Quick Answer: RTX 3080 offers 10GB VRAM and starts around $449.99. It delivers approximately 166 tokens/sec on google-bert/bert-base-uncased. It typically draws 320W 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 |
|---|---|---|---|
| google-bert/bert-base-uncased | Q4 | 165.90 tok/sEstimated Auto-generated benchmark | 1GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 164.92 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 164.59 tok/sEstimated Auto-generated benchmark | 2GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 162.95 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/DeepSeek-OCR | Q4 | 162.84 tok/sEstimated Auto-generated benchmark | 2GB |
| ibm-research/PowerMoE-3b | Q4 | 162.03 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 161.10 tok/sEstimated Auto-generated benchmark | 2GB |
| nari-labs/Dia2-2B | Q4 | 160.77 tok/sEstimated Auto-generated benchmark | 2GB |
| inference-net/Schematron-3B | Q4 | 160.41 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-3B | Q4 | 159.97 tok/sEstimated Auto-generated benchmark | 2GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 158.73 tok/sEstimated Auto-generated benchmark | 1GB |
| bigcode/starcoder2-3b | Q4 | 158.60 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 157.16 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 155.42 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 154.90 tok/sEstimated Auto-generated benchmark | 2GB |
| tencent/HunyuanOCR | Q4 | 154.89 tok/sEstimated Auto-generated benchmark | 1GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 152.45 tok/sEstimated Auto-generated benchmark | 1GB |
| facebook/sam3 | Q4 | 151.35 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 150.35 tok/sEstimated Auto-generated benchmark | 1GB |
| google/embeddinggemma-300m | Q4 | 149.94 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2-2b-it | Q4 | 145.74 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/gemma-3-1b-it | Q4 | 145.07 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B | Q4 | 144.41 tok/sEstimated Auto-generated benchmark | 1GB |
| google-t5/t5-3b | Q4 | 143.36 tok/sEstimated Auto-generated benchmark | 2GB |
| allenai/OLMo-2-0425-1B | Q4 | 143.24 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-3B | Q4 | 142.91 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 140.40 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 140.09 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2b | Q4 | 140.07 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-3-1b-it | Q4 | 138.73 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-1.5B-Instruct | Q4 | 138.08 tok/sEstimated Auto-generated benchmark | 3GB |
| deepseek-ai/DeepSeek-V3-0324 | Q4 | 137.90 tok/sEstimated Auto-generated benchmark | 4GB |
| LiquidAI/LFM2-1.2B | Q4 | 137.86 tok/sEstimated Auto-generated benchmark | 1GB |
| vikhyatk/moondream2 | Q4 | 137.37 tok/sEstimated Auto-generated benchmark | 4GB |
| GSAI-ML/LLaDA-8B-Instruct | Q4 | 137.31 tok/sEstimated Auto-generated benchmark | 4GB |
| zai-org/GLM-4.6-FP8 | Q4 | 137.03 tok/sEstimated Auto-generated benchmark | 4GB |
| Alibaba-NLP/gte-Qwen2-1.5B-instruct | Q4 | 136.97 tok/sEstimated Auto-generated benchmark | 3GB |
| Qwen/Qwen2-1.5B-Instruct | Q4 | 136.47 tok/sEstimated Auto-generated benchmark | 3GB |
| MiniMaxAI/MiniMax-M2 | Q4 | 135.86 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-7B-Instruct | Q4 | 135.09 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-V3 | Q4 | 135.03 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Llama-3.1-8B-Instruct | Q4 | 135.02 tok/sEstimated Auto-generated benchmark | 4GB |
