Quick Answer: NVIDIA A100 40GB PCIe offers 40GB VRAM and starts around current market pricing. It delivers approximately 305 tokens/sec on deepseek-ai/DeepSeek-OCR. It typically draws 250W 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 | 305.06 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-2b | Q4 | 299.56 tok/sEstimated Auto-generated benchmark | 1GB |
| google-t5/t5-3b | Q4 | 292.06 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 292.02 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B | Q4 | 291.66 tok/sEstimated Auto-generated benchmark | 1GB |
| nari-labs/Dia2-2B | Q4 | 291.41 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 288.71 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 288.46 tok/sEstimated Auto-generated benchmark | 2GB |
| ibm-research/PowerMoE-3b | Q4 | 286.95 tok/sEstimated Auto-generated benchmark | 2GB |
| bigcode/starcoder2-3b | Q4 | 286.26 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-3-1b-it | Q4 | 286.00 tok/sEstimated Auto-generated benchmark | 1GB |
| facebook/sam3 | Q4 | 283.67 tok/sEstimated Auto-generated benchmark | 1GB |
| google-bert/bert-base-uncased | Q4 | 279.10 tok/sEstimated Auto-generated benchmark | 1GB |
| inference-net/Schematron-3B | Q4 | 278.91 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-2-2b-it | Q4 | 278.86 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/gemma-3-1b-it | Q4 | 272.47 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B | Q4 | 267.77 tok/sEstimated Auto-generated benchmark | 2GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 266.87 tok/sEstimated Auto-generated benchmark | 1GB |
| allenai/OLMo-2-0425-1B | Q4 | 265.74 tok/sEstimated Auto-generated benchmark | 1GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 263.70 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 261.73 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B | Q4 | 261.26 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 258.34 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 257.39 tok/sEstimated Auto-generated benchmark | 2GB |
| LiquidAI/LFM2-1.2B | Q4 | 255.31 tok/sEstimated Auto-generated benchmark | 1GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 253.25 tok/sEstimated Auto-generated benchmark | 1GB |
| google/embeddinggemma-300m | Q4 | 253.20 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 253.12 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 252.58 tok/sEstimated Auto-generated benchmark | 1GB |
| IlyaGusev/saiga_llama3_8b | Q4 | 249.78 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-R1-0528 | Q4 | 249.76 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/Phi-3.5-mini-instruct | Q4 | 249.38 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-R1-Distill-Llama-8B | Q4 | 249.03 tok/sEstimated Auto-generated benchmark | 4GB |
| mistralai/Mistral-7B-v0.1 | Q4 | 247.89 tok/sEstimated Auto-generated benchmark | 4GB |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q4 | 247.60 tok/sEstimated Auto-generated benchmark | 4GB |
| tencent/HunyuanOCR | Q4 | 247.59 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-Guard-3-8B | Q4 | 247.34 tok/sEstimated Auto-generated benchmark | 4GB |
| GSAI-ML/LLaDA-8B-Instruct | Q4 | 247.20 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-7B | Q4 | 246.36 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 245.70 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen3-4B | Q4 | 245.62 tok/sEstimated Auto-generated benchmark | 2GB |
| trl-internal-testing/tiny-LlamaForCausalLM-3.2 | Q4 | 245.56 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-8B | Q4 | 245.44 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-Reranker-0.6B | Q4 | 245.36 tok/sEstimated Auto-generated benchmark | 3GB |
| Qwen/Qwen3-Embedding-4B | Q4 | 245.00 tok/sEstimated Auto-generated benchmark | 2GB |
| HuggingFaceTB/SmolLM-135M | Q4 | 244.51 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Meta-Llama-3-8B | Q4 | 244.31 tok/sEstimated Auto-generated benchmark | 4GB |
| black-forest-labs/FLUX.2-dev | Q4 | 244.26 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/DialoGPT-small | Q4 | 243.04 tok/sEstimated Auto-generated benchmark | 4GB |
| allenai/Olmo-3-7B-Think | Q4 | 242.76 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 |
|---|---|---|---|---|
| openai-community/gpt2 | FP16 | Fits comfortably | 82.14 tok/sEstimated | 15GB (have 40GB) |
| Qwen/Qwen2.5-7B-Instruct | Q4 | Fits comfortably | 212.12 tok/sEstimated | 4GB (have 40GB) |
| Qwen/Qwen2.5-7B-Instruct | Q8 | Fits comfortably | 157.17 tok/sEstimated | 7GB (have 40GB) |
| Qwen/Qwen2.5-7B-Instruct | FP16 | Fits comfortably | 93.89 tok/sEstimated | 15GB (have 40GB) |
