Quick Answer: NVIDIA H200 SXM 141GB offers 141GB VRAM and starts around current market pricing. It delivers approximately 918 tokens/sec on deepseek-ai/DeepSeek-OCR. It typically draws 700W 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 |
|---|---|---|---|
| deepseek-ai/DeepSeek-OCR | Q4 | 918.04 tok/sEstimated Auto-generated benchmark | 2GB |
| ibm-research/PowerMoE-3b | Q4 | 899.99 tok/sEstimated Auto-generated benchmark | 2GB |
| google/embeddinggemma-300m | Q4 | 892.88 tok/sEstimated Auto-generated benchmark | 1GB |
| google-bert/bert-base-uncased | Q4 | 890.49 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2b | Q4 | 890.18 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 887.95 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-3-1b-it | Q4 | 882.07 tok/sEstimated Auto-generated benchmark | 1GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 880.62 tok/sEstimated Auto-generated benchmark | 1GB |
| allenai/OLMo-2-0425-1B | Q4 | 879.27 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B | Q4 | 874.57 tok/sEstimated Auto-generated benchmark | 2GB |
| facebook/sam3 | Q4 | 854.80 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 845.59 tok/sEstimated Auto-generated benchmark | 1GB |
| inference-net/Schematron-3B | Q4 | 844.62 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 831.79 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 824.89 tok/sEstimated Auto-generated benchmark | 2GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 822.25 tok/sEstimated Auto-generated benchmark | 1GB |
| LiquidAI/LFM2-1.2B | Q4 | 818.45 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B | Q4 | 814.74 tok/sEstimated Auto-generated benchmark | 1GB |
| bigcode/starcoder2-3b | Q4 | 807.54 tok/sEstimated Auto-generated benchmark | 2GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 806.27 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2-2b-it | Q4 | 801.78 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 794.66 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 793.70 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 790.53 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B | Q4 | 783.01 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/gemma-3-1b-it | Q4 | 775.54 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 764.26 tok/sEstimated Auto-generated benchmark | 2GB |
| google-t5/t5-3b | Q4 | 760.55 tok/sEstimated Auto-generated benchmark | 2GB |
| tencent/HunyuanOCR | Q4 | 760.33 tok/sEstimated Auto-generated benchmark | 1GB |
| black-forest-labs/FLUX.2-dev | Q4 | 757.49 tok/sEstimated Auto-generated benchmark | 4GB |
| unsloth/Meta-Llama-3.1-8B-Instruct | Q4 | 756.55 tok/sEstimated Auto-generated benchmark | 4GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 752.49 tok/sEstimated Auto-generated benchmark | 2GB |
| zai-org/GLM-4.6-FP8 | Q4 | 751.25 tok/sEstimated Auto-generated benchmark | 4GB |
| zai-org/GLM-4.5-Air | Q4 | 750.94 tok/sEstimated Auto-generated benchmark | 4GB |