| dicta-il/dictalm2.0-instruct | Q4 | 134.86 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/phi-4 | Q4 | 134.85 tok/sEstimated Auto-generated benchmark | 4GB |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q4 | 134.44 tok/sEstimated Auto-generated benchmark | 4GB |
| HuggingFaceTB/SmolLM-135M | Q4 | 134.06 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-0.5B | Q4 | 133.77 tok/sEstimated Auto-generated benchmark | 3GB |
| tencent/HunyuanVideo-1.5 | Q4 | 133.57 tok/sEstimated Auto-generated benchmark | 4GB |
| unsloth/Meta-Llama-3.1-8B-Instruct | Q4 | 133.52 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct | Q4 | 132.94 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 |
|---|---|---|---|---|
| meta-llama/Meta-Llama-3-8B-Instruct | Q4 | Fits comfortably | 123.79 tok/sEstimated | 4GB (have 10GB) |
| Qwen/Qwen2.5-1.5B | Q4 | Fits comfortably | 121.15 tok/sEstimated | 3GB (have 10GB) |
| meta-llama/Meta-Llama-3-8B | Q4 | Fits comfortably | 122.26 tok/sEstimated | 4GB (have 10GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-7B | Q8 | Fits comfortably | 84.50 tok/sEstimated | 7GB (have 10GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-7B | FP16 | Not supported | 49.55 tok/sEstimated | 15GB (have 10GB) |
| deepseek-ai/DeepSeek-R1-Distill-Llama-8B | Q8 | Fits (tight) | 92.11 tok/sEstimated | 9GB (have 10GB) |
| ibm-research/PowerMoE-3b | Q8 | Fits comfortably | 109.87 tok/sEstimated | 3GB (have 10GB) |
| ibm-research/PowerMoE-3b | FP16 | Fits comfortably | 57.52 tok/sEstimated | 6GB (have 10GB) |
| lmstudio-community/Qwen3-4B-Thinking-2507-MLX-6bit | Q4 | Fits comfortably | 124.62 tok/sEstimated | 2GB (have 10GB) |
| lmstudio-community/Qwen3-4B-Thinking-2507-MLX-6bit | Q8 | Fits comfortably | 94.99 tok/sEstimated | 4GB (have 10GB) |
| Qwen/Qwen3-1.7B-Base | FP16 | Not supported | 43.21 tok/sEstimated | 15GB (have 10GB) |
| baichuan-inc/Baichuan-M2-32B | Q8 | Not supported | 29.86 tok/sEstimated | 33GB (have 10GB) |
| baichuan-inc/Baichuan-M2-32B | FP16 | Not supported | 16.22 tok/sEstimated | 66GB (have 10GB) |
| ai-forever/ruGPT-3.5-13B | Q4 | Fits comfortably | 103.60 tok/sEstimated | 7GB (have 10GB) |
| tencent/HunyuanOCR | Q4 | Fits comfortably | 154.89 tok/sEstimated | 1GB (have 10GB) |
| tencent/HunyuanOCR | Q8 | Fits comfortably | 95.41 tok/sEstimated | 2GB (have 10GB) |
| tencent/HunyuanOCR | FP16 | Fits comfortably | 58.12 tok/sEstimated | 3GB (have 10GB) |
| facebook/sam3 | Q4 | Fits comfortably | 151.35 tok/sEstimated | 1GB (have 10GB) |
| facebook/sam3 | Q8 | Fits comfortably | 105.55 tok/sEstimated | 1GB (have 10GB) |
| facebook/sam3 | FP16 | Fits comfortably | 58.82 tok/sEstimated | 2GB (have 10GB) |
| Qwen/Qwen-Image-Edit-2509 | Q4 | Fits comfortably | 115.89 tok/sEstimated | 4GB (have 10GB) |
| google-bert/bert-base-uncased | Q8 | Fits comfortably | 112.65 tok/sEstimated | 1GB (have 10GB) |
| google-bert/bert-base-uncased | FP16 | Fits comfortably | 56.55 tok/sEstimated | 1GB (have 10GB) |
| MiniMaxAI/MiniMax-VL-01 | Q4 | Not supported | 14.82 tok/sEstimated | 256GB (have 10GB) |
| baichuan-inc/Baichuan-M2-32B | Q4 | Not supported | 42.25 tok/sEstimated | 16GB (have 10GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-8bit | Q4 | Not supported | 69.91 tok/sEstimated | 15GB (have 10GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-8bit | Q8 | Not supported | 47.97 tok/sEstimated | 31GB (have 10GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-6bit | Q8 | Not supported | 51.71 tok/sEstimated | 31GB (have 10GB) |
