Quick Answer: RTX 4060 offers 8GB VRAM and starts around $550.92. It delivers approximately 62 tokens/sec on deepseek-ai/DeepSeek-OCR. It typically draws 115W 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 | 61.60 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 58.67 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-research/PowerMoE-3b | Q4 | 58.43 tok/sEstimated Auto-generated benchmark | 2GB |
| bigcode/starcoder2-3b | Q4 | 58.25 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 57.59 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 57.25 tok/sEstimated Auto-generated benchmark | 1GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 57.02 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 56.95 tok/sEstimated Auto-generated benchmark | 2GB |
| google-bert/bert-base-uncased | Q4 | 56.57 tok/sEstimated Auto-generated benchmark | 1GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 56.41 tok/sEstimated Auto-generated benchmark | 2GB |
| google/embeddinggemma-300m | Q4 | 55.99 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B | Q4 | 55.82 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-2-2b-it | Q4 | 55.73 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 55.59 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 54.76 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 54.75 tok/sEstimated Auto-generated benchmark | 2GB |
| LiquidAI/LFM2-1.2B | Q4 | 54.63 tok/sEstimated Auto-generated benchmark | 1GB |
| nari-labs/Dia2-2B | Q4 | 54.50 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B | Q4 | 54.48 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/gemma-3-1b-it | Q4 | 54.36 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B | Q4 | 53.78 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 52.36 tok/sEstimated Auto-generated benchmark | 2GB |
| inference-net/Schematron-3B | Q4 | 51.31 tok/sEstimated Auto-generated benchmark | 2GB |
| tencent/HunyuanOCR | Q4 | 51.08 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-3-1b-it | Q4 | 50.56 tok/sEstimated Auto-generated benchmark | 1GB |
| facebook/sam3 | Q4 | 49.88 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 49.83 tok/sEstimated Auto-generated benchmark | 1GB |
| allenai/OLMo-2-0425-1B | Q4 | 49.58 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/DeepSeek-R1-0528 | Q4 | 49.34 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-V3 | Q4 | 49.27 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-Embedding-0.6B | Q4 | 49.24 tok/sEstimated Auto-generated benchmark | 3GB |
| Tongyi-MAI/Z-Image-Turbo | Q4 | 49.17 tok/sEstimated Auto-generated benchmark | 4GB |
| HuggingFaceM4/tiny-random-LlamaForCausalLM | Q4 | 49.07 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-4B | Q4 | 48.96 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-7B-Instruct | Q4 | 48.94 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-Embedding-8B | Q4 | 48.93 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-V3.1 | Q4 | 48.88 tok/sEstimated Auto-generated benchmark | 4GB |
| google/gemma-2b | Q4 | 48.80 tok/sEstimated Auto-generated benchmark | 1GB |
| llamafactory/tiny-random-Llama-3 | Q4 | 48.79 tok/sEstimated Auto-generated benchmark | 4GB |
| google-t5/t5-3b | Q4 | 48.73 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-Coder-1.5B | Q4 | 48.56 tok/sEstimated Auto-generated benchmark | 3GB |
| Qwen/Qwen3-4B-Thinking-2507-FP8 | Q4 | 48.56 tok/sEstimated Auto-generated benchmark | 2GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 48.52 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2-7B-Instruct | Q4 | 48.50 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-0.6B-Base | Q4 | 48.30 tok/sEstimated Auto-generated benchmark | 3GB |
| GSAI-ML/LLaDA-8B-Instruct | Q4 | 48.19 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-1.5B-Instruct | Q4 | 48.14 tok/sEstimated Auto-generated benchmark | 3GB |
| ibm-granite/granite-docling-258M | Q4 | 48.08 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Llama-3.1-8B-Instruct | Q4 | 48.01 tok/sEstimated Auto-generated benchmark | 4GB |
| lmsys/vicuna-7b-v1.5 | Q4 | 47.96 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 |
|---|---|---|---|---|
| petals-team/StableBeluga2 | FP16 | Not supported | 17.69 tok/sEstimated | 15GB (have 8GB) |
| meta-llama/Llama-3.2-1B | Q4 | Fits comfortably | 54.48 tok/sEstimated | 1GB (have 8GB) |
| meta-llama/Llama-3.2-1B | Q8 | Fits comfortably | 34.49 tok/sEstimated | 1GB (have 8GB) |
