Quick Answer: RTX 5070 offers 12GB VRAM and starts around $761.10. It delivers approximately 144 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 | 143.92 tok/sEstimated Auto-generated benchmark | 2GB |
| nari-labs/Dia2-2B | Q4 | 141.95 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 141.74 tok/sEstimated Auto-generated benchmark | 1GB |
| allenai/OLMo-2-0425-1B | Q4 | 141.60 tok/sEstimated Auto-generated benchmark | 1GB |
| inference-net/Schematron-3B | Q4 | 136.31 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-2b | Q4 | 134.87 tok/sEstimated Auto-generated benchmark | 1GB |
| LiquidAI/LFM2-1.2B | Q4 | 134.12 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 133.85 tok/sEstimated Auto-generated benchmark | 2GB |
| tencent/HunyuanOCR | Q4 | 133.76 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 133.64 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 133.56 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/gemma-3-1b-it | Q4 | 132.21 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 131.10 tok/sEstimated Auto-generated benchmark | 1GB |
| google/embeddinggemma-300m | Q4 | 129.89 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 128.63 tok/sEstimated Auto-generated benchmark | 1GB |
| bigcode/starcoder2-3b | Q4 | 128.30 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-3B | Q4 | 127.58 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B | Q4 | 127.44 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B | Q4 | 126.17 tok/sEstimated Auto-generated benchmark | 2GB |
| google-t5/t5-3b | Q4 | 125.71 tok/sEstimated Auto-generated benchmark | 2GB |
| google-bert/bert-base-uncased | Q4 | 125.34 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 124.90 tok/sEstimated Auto-generated benchmark | 2GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 124.33 tok/sEstimated Auto-generated benchmark | 2GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 120.35 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2-2b-it | Q4 | 120.32 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-3-1b-it | Q4 | 119.93 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 119.49 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-research/PowerMoE-3b | Q4 | 119.37 tok/sEstimated Auto-generated benchmark | 2GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 118.94 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 118.38 tok/sEstimated Auto-generated benchmark | 2GB |
| lmstudio-community/Qwen3-4B-Thinking-2507-MLX-4bit | Q4 | 118.32 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-7B | Q4 | 118.23 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/Phi-3-mini-4k-instruct | Q4 | 117.77 tok/sEstimated Auto-generated benchmark | 4GB |
| EleutherAI/pythia-70m-deduped | Q4 | 117.51 tok/sEstimated Auto-generated benchmark | 4GB |
| facebook/sam3 | Q4 | 117.47 tok/sEstimated Auto-generated benchmark | 1GB |
| huggyllama/llama-7b | Q4 | 117.26 tok/sEstimated Auto-generated benchmark | 4GB |
| facebook/opt-125m | Q4 | 117.20 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-4B-Base | Q4 | 117.14 tok/sEstimated Auto-generated benchmark | 2GB |
| microsoft/Phi-3.5-mini-instruct | Q4 | 117.04 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Llama-3.1-8B-Instruct | Q4 | 116.74 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-Coder-1.5B | Q4 | 116.62 tok/sEstimated Auto-generated benchmark | 3GB |
| Qwen/Qwen3-4B-Thinking-2507 | Q4 | 116.54 tok/sEstimated Auto-generated benchmark | 2GB |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-4bit | Q4 | 116.10 tok/sEstimated Auto-generated benchmark | 4GB |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q4 | 116.01 tok/sEstimated Auto-generated benchmark | 4GB |
| swiss-ai/Apertus-8B-Instruct-2509 | Q4 | 115.80 tok/sEstimated Auto-generated benchmark | 4GB |
| dicta-il/dictalm2.0-instruct | Q4 | 115.74 tok/sEstimated Auto-generated benchmark | 4GB |
| IlyaGusev/saiga_llama3_8b | Q4 | 115.63 tok/sEstimated Auto-generated benchmark | 4GB |
| MiniMaxAI/MiniMax-M2 | Q4 | 115.14 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-8B-Base | Q4 | 115.10 tok/sEstimated Auto-generated benchmark | 4GB |
| rednote-hilab/dots.ocr | Q4 | 114.93 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 |
|---|---|---|---|---|
| google/gemma-3-1b-it | Q4 | Fits comfortably | 119.93 tok/sEstimated | 1GB (have 12GB) |
| google/gemma-3-1b-it | Q8 | Fits comfortably | 82.44 tok/sEstimated | 1GB (have 12GB) |
| google/gemma-3-1b-it | FP16 | Fits comfortably | 45.79 tok/sEstimated | 2GB (have 12GB) |
| Qwen/Qwen3-Embedding-0.6B | Q4 | Fits comfortably | 108.09 tok/sEstimated | 3GB (have 12GB) |
