemma-300m | Q4 | 87.40 tok/sEstimated Auto-generated benchmark | 1GB |
| facebook/sam3 | Q4 | 87.37 tok/sEstimated Auto-generated benchmark | 1GB |
| google-bert/bert-base-uncased | Q4 | 86.75 tok/sEstimated Auto-generated benchmark | 1GB |
| nineninesix/kani-tts-2-en | Q4 | 86.43 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/DeepSeek-OCR-2 | Q4 | 86.32 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 85.28 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-3-1b-it | Q4 | 85.19 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 84.80 tok/sEstimated Auto-generated benchmark | 2GB |
| allenai/OLMo-2-0425-1B | Q4 | 84.76 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen3-ASR-1.7B | Q4 | 84.11 tok/sEstimated Auto-generated benchmark | 2GB |
| nari-labs/Dia2-2B | Q4 | 83.51 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B | Q4 | 83.21 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-research/PowerMoE-3b | Q4 | 82.90 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 80.80 tok/sEstimated Auto-generated benchmark | 1GB |
| numind/NuExtract-1.5 | Q4 | 80.43 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-V3-0324 | Q4 | 80.31 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-8B-Base | Q4 | 80.19 tok/sEstimated Auto-generated benchmark | 4GB |
| lmstudio-community/Qwen3-4B-Thinking-2507-MLX-8bit | Q4 | 80.09 tok/sEstimated Auto-generated benchmark | 2GB |
| moonshotai/Kimi-K2.5 | Q4 | 80.08 tok/sEstimated Auto-generated benchmark | 4GB |
| unsloth/Meta-Llama-3.1-8B-Instruct | Q4 | 79.94 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/phi-4 | Q4 | 79.91 tok/sEstimated Auto-generated benchmark | 4GB |
| trl-internal-testing/tiny-random-LlamaForCausalLM | Q4 | 79.79 tok/sEstimated Auto-generated benchmark | 4GB |
| black-forest-labs/FLUX.2-dev | Q4 | 79.75 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-Math-1.5B | Q4 | 79.65 tok/sEstimated Auto-generated benchmark | 3GB |
| deepseek-ai/DeepSeek-V3 | Q4 | 79.34 tok/sEstimated Auto-generated benchmark | 4GB |
| openai-community/gpt2-medium | Q4 | 79.32 tok/sEstimated Auto-generated benchmark | 4GB |
| liuhaotian/llava-v1.5-7b | Q4 | 79.30 tok/sEstimated Auto-generated benchmark | 4GB |
| LiquidAI/LFM2-1.2B | Q4 | 79.30 tok/sEstimated Auto-generated benchmark | 1GB |
| vikhyatk/moondream2 | Q4 | 79.28 tok/sEstimated Auto-generated benchmark | 4GB |
| ibm-granite/granite-docling-258M | Q4 | 79.25 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/Phi-3.5-mini-instruct | Q4 | 78.70 tok/sEstimated Auto-generated benchmark | 2GB |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
| Model | Quantization | Verdict | Estimated speed | VRAM needed |
|---|---|---|---|---|
| openai-community/gpt2 | Q8 | Fits comfortably | 52.62 tok/sEstimated | 7GB (have 128GB) |
| openai-community/gpt2 | FP16 | Fits comfortably | 25.71 tok/sEstimated | 15GB (have 128GB) |
| Qwen/Qwen2.5-7B-Instruct | Q4 | Fits comfortably | 71.21 tok/sEstimated | 4GB (have 128GB) |
| Qwen/Qwen2.5-7B-Instruct | Q8 | Fits comfortably | 47.46 tok/sEstimated | 7GB (have 128GB) |
| Qwen/Qwen2.5-7B-Instruct | FP16 | Fits comfortably | 30.30 tok/sEstimated | 15GB (have 128GB) |
| Qwen/Qwen3-0.6B | Q4 | Fits comfortably | 75.71 tok/sEstimated | 3GB (have 128GB) |
| Qwen/Qwen3-0.6B | Q8 | Fits comfortably | 53.46 tok/sEstimated | 6GB (have 128GB) |
| Qwen/Qwen3-0.6B | FP16 | Fits comfortably | 30.31 tok/sEstimated | 13GB (have 128GB) |
| Gensyn/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 70.95 tok/sEstimated | 3GB (have 128GB) |
| Gensyn/Qwen2.5-0.5B-Instruct | Q8 | Fits comfortably | 46.66 tok/sEstimated | 5GB (have 128GB) |
| Gensyn/Qwen2.5-0.5B-Instruct | FP16 | Fits comfortably | 29.91 tok/sEstimated | 11GB (have 128GB) |
| meta-llama/Llama-3.1-8B-Instruct | Q4 | Fits comfortably | 77.72 tok/sEstimated | 4GB (have 128GB) |