| llamafactory/tiny-random-Llama-3 | Q4 | 750.21 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-4B-Thinking-2507-FP8 | Q4 | 749.40 tok/sEstimated Auto-generated benchmark | 2GB |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-7B | Q4 | 749.00 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/Phi-4-multimodal-instruct | Q4 | 747.88 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Llama-3.1-8B | Q4 | 747.62 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-1.5B | Q4 | 746.78 tok/sEstimated Auto-generated benchmark | 3GB |
| Qwen/Qwen2.5-Math-1.5B | Q4 | 746.03 tok/sEstimated Auto-generated benchmark | 3GB |
| deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct | Q4 | 745.77 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen-Image-Edit-2509 | Q4 | 744.63 tok/sEstimated Auto-generated benchmark | 4GB |
| nari-labs/Dia2-2B | Q4 | 744.44 tok/sEstimated Auto-generated benchmark | 2GB |
| distilbert/distilgpt2 | Q4 | 744.14 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-Coder-1.5B | Q4 | 744.01 tok/sEstimated Auto-generated benchmark | 3GB |
| Qwen/Qwen3-Embedding-0.6B | Q4 | 743.37 tok/sEstimated Auto-generated benchmark | 3GB |
| mistralai/Mistral-7B-Instruct-v0.1 | Q4 | 743.33 tok/sEstimated Auto-generated benchmark | 4GB |
| numind/NuExtract-1.5 | Q4 | 741.76 tok/sEstimated Auto-generated benchmark | 4GB |
| unsloth/mistral-7b-v0.3-bnb-4bit | Q4 | 741.46 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 |
|---|---|---|---|---|
| codellama/CodeLlama-34b-hf | Q4 | Fits comfortably | 262.21 tok/sEstimated | 17GB (have 141GB) |
| google/gemma-3-1b-it | FP16 | Fits comfortably | 315.12 tok/sEstimated | 2GB (have 141GB) |
| Qwen/Qwen3-Embedding-0.6B | Q4 | Fits comfortably | 743.37 tok/sEstimated | 3GB (have 141GB) |
| Qwen/Qwen3-0.6B | FP16 | Fits comfortably | 277.30 tok/sEstimated | 13GB (have 141GB) |
| Gensyn/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 628.06 tok/sEstimated | 3GB (have 141GB) |
| Qwen/Qwen3-Embedding-0.6B | Q8 | Fits comfortably | 451.95 tok/sEstimated | 6GB (have 141GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q4 | Fits comfortably | 716.31 tok/sEstimated | 4GB (have 141GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q8 | Fits comfortably | 438.05 tok/sEstimated | 7GB (have 141GB) |
| Qwen/Qwen2.5-0.5B-Instruct | FP16 | Fits comfortably | 245.18 tok/sEstimated | 11GB (have 141GB) |
| Qwen/Qwen3-Next-80B-A3B-Instruct | Q4 | Fits comfortably | 125.93 tok/sEstimated | 39GB (have 141GB) |
| Qwen/Qwen3-Next-80B-A3B-Instruct | Q8 | Fits comfortably | 102.14 tok/sEstimated | 78GB (have 141GB) |
| Qwen/Qwen3-Next-80B-A3B-Instruct | FP16 | Not supported | 56.23 tok/sEstimated | 156GB (have 141GB) |
| allenai/OLMo-2-0425-1B | Q4 | Fits comfortably | 879.27 tok/sEstimated | 1GB (have 141GB) |
| openai-community/gpt2-large | FP16 | Fits comfortably | 242.81 tok/sEstimated | 15GB (have 141GB) |
| Qwen/Qwen3-1.7B | Q4 | Fits comfortably | 632.44 tok/sEstimated | 4GB (have 141GB) |
| Qwen/Qwen3-1.7B | Q8 | Fits comfortably | 505.75 tok/sEstimated | 7GB (have 141GB) |
| Qwen/Qwen3-4B | Q8 | Fits comfortably | 436.11 tok/sEstimated | 4GB (have 141GB) |
| Qwen/Qwen3-4B | FP16 | Fits comfortably | 277.19 tok/sEstimated | 9GB (have 141GB) |
| Qwen/Qwen3-30B-A3B-Instruct-2507 | Q4 | Fits comfortably | 343.71 tok/sEstimated | 15GB (have 141GB) |
