Quick Answer: AMD Instinct MI250X offers 128GB VRAM and starts around current market pricing. It delivers approximately 627 tokens/sec on facebook/sam3. It typically draws 560W 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 |
|---|---|---|---|
| facebook/sam3 | Q4 | 627.06 tok/sEstimated Auto-generated benchmark | 1GB |
| tencent/HunyuanOCR | Q4 | 615.02 tok/sEstimated Auto-generated benchmark | 1GB |
| google-bert/bert-base-uncased | Q4 | 610.55 tok/sEstimated Auto-generated benchmark | 1GB |
| nari-labs/Dia2-2B | Q4 | 608.94 tok/sEstimated Auto-generated benchmark | 2GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 607.29 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 607.28 tok/sEstimated Auto-generated benchmark | 1GB |
| inference-net/Schematron-3B | Q4 | 599.61 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B | Q4 | 592.66 tok/sEstimated Auto-generated benchmark | 2GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 591.74 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 591.59 tok/sEstimated Auto-generated benchmark | 2GB |
| deepseek-ai/DeepSeek-OCR | Q4 | 583.13 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 581.41 tok/sEstimated Auto-generated benchmark | 2GB |
| google-t5/t5-3b | Q4 | 579.13 tok/sEstimated Auto-generated benchmark | 2GB |
| LiquidAI/LFM2-1.2B | Q4 | 573.43 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 550.67 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 548.44 tok/sEstimated Auto-generated benchmark | 1GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 543.98 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B | Q4 | 543.31 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-3-1b-it | Q4 | 541.88 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2b | Q4 | 540.82 tok/sEstimated Auto-generated benchmark | 1GB |
| google/embeddinggemma-300m | Q4 | 534.97 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/gemma-3-1b-it | Q4 | 534.01 tok/sEstimated Auto-generated benchmark | 1GB |
| allenai/OLMo-2-0425-1B | Q4 | 533.37 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-research/PowerMoE-3b | Q4 | 532.99 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B | Q4 | 528.24 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen3-4B-Base | Q4 | 524.42 tok/sEstimated Auto-generated benchmark | 2GB |
| microsoft/Phi-4-mini-instruct | Q4 | 523.92 tok/sEstimated Auto-generated benchmark | 4GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 521.18 tok/sEstimated Auto-generated benchmark | 2GB |
| skt/kogpt2-base-v2 | Q4 | 521.12 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-7B-Instruct | Q4 | 520.43 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2-7B-Instruct | Q4 | 520.08 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 520.02 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 519.91 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-2-2b-it | Q4 | 519.81 tok/sEstimated Auto-generated benchmark | 1GB |
| bigcode/starcoder2-3b | Q4 | 519.30 tok/sEstimated Auto-generated benchmark | 2GB |
| IlyaGusev/saiga_llama3_8b | Q4 | 519.22 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-Embedding-0.6B | Q4 | 518.10 tok/sEstimated Auto-generated benchmark | 3GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 517.84 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen3-4B-Thinking-2507 | Q4 | 516.16 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen3-4B-Instruct-2507 | Q4 | 515.59 tok/sEstimated Auto-generated benchmark | 2GB |
| allenai/Olmo-3-7B-Think | Q4 | 515.34 tok/sEstimated Auto-generated benchmark | 4GB |
| trl-internal-testing/tiny-LlamaForCausalLM-3.2 | Q4 | 514.65 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/phi-4 | Q4 | 514.55 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/Phi-3.5-vision-instruct | Q4 | 513.89 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-1.5B | Q4 | 511.83 tok/sEstimated Auto-generated benchmark | 3GB |
| EleutherAI/gpt-neo-125m | Q4 | 511.67 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-R1 | Q4 | 511.44 tok/sEstimated Auto-generated benchmark | 4GB |
| parler-tts/parler-tts-large-v1 | Q4 | 511.25 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct | Q4 | 510.08 tok/sEstimated Auto-generated benchmark | 4GB |
| GSAI-ML/LLaDA-8B-Base | Q4 | 509.92 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 |
|---|---|---|---|---|
| Gensyn/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 487.68 tok/sEstimated | 3GB (have 128GB) |
| dphn/dolphin-2.9.1-yi-1.5-34b | Q4 | Fits comfortably | 168.08 tok/sEstimated | 17GB (have 128GB) |
| Qwen/Qwen3-Embedding-0.6B | Q4 | Fits comfortably | 518.10 tok/sEstimated | 3GB (have 128GB) |
| Qwen/Qwen3-Embedding-0.6B | Q8 | Fits comfortably | 317.40 tok/sEstimated | 6GB (have 128GB) |