| meta-llama/Llama-3.1-8B-Instruct | Q8 | Fits comfortably | 46.69 tok/sEstimated | 9GB (have 128GB) |
| meta-llama/Llama-3.1-8B-Instruct | FP16 | Fits comfortably | 29.75 tok/sEstimated | 17GB (have 128GB) |
| dphn/dolphin-2.9.1-yi-1.5-34b | Q4 | Fits comfortably | 26.73 tok/sEstimated | 17GB (have 128GB) |
| dphn/dolphin-2.9.1-yi-1.5-34b | Q8 | Fits comfortably | 19.42 tok/sEstimated | 35GB (have 128GB) |
| dphn/dolphin-2.9.1-yi-1.5-34b | FP16 | Fits comfortably | 9.15 tok/sEstimated | 70GB (have 128GB) |
| openai/gpt-oss-20b | Q4 | Fits comfortably | 38.62 tok/sEstimated | 10GB (have 128GB) |
| openai/gpt-oss-20b | Q8 | Fits comfortably | 29.66 tok/sEstimated | 20GB (have 128GB) |
| openai/gpt-oss-20b | FP16 | Fits comfortably | 13.78 tok/sEstimated | 41GB (have 128GB) |
| google/gemma-3-1b-it | Q4 | Fits comfortably | 85.19 tok/sEstimated | 1GB (have 128GB) |
| google/gemma-3-1b-it | Q8 | Fits comfortably | 60.47 tok/sEstimated | 1GB (have 128GB) |
| google/gemma-3-1b-it | FP16 | Fits comfortably | 36.34 tok/sEstimated | 2GB (have 128GB) |
| Qwen/Qwen3-Embedding-0.6B | Q4 | Fits comfortably | 70.69 tok/sEstimated | 3GB (have 128GB) |
| Qwen/Qwen3-Embedding-0.6B | Q8 | Fits comfortably | 51.87 tok/sEstimated | 6GB (have 128GB) |
| Qwen/Qwen3-Embedding-0.6B | FP16 | Fits comfortably | 30.43 tok/sEstimated | 13GB (have 128GB) |
| Qwen/Qwen2.5-1.5B-Instruct | Q4 | Fits comfortably | 70.92 tok/sEstimated | 3GB (have 128GB) |
| Qwen/Qwen2.5-1.5B-Instruct | Q8 | Fits comfortably | 53.03 tok/sEstimated | 5GB (have 128GB) |
| Qwen/Qwen2.5-1.5B-Instruct | FP16 | Fits comfortably | 28.53 tok/sEstimated | 11GB (have 128GB) |
| facebook/opt-125m | Q4 | Fits comfortably | 76.39 tok/sEstimated | 4GB (have 128GB) |
| facebook/opt-125m | Q8 | Fits comfortably | 46.39 tok/sEstimated | 7GB (have 128GB) |
| facebook/opt-125m | FP16 | Fits comfortably | 27.10 tok/sEstimated | 15GB (have 128GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | Fits comfortably | 91.63 tok/sEstimated | 1GB (have 128GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q8 | Fits comfortably | 56.56 tok/sEstimated | 1GB (have 128GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | FP16 | Fits comfortably | 34.15 tok/sEstimated | 2GB (have 128GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q4 | Fits comfortably | 70.12 tok/sEstimated | 4GB (have 128GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q8 | Fits comfortably | 52.70 tok/sEstimated | 7GB (have 128GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | FP16 | Fits comfortably | 25.71 tok/sEstimated | 15GB (have 128GB) |
| Qwen/Qwen3-4B-Instruct-2507 | Q4 | Fits comfortably | 74.29 tok/sEstimated | 2GB (have 128GB) |
| Qwen/Qwen3-4B-Instruct-2507 | Q8 | Fits comfortably | 46.57 tok/sEstimated | 4GB (have 128GB) |
| Qwen/Qwen3-4B-Instruct-2507 | FP16 | Fits comfortably | 26.97 tok/sEstimated | 9GB (have 128GB) |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | Fits comfortably | 85.28 tok/sEstimated | 1GB (have 128GB) |
| meta-llama/Llama-3.2-1B-Instruct | Q8 | Fits comfortably | 61.91 tok/sEstimated | 1GB (have 128GB) |
| meta-llama/Llama-3.2-1B-Instruct | FP16 | Fits comfortably | 34.90 tok/sEstimated | 2GB (have 128GB) |
| openai/gpt-oss-120b | Q4 | Fits comfortably | 15.79 tok/sEstimated | 59GB (have 128GB) |
| openai/gpt-oss-120b | Q8 | Fits comfortably | 9.42 tok/sEstimated | 117GB (have 128GB) |
| openai/gpt-oss-120b | FP16 | Not supported | 5.33 tok/sEstimated | 235GB (have 128GB) |
| Qwen/Qwen2.5-3B-Instruct | Q4 | Fits comfortably | 96.02 tok/sEstimated | 2GB (have 128GB) |
| Qwen/Qwen2.5-3B-Instruct | Q8 | Fits comfortably | 58.91 tok/sEstimated | 3GB (have 128GB) |
| openai-community/gpt2 | Q4 | Fits comfortably | 77.53 tok/sEstimated | 4GB (have 128GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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