| google-t5/t5-3b | Q8 | Fits comfortably | 543.51 tok/sEstimated | 3GB (have 141GB) |
| google-t5/t5-3b | FP16 | Fits comfortably | 343.50 tok/sEstimated | 6GB (have 141GB) |
| meta-llama/Meta-Llama-3-8B-Instruct | FP16 | Fits comfortably | 237.97 tok/sEstimated | 17GB (have 141GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | Q4 | Fits comfortably | 661.64 tok/sEstimated | 3GB (have 141GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | Q8 | Fits comfortably | 508.74 tok/sEstimated | 5GB (have 141GB) |
| Qwen/Qwen2.5-1.5B | Q8 | Fits comfortably | 479.10 tok/sEstimated | 5GB (have 141GB) |
| Qwen/Qwen2.5-1.5B | FP16 | Fits comfortably | 254.57 tok/sEstimated | 11GB (have 141GB) |
| Qwen/Qwen2.5-14B-Instruct | Q4 | Fits comfortably | 567.14 tok/sEstimated | 7GB (have 141GB) |
| Qwen/Qwen2.5-14B-Instruct | Q8 | Fits comfortably | 332.17 tok/sEstimated | 14GB (have 141GB) |
| Qwen/Qwen2.5-0.5B | Q8 | Fits comfortably | 444.56 tok/sEstimated | 5GB (have 141GB) |
| Qwen/Qwen2.5-0.5B | FP16 | Fits comfortably | 261.43 tok/sEstimated | 11GB (have 141GB) |
| meta-llama/Llama-3.1-70B-Instruct | Q4 | Fits comfortably | 238.34 tok/sEstimated | 34GB (have 141GB) |
| zai-org/GLM-4.6-FP8 | Q8 | Fits comfortably | 516.40 tok/sEstimated | 7GB (have 141GB) |
| zai-org/GLM-4.6-FP8 | FP16 | Fits comfortably | 256.62 tok/sEstimated | 15GB (have 141GB) |
| deepseek-ai/DeepSeek-V3.1 | FP16 | Fits comfortably | 280.41 tok/sEstimated | 15GB (have 141GB) |
| meta-llama/Llama-3.1-8B | Q4 | Fits comfortably | 747.62 tok/sEstimated | 4GB (have 141GB) |
| meta-llama/Llama-3.1-8B | Q8 | Fits comfortably | 494.06 tok/sEstimated | 9GB (have 141GB) |
| LiquidAI/LFM2-1.2B | Q8 | Fits comfortably | 587.46 tok/sEstimated | 2GB (have 141GB) |
| unsloth/Meta-Llama-3.1-8B-Instruct | Q8 | Fits comfortably | 457.50 tok/sEstimated | 9GB (have 141GB) |
| unsloth/Meta-Llama-3.1-8B-Instruct | FP16 | Fits comfortably | 261.98 tok/sEstimated | 17GB (have 141GB) |
| meta-llama/Meta-Llama-3-70B-Instruct | Q4 | Fits comfortably | 237.83 tok/sEstimated | 34GB (have 141GB) |
| meta-llama/Meta-Llama-3-70B-Instruct | Q8 | Fits comfortably | 185.61 tok/sEstimated | 68GB (have 141GB) |
| Qwen/Qwen2.5-Math-1.5B | FP16 | Fits comfortably | 285.10 tok/sEstimated | 11GB (have 141GB) |
| trl-internal-testing/tiny-random-LlamaForCausalLM | Q4 | Fits comfortably | 718.80 tok/sEstimated | 4GB (have 141GB) |
| Qwen/Qwen3-Embedding-4B | Q4 | Fits comfortably | 662.33 tok/sEstimated | 2GB (have 141GB) |
| Qwen/Qwen3-Embedding-4B | Q8 | Fits comfortably | 477.16 tok/sEstimated | 4GB (have 141GB) |
| Qwen/Qwen3-Embedding-4B | FP16 | Fits comfortably | 265.14 tok/sEstimated | 9GB (have 141GB) |
| unsloth/mistral-7b-v0.3-bnb-4bit | FP16 | Fits comfortably | 241.52 tok/sEstimated | 15GB (have 141GB) |
| Qwen/Qwen2.5-14B | Q4 | Fits comfortably | 491.17 tok/sEstimated | 7GB (have 141GB) |
| Qwen/Qwen2.5-14B | Q8 | Fits comfortably | 340.33 tok/sEstimated | 14GB (have 141GB) |
| Qwen/Qwen2-1.5B-Instruct | Q8 | Fits comfortably | 473.49 tok/sEstimated | 5GB (have 141GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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