Quick Answer: Apple M2 Max offers 96GB VRAM and starts around $39.99. It delivers approximately 71 tokens/sec on LiquidAI/LFM2-1.2B. It typically draws 40W 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 |
|---|---|---|---|
| LiquidAI/LFM2-1.2B | Q4 | 70.68 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2-2b-it | Q4 | 69.24 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 67.95 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B | Q4 | 67.85 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 67.73 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 67.66 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 67.53 tok/sEstimated Auto-generated benchmark | 2GB |
| tencent/HunyuanOCR | Q4 | 66.66 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2b | Q4 | 66.64 tok/sEstimated Auto-generated benchmark | 1GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 66.48 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-3-1b-it | Q4 | 65.66 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/DeepSeek-OCR | Q4 | 64.54 tok/sEstimated Auto-generated benchmark | 2GB |
| google/embeddinggemma-300m | Q4 | 64.50 tok/sEstimated Auto-generated benchmark | 1GB |
| google-t5/t5-3b | Q4 | 64.39 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 63.60 tok/sEstimated Auto-generated benchmark | 2GB |
| google-bert/bert-base-uncased | Q4 | 63.43 tok/sEstimated Auto-generated benchmark | 1GB |
| nari-labs/Dia2-2B | Q4 | 63.17 tok/sEstimated Auto-generated benchmark | 2GB |
| bigcode/starcoder2-3b | Q4 | 62.67 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-3B | Q4 | 62.63 tok/sEstimated Auto-generated benchmark | 2GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 62.45 tok/sEstimated Auto-generated benchmark | 1GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 62.15 tok/sEstimated Auto-generated benchmark | 2GB |
| allenai/OLMo-2-0425-1B | Q4 | 61.42 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B | Q4 | 60.33 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 60.15 tok/sEstimated Auto-generated benchmark | 2GB |
| ibm-research/PowerMoE-3b | Q4 | 59.20 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 58.99 tok/sEstimated Auto-generated benchmark | 1GB |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-8bit | Q4 | 58.98 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct | Q4 | 58.91 tok/sEstimated Auto-generated benchmark | 4GB |
| openai-community/gpt2-xl | Q4 | 58.90 tok/sEstimated Auto-generated benchmark | 4GB |
| tencent/HunyuanVideo-1.5 | Q4 | 58.88 tok/sEstimated Auto-generated benchmark | 4GB |
| ibm-granite/granite-docling-258M | Q4 | 58.88 tok/sEstimated Auto-generated benchmark | 4GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 58.85 tok/sEstimated Auto-generated benchmark | 1GB |
| llamafactory/tiny-random-Llama-3 | Q4 | 58.76 tok/sEstimated Auto-generated benchmark | 4GB |
| inference-net/Schematron-3B | Q4 | 58.75 tok/sEstimated Auto-generated benchmark | 2GB |
| skt/kogpt2-base-v2 | Q4 | 58.59 tok/sEstimated Auto-generated benchmark | 4GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 58.40 tok/sEstimated Auto-generated benchmark | 1GB |