| deepseek-ai/DeepSeek-Math-V2 | Q4 | Not supported | 17.17 tok/sEstimated | 383GB (have 10GB) |
| mistralai/Mistral-7B-Instruct-v0.1 | Q4 | Fits comfortably | 124.36 tok/sEstimated | 4GB (have 10GB) |
| mistralai/Mistral-7B-Instruct-v0.1 | Q8 | Fits comfortably | 93.28 tok/sEstimated | 7GB (have 10GB) |
| Qwen/Qwen2-7B-Instruct | Q8 | Fits comfortably | 94.83 tok/sEstimated | 7GB (have 10GB) |
| deepseek-ai/DeepSeek-V2.5 | Q8 | Not supported | 33.71 tok/sEstimated | 656GB (have 10GB) |
| Qwen/Qwen2.5-7B-Instruct | FP16 | Not supported | 47.55 tok/sEstimated | 15GB (have 10GB) |
| Qwen/Qwen3-0.6B | Q4 | Fits comfortably | 121.19 tok/sEstimated | 3GB (have 10GB) |
| Qwen/Qwen2.5-3B-Instruct | Q4 | Fits comfortably | 140.40 tok/sEstimated | 2GB (have 10GB) |
| Qwen/Qwen2.5-3B-Instruct | Q8 | Fits comfortably | 98.32 tok/sEstimated | 3GB (have 10GB) |
| Qwen/Qwen2.5-3B-Instruct | FP16 | Fits comfortably | 57.64 tok/sEstimated | 6GB (have 10GB) |
| vikhyatk/moondream2 | Q4 | Fits comfortably | 137.37 tok/sEstimated | 4GB (have 10GB) |
| vikhyatk/moondream2 | Q8 | Fits comfortably | 81.74 tok/sEstimated | 7GB (have 10GB) |
| vikhyatk/moondream2 | FP16 | Not supported | 49.42 tok/sEstimated | 15GB (have 10GB) |
| petals-team/StableBeluga2 | Q4 | Fits comfortably | 123.30 tok/sEstimated | 4GB (have 10GB) |
| Qwen/Qwen3-0.6B-Base | Q4 | Fits comfortably | 130.69 tok/sEstimated | 3GB (have 10GB) |
| microsoft/Phi-4-mini-instruct | Q8 | Fits comfortably | 89.90 tok/sEstimated | 7GB (have 10GB) |
| microsoft/Phi-4-mini-instruct | FP16 | Not supported | 46.24 tok/sEstimated | 15GB (have 10GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-5bit | Q8 | Not supported | 48.55 tok/sEstimated | 31GB (have 10GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-5bit | FP16 | Not supported | 25.26 tok/sEstimated | 61GB (have 10GB) |
| moonshotai/Kimi-Linear-48B-A3B-Instruct | Q4 | Not supported | 39.91 tok/sEstimated | 25GB (have 10GB) |
| moonshotai/Kimi-Linear-48B-A3B-Instruct | Q8 | Not supported | 29.40 tok/sEstimated | 50GB (have 10GB) |
| openai/gpt-oss-20b | Q8 | Not supported | 51.68 tok/sEstimated | 20GB (have 10GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
Data-backed answers pulled from community benchmarks, manufacturer specs, and live pricing.
Owners running Qwen3-30B-A3B on a 10 GB RTX 3080 report roughly 15 tokens/sec after tuning, keeping interactive coding prompts responsive.
Source: Reddit – /r/LocalLLaMA (mquvxwc)
Some spec sheets assume higher ceilings, but real-world users note they already achieve ~10 tok/sec on a 10 GB 3080—showing how tuning beats blanket requirements.
Source: Reddit – /r/LocalLLaMA (mj408ke)
With larger context windows, Ollama reports 40% of layers moving to system RAM even on 12B models—illustrating the need to tune gpu_layers on 10 GB cards.
Source: Reddit – /r/LocalLLaMA (mnspe0d)
The RTX 3080 Founders Edition includes 10 GB GDDR6X, a 320 W board power, triple 8-pin power connectors, and NVIDIA recommends a 750 W PSU.
Source: TechPowerUp – RTX 3080 Specs
Latest snapshot (Nov 2025): Amazon at $699 (check current availability).
Source: Supabase price tracker snapshot – 2025-11-03
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Side-by-side VRAM, throughput, efficiency, and pricing benchmarks for both GPUs.
Side-by-side VRAM, throughput, efficiency, and pricing benchmarks for both GPUs.
Side-by-side VRAM, throughput, efficiency, and pricing benchmarks for both GPUs.