| Qwen/Qwen3-Embedding-0.6B | FP16 | Fits comfortably | 197.63 tok/sEstimated | 13GB (have 128GB) |
| Qwen/Qwen2.5-1.5B-Instruct | Q4 | Fits comfortably | 498.82 tok/sEstimated | 3GB (have 128GB) |
| Qwen/Qwen2.5-1.5B-Instruct | Q8 | Fits comfortably | 355.31 tok/sEstimated | 5GB (have 128GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | FP16 | Fits comfortably | 215.55 tok/sEstimated | 2GB (have 128GB) |
| vikhyatk/moondream2 | Q8 | Fits comfortably | 349.42 tok/sEstimated | 7GB (have 128GB) |
| vikhyatk/moondream2 | FP16 | Fits comfortably | 166.81 tok/sEstimated | 15GB (have 128GB) |
| petals-team/StableBeluga2 | Q4 | Fits comfortably | 475.68 tok/sEstimated | 4GB (have 128GB) |
| petals-team/StableBeluga2 | Q8 | Fits comfortably | 350.92 tok/sEstimated | 7GB (have 128GB) |
| petals-team/StableBeluga2 | FP16 | Fits comfortably | 194.60 tok/sEstimated | 15GB (have 128GB) |
| microsoft/Phi-3-mini-4k-instruct | Q4 | Fits comfortably | 503.83 tok/sEstimated | 4GB (have 128GB) |
| openai-community/gpt2-large | Q4 | Fits comfortably | 502.20 tok/sEstimated | 4GB (have 128GB) |
| openai-community/gpt2-large | Q8 | Fits comfortably | 337.91 tok/sEstimated | 7GB (have 128GB) |
| meta-llama/Meta-Llama-3-8B-Instruct | FP16 | Fits comfortably | 188.97 tok/sEstimated | 17GB (have 128GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | Q4 | Fits comfortably | 461.20 tok/sEstimated | 3GB (have 128GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | Q8 | Fits comfortably | 336.82 tok/sEstimated | 5GB (have 128GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | FP16 | Fits comfortably | 191.34 tok/sEstimated | 11GB (have 128GB) |
| mlx-community/gpt-oss-20b-MXFP4-Q8 | Q4 | Fits comfortably | 260.79 tok/sEstimated | 10GB (have 128GB) |
| mlx-community/gpt-oss-20b-MXFP4-Q8 | Q8 | Fits comfortably | 187.35 tok/sEstimated | 20GB (have 128GB) |
| mlx-community/gpt-oss-20b-MXFP4-Q8 | FP16 | Fits comfortably | 98.15 tok/sEstimated | 41GB (have 128GB) |
| Qwen/Qwen2.5-0.5B | Q4 | Fits comfortably | 453.63 tok/sEstimated | 3GB (have 128GB) |
| zai-org/GLM-4.6-FP8 | Q8 | Fits comfortably | 310.13 tok/sEstimated | 7GB (have 128GB) |
| zai-org/GLM-4.6-FP8 | FP16 | Fits comfortably | 167.31 tok/sEstimated | 15GB (have 128GB) |
| microsoft/DialoGPT-medium | Q4 | Fits comfortably | 461.06 tok/sEstimated | 4GB (have 128GB) |
| HuggingFaceTB/SmolLM-135M | FP16 | Fits comfortably | 197.24 tok/sEstimated | 15GB (have 128GB) |
| Qwen/Qwen2.5-Math-1.5B | Q4 | Fits comfortably | 467.51 tok/sEstimated | 3GB (have 128GB) |
| Qwen/Qwen2.5-Math-1.5B | Q8 | Fits comfortably | 304.13 tok/sEstimated | 5GB (have 128GB) |
| Qwen/Qwen2.5-Coder-1.5B | Q8 | Fits comfortably | 332.77 tok/sEstimated | 5GB (have 128GB) |
| swiss-ai/Apertus-8B-Instruct-2509 | Q4 | Fits comfortably | 490.54 tok/sEstimated | 4GB (have 128GB) |
| swiss-ai/Apertus-8B-Instruct-2509 | Q8 | Fits comfortably | 333.25 tok/sEstimated | 9GB (have 128GB) |
| microsoft/Phi-3.5-mini-instruct | Q4 | Fits comfortably | 495.64 tok/sEstimated | 4GB (have 128GB) |
| microsoft/Phi-3.5-mini-instruct | Q8 | Fits comfortably | 322.68 tok/sEstimated | 7GB (have 128GB) |
| unsloth/Llama-3.2-1B-Instruct | FP16 | Fits comfortably | 215.75 tok/sEstimated | 2GB (have 128GB) |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-4bit | Q4 | Fits comfortably | 476.41 tok/sEstimated | 4GB (have 128GB) |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-4bit | Q8 | Fits comfortably | 345.94 tok/sEstimated | 9GB (have 128GB) |
| llamafactory/tiny-random-Llama-3 | Q4 | Fits comfortably | 465.34 tok/sEstimated | 4GB (have 128GB) |
| llamafactory/tiny-random-Llama-3 | Q8 | Fits comfortably | 346.43 tok/sEstimated | 7GB (have 128GB) |
| llamafactory/tiny-random-Llama-3 | FP16 | Fits comfortably | 199.12 tok/sEstimated | 15GB (have 128GB) |
| deepseek-ai/DeepSeek-V3 | Q8 | Fits comfortably | 311.69 tok/sEstimated | 7GB (have 128GB) |
| deepseek-ai/DeepSeek-V3 | FP16 | Fits comfortably | 165.92 tok/sEstimated | 15GB (have 128GB) |
| baichuan-inc/Baichuan-M2-32B | Q4 | Fits comfortably | 167.20 tok/sEstimated | 16GB (have 128GB) |
| baichuan-inc/Baichuan-M2-32B | Q8 | Fits comfortably | 114.60 tok/sEstimated | 33GB (have 128GB) |
| mistralai/Mistral-Small-Instruct-2409 | Q8 | Fits comfortably | 185.36 tok/sEstimated | 23GB (have 128GB) |
| mistralai/Mistral-Small-Instruct-2409 | FP16 | Fits comfortably | 101.57 tok/sEstimated | 46GB (have 128GB) |
| microsoft/Phi-3.5-mini-instruct | FP16 | Fits comfortably | 191.08 tok/sEstimated | 8GB (have 128GB) |
| microsoft/Phi-3-medium-128k-instruct | Q4 | Fits comfortably | 347.47 tok/sEstimated | 7GB (have 128GB) |
| Qwen/Qwen3-0.6B | FP16 | Fits comfortably | 192.16 tok/sEstimated | 13GB (have 128GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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