| lmsys/vicuna-7b-v1.5 | Q4 | 58.37 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-8B-FP8 | Q4 | 58.29 tok/sEstimated Auto-generated benchmark | 4GB |
| unsloth/gemma-3-1b-it | Q4 | 58.22 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen3-0.6B-Base | Q4 | 58.19 tok/sEstimated Auto-generated benchmark | 3GB |
| HuggingFaceTB/SmolLM2-135M | Q4 | 58.18 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-4B | Q4 | 58.15 tok/sEstimated Auto-generated benchmark | 2GB |
| facebook/sam3 | Q4 | 58.08 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/DeepSeek-R1-0528 | Q4 | 57.96 tok/sEstimated Auto-generated benchmark | 4GB |
| trl-internal-testing/tiny-LlamaForCausalLM-3.2 | Q4 | 57.88 tok/sEstimated Auto-generated benchmark | 4GB |
| black-forest-labs/FLUX.1-dev | Q4 | 57.81 tok/sEstimated Auto-generated benchmark | 4GB |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-4bit | Q4 | 57.78 tok/sEstimated Auto-generated benchmark | 4GB |
| mistralai/Mistral-7B-v0.1 | Q4 | 57.78 tok/sEstimated Auto-generated benchmark | 4GB |
| lmstudio-community/Qwen3-4B-Thinking-2507-MLX-6bit | Q4 | 57.74 tok/sEstimated Auto-generated benchmark | 2GB |
| openai-community/gpt2 | Q4 | 57.70 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 | FP16 | Fits comfortably | 20.79 tok/sEstimated | 15GB (have 96GB) |
| mistralai/Mistral-Large-3-675B-Instruct-2512 | Q4 | Not supported | 7.04 tok/sEstimated | 378GB (have 96GB) |
| mistralai/Mistral-Large-3-675B-Instruct-2512 | Q8 | Not supported | 4.16 tok/sEstimated | 755GB (have 96GB) |
| mistralai/Mistral-Large-3-675B-Instruct-2512 | FP16 | Not supported | 2.39 tok/sEstimated | 1509GB (have 96GB) |
| EssentialAI/rnj-1 | Q4 | Fits comfortably | 42.88 tok/sEstimated | 5GB (have 96GB) |
| EssentialAI/rnj-1 | Q8 | Fits comfortably | 26.80 tok/sEstimated | 10GB (have 96GB) |
| EssentialAI/rnj-1 | FP16 | Fits comfortably | 15.03 tok/sEstimated | 19GB (have 96GB) |
| Qwen/Qwen2.5-7B-Instruct | Q8 | Fits comfortably | 37.00 tok/sEstimated | 7GB (have 96GB) |
| openai/gpt-oss-20b | Q4 | Fits comfortably | 29.04 tok/sEstimated | 10GB (have 96GB) |
| openai/gpt-oss-20b | Q8 | Fits comfortably | 20.24 tok/sEstimated | 20GB (have 96GB) |
| openai/gpt-oss-20b | FP16 | Fits comfortably | 10.83 tok/sEstimated | 41GB (have 96GB) |
| google/gemma-3-1b-it | Q4 | Fits comfortably | 65.66 tok/sEstimated | 1GB (have 96GB) |
| facebook/opt-125m | Q8 | Fits comfortably | 36.50 tok/sEstimated | 7GB (have 96GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | Fits comfortably | 67.73 tok/sEstimated | 1GB (have 96GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q8 | Fits comfortably | 43.65 tok/sEstimated | 1GB (have 96GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | FP16 | Fits comfortably | 26.32 tok/sEstimated | 2GB (have 96GB) |
| Qwen/Qwen2.5-7B | FP16 | Fits comfortably | 21.84 tok/sEstimated | 15GB (have 96GB) |
| Qwen/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 48.64 tok/sEstimated | 3GB (have 96GB) |
| Qwen/Qwen2.5-0.5B-Instruct | Q8 | Fits comfortably | 40.06 tok/sEstimated | 5GB (have 96GB) |