| Qwen/Qwen3-0.6B | FP16 | Fits comfortably | 86.25 tok/sEstimated | 13GB (have 40GB) |
| meta-llama/Llama-3.1-8B-Instruct | Q8 | Fits comfortably | 157.58 tok/sEstimated | 9GB (have 40GB) |
| meta-llama/Llama-3.1-8B-Instruct | FP16 | Fits comfortably | 80.80 tok/sEstimated | 17GB (have 40GB) |
| dphn/dolphin-2.9.1-yi-1.5-34b | Q4 | Fits comfortably | 82.01 tok/sEstimated | 17GB (have 40GB) |
| dphn/dolphin-2.9.1-yi-1.5-34b | Q8 | Fits comfortably | 58.89 tok/sEstimated | 35GB (have 40GB) |
| openai/gpt-oss-20b | FP16 | Not supported | 46.10 tok/sEstimated | 41GB (have 40GB) |
| google/gemma-3-1b-it | Q4 | Fits comfortably | 286.00 tok/sEstimated | 1GB (have 40GB) |
| google/gemma-3-1b-it | Q8 | Fits comfortably | 175.67 tok/sEstimated | 1GB (have 40GB) |
| google/gemma-3-1b-it | FP16 | Fits comfortably | 96.54 tok/sEstimated | 2GB (have 40GB) |
| Qwen/Qwen3-Embedding-0.6B | Q8 | Fits comfortably | 166.01 tok/sEstimated | 6GB (have 40GB) |
| facebook/opt-125m | FP16 | Fits comfortably | 83.94 tok/sEstimated | 15GB (have 40GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | Fits comfortably | 253.12 tok/sEstimated | 1GB (have 40GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q8 | Fits comfortably | 194.52 tok/sEstimated | 1GB (have 40GB) |
| Qwen/Qwen3-4B-Instruct-2507 | Q8 | Fits comfortably | 171.15 tok/sEstimated | 4GB (have 40GB) |
| Qwen/Qwen3-4B-Instruct-2507 | FP16 | Fits comfortably | 87.85 tok/sEstimated | 9GB (have 40GB) |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | Fits comfortably | 261.73 tok/sEstimated | 1GB (have 40GB) |
| meta-llama/Llama-3.2-1B-Instruct | Q8 | Fits comfortably | 182.83 tok/sEstimated | 1GB (have 40GB) |
| meta-llama/Llama-3.2-1B-Instruct | FP16 | Fits comfortably | 107.24 tok/sEstimated | 2GB (have 40GB) |
| openai/gpt-oss-120b | Q4 | Not supported | 44.76 tok/sEstimated | 59GB (have 40GB) |
| openai/gpt-oss-120b | Q8 | Not supported | 34.13 tok/sEstimated | 117GB (have 40GB) |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | Fits comfortably | 263.70 tok/sEstimated | 2GB (have 40GB) |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q8 | Fits comfortably | 189.76 tok/sEstimated | 3GB (have 40GB) |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | FP16 | Fits comfortably | 99.35 tok/sEstimated | 6GB (have 40GB) |
| mistralai/Mistral-7B-Instruct-v0.2 | Q4 | Fits comfortably | 230.33 tok/sEstimated | 4GB (have 40GB) |
| mistralai/Mistral-7B-Instruct-v0.2 | Q8 | Fits comfortably | 143.52 tok/sEstimated | 7GB (have 40GB) |
| mistralai/Mistral-7B-Instruct-v0.2 | FP16 | Fits comfortably | 86.44 tok/sEstimated | 15GB (have 40GB) |
| Qwen/Qwen3-8B | Q8 | Fits comfortably | 160.82 tok/sEstimated | 9GB (have 40GB) |
| Qwen/Qwen3-8B | FP16 | Fits comfortably | 78.21 tok/sEstimated | 17GB (have 40GB) |
| inference-net/Schematron-3B | Q4 | Fits comfortably | 278.91 tok/sEstimated | 2GB (have 40GB) |
| inference-net/Schematron-3B | Q8 | Fits comfortably | 204.68 tok/sEstimated | 3GB (have 40GB) |
| inference-net/Schematron-3B | FP16 | Fits comfortably | 109.19 tok/sEstimated | 6GB (have 40GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | Q4 | Fits comfortably | 71.99 tok/sEstimated | 16GB (have 40GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | Q8 | Fits comfortably | 57.95 tok/sEstimated | 33GB (have 40GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | FP16 | Not supported | 30.91 tok/sEstimated | 66GB (have 40GB) |
| Qwen/Qwen2.5-7B | FP16 | Fits comfortably | 92.88 tok/sEstimated | 15GB (have 40GB) |
| Qwen/Qwen3-Next-80B-A3B-Instruct | Q4 | Fits (tight) | 44.99 tok/sEstimated | 39GB (have 40GB) |
| allenai/OLMo-2-0425-1B | FP16 | Fits comfortably | 109.38 tok/sEstimated | 2GB (have 40GB) |
| microsoft/Phi-3-mini-4k-instruct | Q4 | Fits comfortably | 239.34 tok/sEstimated | 4GB (have 40GB) |
| microsoft/Phi-3-mini-4k-instruct | Q8 | Fits comfortably | 159.70 tok/sEstimated | 7GB (have 40GB) |
| microsoft/Phi-3-mini-4k-instruct | FP16 | Fits comfortably | 82.87 tok/sEstimated | 15GB (have 40GB) |
| openai-community/gpt2-large | Q8 | Fits comfortably | 144.36 tok/sEstimated | 7GB (have 40GB) |
| openai-community/gpt2-large | FP16 | Fits comfortably | 93.75 tok/sEstimated | 15GB (have 40GB) |
| Qwen/Qwen3-1.7B | Q4 | Fits comfortably | 214.33 tok/sEstimated | 4GB (have 40GB) |
| Qwen/Qwen3-1.7B | Q8 | Fits comfortably | 148.42 tok/sEstimated | 7GB (have 40GB) |
| Qwen/Qwen3-1.7B | FP16 | Fits comfortably | 79.76 tok/sEstimated | 15GB (have 40GB) |
| openai-community/gpt2 | Q8 | Fits comfortably | 158.89 tok/sEstimated | 7GB (have 40GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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