| meta-llama/Llama-3.2-1B | FP16 | Fits comfortably | 21.74 tok/sEstimated | 2GB (have 8GB) |
| Qwen/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 44.63 tok/sEstimated | 3GB (have 8GB) |
| Qwen/Qwen3-32B | Q4 | Not supported | 14.84 tok/sEstimated | 16GB (have 8GB) |
| microsoft/Phi-3-mini-4k-instruct | Q4 | Fits comfortably | 42.48 tok/sEstimated | 4GB (have 8GB) |
| microsoft/Phi-3-mini-4k-instruct | Q8 | Fits (tight) | 28.66 tok/sEstimated | 7GB (have 8GB) |
| microsoft/Phi-3-mini-4k-instruct | FP16 | Not supported | 18.63 tok/sEstimated | 15GB (have 8GB) |
| deepseek-ai/DeepSeek-R1-0528 | Q4 | Fits comfortably | 49.34 tok/sEstimated | 4GB (have 8GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-6bit | Q4 | Not supported | 22.58 tok/sEstimated | 15GB (have 8GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-6bit | Q8 | Not supported | 17.55 tok/sEstimated | 31GB (have 8GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-6bit | FP16 | Not supported | 9.05 tok/sEstimated | 61GB (have 8GB) |
| dicta-il/dictalm2.0-instruct | Q4 | Fits comfortably | 43.07 tok/sEstimated | 4GB (have 8GB) |
| HuggingFaceM4/tiny-random-LlamaForCausalLM | Q8 | Fits (tight) | 30.45 tok/sEstimated | 7GB (have 8GB) |
| HuggingFaceM4/tiny-random-LlamaForCausalLM | FP16 | Not supported | 17.02 tok/sEstimated | 15GB (have 8GB) |
| ai-forever/ruGPT-3.5-13B | FP16 | Not supported | 11.68 tok/sEstimated | 27GB (have 8GB) |
| MiniMaxAI/MiniMax-M1-40k | Q8 | Not supported | 3.48 tok/sEstimated | 510GB (have 8GB) |
| MiniMaxAI/MiniMax-M1-40k | FP16 | Not supported | 2.11 tok/sEstimated | 1020GB (have 8GB) |
| WeiboAI/VibeThinker-1.5B | Q4 | Fits comfortably | 57.02 tok/sEstimated | 1GB (have 8GB) |
| WeiboAI/VibeThinker-1.5B | Q8 | Fits comfortably | 38.89 tok/sEstimated | 2GB (have 8GB) |
| WeiboAI/VibeThinker-1.5B | FP16 | Fits comfortably | 21.52 tok/sEstimated | 4GB (have 8GB) |
| HuggingFaceTB/SmolLM-135M | Q8 | Fits (tight) | 33.31 tok/sEstimated | 7GB (have 8GB) |
| openai-community/gpt2 | Q8 | Fits (tight) | 31.17 tok/sEstimated | 7GB (have 8GB) |
| Qwen/Qwen2.5-7B-Instruct | FP16 | Not supported | 15.46 tok/sEstimated | 15GB (have 8GB) |
| Qwen/Qwen3-Embedding-0.6B | Q4 | Fits comfortably | 49.24 tok/sEstimated | 3GB (have 8GB) |
| Qwen/Qwen2.5-1.5B-Instruct | FP16 | Not supported | 18.70 tok/sEstimated | 11GB (have 8GB) |
| facebook/opt-125m | Q4 | Fits comfortably | 47.47 tok/sEstimated | 4GB (have 8GB) |
| facebook/opt-125m | Q8 | Fits (tight) | 34.50 tok/sEstimated | 7GB (have 8GB) |
| facebook/opt-125m | FP16 | Not supported | 16.59 tok/sEstimated | 15GB (have 8GB) |
| Qwen/Qwen3-Reranker-0.6B | FP16 | Not supported | 17.68 tok/sEstimated | 13GB (have 8GB) |
| meta-llama/Llama-3.1-70B-Instruct | Q8 | Not supported | 10.73 tok/sEstimated | 68GB (have 8GB) |
| microsoft/Phi-4-multimodal-instruct | Q8 | Fits (tight) | 32.68 tok/sEstimated | 7GB (have 8GB) |
| Qwen/Qwen3-Embedding-4B | Q8 | Fits comfortably | 31.71 tok/sEstimated | 4GB (have 8GB) |
| Qwen/Qwen3-Embedding-4B | FP16 | Not supported | 15.60 tok/sEstimated | 9GB (have 8GB) |
| Qwen/Qwen3-30B-A3B | FP16 | Not supported | 9.37 tok/sEstimated | 61GB (have 8GB) |
| IlyaGusev/saiga_llama3_8b | Q4 | Fits comfortably | 44.91 tok/sEstimated | 4GB (have 8GB) |
| Qwen/Qwen2-1.5B-Instruct | FP16 | Not supported | 17.73 tok/sEstimated | 11GB (have 8GB) |
| meta-llama/Llama-Guard-3-1B | Q4 | Fits comfortably | 54.76 tok/sEstimated | 1GB (have 8GB) |
| unsloth/Llama-3.2-1B-Instruct | Q8 | Fits comfortably | 36.90 tok/sEstimated | 1GB (have 8GB) |
| unsloth/Llama-3.2-1B-Instruct | FP16 | Fits comfortably | 21.62 tok/sEstimated | 2GB (have 8GB) |
| Tongyi-MAI/Z-Image-Turbo | Q4 | Fits comfortably | 49.17 tok/sEstimated | 4GB (have 8GB) |
| Tongyi-MAI/Z-Image-Turbo | Q8 | Fits (tight) | 33.07 tok/sEstimated | 8GB (have 8GB) |
| facebook/sam3 | FP16 | Fits comfortably | 22.40 tok/sEstimated | 2GB (have 8GB) |
| openai-community/gpt2 | FP16 | Not supported | 17.43 tok/sEstimated | 15GB (have 8GB) |
| Qwen/Qwen2.5-7B-Instruct | Q4 | Fits comfortably | 47.13 tok/sEstimated | 4GB (have 8GB) |
| Qwen/Qwen3-0.6B | Q8 | Fits comfortably | 28.49 tok/sEstimated | 6GB (have 8GB) |
| Qwen/Qwen3-0.6B | FP16 | Not supported | 17.23 tok/sEstimated | 13GB (have 8GB) |
| meta-llama/Llama-3.1-8B-Instruct | Q4 | Fits comfortably | 48.01 tok/sEstimated | 4GB (have 8GB) |
| petals-team/StableBeluga2 | Q8 | Fits (tight) | 33.40 tok/sEstimated | 7GB (have 8GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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