| Qwen/Qwen2.5-0.5B-Instruct | FP16 | Fits comfortably | 21.31 tok/sEstimated | 11GB (have 96GB) |
| Qwen/Qwen3-32B | Q4 | Fits comfortably | 20.07 tok/sEstimated | 16GB (have 96GB) |
| Qwen/Qwen3-32B | Q8 | Fits comfortably | 12.42 tok/sEstimated | 33GB (have 96GB) |
| allenai/OLMo-2-0425-1B | Q8 | Fits comfortably | 41.52 tok/sEstimated | 1GB (have 96GB) |
| allenai/OLMo-2-0425-1B | FP16 | Fits comfortably | 25.08 tok/sEstimated | 2GB (have 96GB) |
| microsoft/Phi-3-mini-4k-instruct | Q4 | Fits comfortably | 56.29 tok/sEstimated | 4GB (have 96GB) |
| Qwen/Qwen3-4B | Q4 | Fits comfortably | 58.15 tok/sEstimated | 2GB (have 96GB) |
| Qwen/Qwen3-4B | Q8 | Fits comfortably | 40.42 tok/sEstimated | 4GB (have 96GB) |
| Qwen/Qwen3-0.6B | Q8 | Fits comfortably | 37.49 tok/sEstimated | 6GB (have 96GB) |
| google/gemma-3-1b-it | Q8 | Fits comfortably | 42.27 tok/sEstimated | 1GB (have 96GB) |
| google/gemma-3-1b-it | FP16 | Fits comfortably | 23.94 tok/sEstimated | 2GB (have 96GB) |
| meta-llama/Llama-3.2-3B-Instruct | Q8 | Fits comfortably | 47.55 tok/sEstimated | 3GB (have 96GB) |
| meta-llama/Llama-3.2-3B-Instruct | FP16 | Fits comfortably | 26.13 tok/sEstimated | 6GB (have 96GB) |
| vikhyatk/moondream2 | Q4 | Fits comfortably | 51.92 tok/sEstimated | 4GB (have 96GB) |
| vikhyatk/moondream2 | Q8 | Fits comfortably | 40.42 tok/sEstimated | 7GB (have 96GB) |
| unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit | Q4 | Fits comfortably | 54.82 tok/sEstimated | 4GB (have 96GB) |
| unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit | FP16 | Fits comfortably | 20.13 tok/sEstimated | 17GB (have 96GB) |
| meta-llama/Llama-3.3-70B-Instruct | Q4 | Fits comfortably | 17.57 tok/sEstimated | 34GB (have 96GB) |
| meta-llama/Llama-3.3-70B-Instruct | Q8 | Fits comfortably | 13.41 tok/sEstimated | 68GB (have 96GB) |
| meta-llama/Llama-3.3-70B-Instruct | FP16 | Not supported | 7.43 tok/sEstimated | 137GB (have 96GB) |
| deepseek-ai/DeepSeek-R1-Distill-Llama-8B | Q8 | Fits comfortably | 36.10 tok/sEstimated | 9GB (have 96GB) |
| deepseek-ai/DeepSeek-R1-Distill-Llama-8B | FP16 | Fits comfortably | 20.03 tok/sEstimated | 17GB (have 96GB) |
| HuggingFaceTB/SmolLM2-135M | Q4 | Fits comfortably | 58.18 tok/sEstimated | 4GB (have 96GB) |
| HuggingFaceTB/SmolLM2-135M | Q8 | Fits comfortably | 36.30 tok/sEstimated | 7GB (have 96GB) |
| Qwen/Qwen2-7B-Instruct | Q4 | Fits comfortably | 48.81 tok/sEstimated | 4GB (have 96GB) |
| google-t5/t5-3b | Q4 | Fits comfortably | 64.39 tok/sEstimated | 2GB (have 96GB) |
| EleutherAI/gpt-neo-125m | Q4 | Fits comfortably | 51.65 tok/sEstimated | 4GB (have 96GB) |
| EleutherAI/gpt-neo-125m | Q8 | Fits comfortably | 38.49 tok/sEstimated | 7GB (have 96GB) |
| lmstudio-community/Qwen3-4B-Thinking-2507-MLX-8bit | Q4 | Fits comfortably | 52.49 tok/sEstimated | 2GB (have 96GB) |
| lmstudio-community/Qwen3-4B-Thinking-2507-MLX-8bit | Q8 | Fits comfortably | 39.03 tok/sEstimated | 4GB (have 96GB) |
| Qwen/Qwen3-4B-Instruct-2507 | Q4 | Fits comfortably | 53.69 tok/sEstimated | 2GB (have 96GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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