| facebook/opt-125m | FP16 | Not supported | 43.16 tok/sEstimated | 15GB (have 12GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | Fits comfortably | 133.64 tok/sEstimated | 1GB (have 12GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q8 | Fits comfortably | 85.12 tok/sEstimated | 1GB (have 12GB) |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | FP16 | Fits comfortably | 48.54 tok/sEstimated | 2GB (have 12GB) |
| meta-llama/Llama-3.2-1B-Instruct | FP16 | Fits comfortably | 44.66 tok/sEstimated | 2GB (have 12GB) |
| openai/gpt-oss-120b | Q4 | Not supported | 22.60 tok/sEstimated | 59GB (have 12GB) |
| Qwen/Qwen3-8B | Q8 | Fits comfortably | 68.37 tok/sEstimated | 9GB (have 12GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | Q4 | Not supported | 35.01 tok/sEstimated | 16GB (have 12GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | Q8 | Not supported | 24.16 tok/sEstimated | 33GB (have 12GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | FP16 | Not supported | 13.34 tok/sEstimated | 66GB (have 12GB) |
| distilbert/distilgpt2 | Q4 | Fits comfortably | 112.87 tok/sEstimated | 4GB (have 12GB) |
| Qwen/Qwen2.5-7B | FP16 | Not supported | 38.79 tok/sEstimated | 15GB (have 12GB) |
| Qwen/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 109.54 tok/sEstimated | 3GB (have 12GB) |
| Qwen/Qwen2.5-0.5B-Instruct | Q8 | Fits comfortably | 76.00 tok/sEstimated | 5GB (have 12GB) |
| Qwen/Qwen2.5-0.5B-Instruct | FP16 | Fits (tight) | 38.63 tok/sEstimated | 11GB (have 12GB) |
| Qwen/Qwen3-Next-80B-A3B-Instruct | Q4 | Not supported | 23.66 tok/sEstimated | 39GB (have 12GB) |
| microsoft/Phi-3-mini-4k-instruct | Q8 | Fits comfortably | 68.96 tok/sEstimated | 7GB (have 12GB) |
| microsoft/Phi-3-mini-4k-instruct | FP16 | Not supported | 38.46 tok/sEstimated | 15GB (have 12GB) |
| openai-community/gpt2-large | Q4 | Fits comfortably | 110.27 tok/sEstimated | 4GB (have 12GB) |
| meta-llama/Meta-Llama-3-8B-Instruct | Q4 | Fits comfortably | 101.44 tok/sEstimated | 4GB (have 12GB) |
| meta-llama/Meta-Llama-3-8B-Instruct | Q8 | Fits comfortably | 74.15 tok/sEstimated | 9GB (have 12GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B | FP16 | Fits (tight) | 41.70 tok/sEstimated | 11GB (have 12GB) |
| mlx-community/gpt-oss-20b-MXFP4-Q8 | Q4 | Fits comfortably | 55.61 tok/sEstimated | 10GB (have 12GB) |
| Qwen/Qwen2.5-1.5B | Q8 | Fits comfortably | 80.17 tok/sEstimated | 5GB (have 12GB) |
| Qwen/Qwen2.5-1.5B | FP16 | Fits (tight) | 37.30 tok/sEstimated | 11GB (have 12GB) |
| Qwen/Qwen2.5-14B-Instruct | Q4 | Fits comfortably | 85.00 tok/sEstimated | 7GB (have 12GB) |
| Qwen/Qwen2.5-14B-Instruct | Q8 | Not supported | 61.26 tok/sEstimated | 14GB (have 12GB) |
| Qwen/Qwen2.5-14B-Instruct | FP16 | Not supported | 29.44 tok/sEstimated | 29GB (have 12GB) |
| Qwen/Qwen2.5-0.5B | FP16 | Fits (tight) | 37.77 tok/sEstimated | 11GB (have 12GB) |
| meta-llama/Llama-3.1-70B-Instruct | Q4 | Not supported | 35.42 tok/sEstimated | 34GB (have 12GB) |
| HuggingFaceTB/SmolLM2-135M | Q8 | Fits comfortably | 73.76 tok/sEstimated | 7GB (have 12GB) |
| zai-org/GLM-4.5-Air | Q4 | Fits comfortably | 111.21 tok/sEstimated | 4GB (have 12GB) |
| zai-org/GLM-4.5-Air | Q8 | Fits comfortably | 72.82 tok/sEstimated | 7GB (have 12GB) |
| zai-org/GLM-4.5-Air | FP16 | Not supported | 44.39 tok/sEstimated | 15GB (have 12GB) |
| unsloth/Meta-Llama-3.1-8B-Instruct | Q4 | Fits comfortably | 107.10 tok/sEstimated | 4GB (have 12GB) |
| unsloth/Meta-Llama-3.1-8B-Instruct | Q8 | Fits comfortably | 72.13 tok/sEstimated | 9GB (have 12GB) |
| unsloth/gpt-oss-20b-BF16 | Q8 | Not supported | 40.47 tok/sEstimated | 20GB (have 12GB) |
| unsloth/gpt-oss-20b-BF16 | FP16 | Not supported | 20.65 tok/sEstimated | 41GB (have 12GB) |
| HuggingFaceTB/SmolLM-135M | Q4 | Fits comfortably | 98.79 tok/sEstimated | 4GB (have 12GB) |
| Qwen/Qwen2.5-Math-1.5B | Q8 | Fits comfortably | 71.11 tok/sEstimated | 5GB (have 12GB) |
| IlyaGusev/saiga_llama3_8b | Q4 | Fits comfortably | 115.63 tok/sEstimated | 4GB (have 12GB) |
| IlyaGusev/saiga_llama3_8b | Q8 | Fits comfortably | 81.34 tok/sEstimated | 9GB (have 12GB) |
| IlyaGusev/saiga_llama3_8b | FP16 | Not supported | 38.93 tok/sEstimated | 17GB (have 12GB) |
| Qwen/Qwen2.5-Coder-1.5B | Q4 | Fits comfortably | 116.62 tok/sEstimated | 3GB (have 12GB) |
| Qwen/Qwen2.5-Coder-1.5B | Q8 | Fits comfortably | 69.16 tok/sEstimated | 5GB (have 12GB) |
| Qwen/Qwen3-0.6B | FP16 | Not supported | 40.02 tok/sEstimated | 13GB (have 12GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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