Discrete GPU
GeForce RTX 4090
Data as of
- Memory bandwidth
- 1,008 GB/s
- Source
- Checked:
With 24 GB
One entry per model, up to 30, sorted by popularity. For each model we show the largest (most precise) quantization that fits in this memory with a context of at least 8K tokens. The context length is the longest one that quantization fits (for models whose maximum is under 8K, such as embedding models, that maximum). Models that are not for chat or text generation are labelled with their use. "Left" is the memory minus the estimate; under 5% of the memory is marked "tight" (not a guarantee that it fits).
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Context length 8,192 Estimated 25.6 GB 0.17 GB left (tight) Speed 25–34
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Ornith-1.5-9B BF16Context length 131,072 Estimated 23.8 GB 1.94 GB left Speed 33–44
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Context length 131,072 Estimated 25.5 GB 0.26 GB left (tight) Speed not estimated (MoE)
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Context length 65,536 Estimated 24.9 GB 0.87 GB left (tight) Speed not estimated (MoE)
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Context length 8,192 Estimated 25.7 GB 0.09 GB left (tight) Speed 25–34
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Context length 262,144 Estimated 23.6 GB 2.22 GB left Speed not estimated (MoE)
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Context length 65,536 Estimated 22.6 GB 3.15 GB left Speed 35–47
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Context length 65,536 Estimated 25.2 GB 0.57 GB left (tight) Speed not estimated (MoE)
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Context length 16,384 Estimated 25.7 GB 0.09 GB left (tight) Speed 25–34
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Context length 16,384 Estimated 24.7 GB 1.06 GB left (tight) Speed 27–36
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Ornith-1.0-9B BF16Context length 131,072 Estimated 23.3 GB 2.43 GB left Speed 34–45
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Context length 512 Estimated 2.41 GB 23.4 GB left Speed 452–603
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Context length 65,536 Estimated 25.3 GB 0.46 GB left (tight) Speed not estimated (MoE)
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Context length 131,072 Estimated 23.8 GB 1.97 GB left Speed 33–44
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Context length 40,960 Estimated 23.3 GB 2.49 GB left Speed 37–49
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Context length 65,536 Estimated 25.7 GB 0.05 GB left (tight) Speed 30–40
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Context length 32,768 Estimated 25.4 GB 0.42 GB left (tight) Speed not estimated (MoE)
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Context length 32,768 Estimated 22.1 GB 3.70 GB left Speed 37–49
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Context length 131,072 Estimated 23.8 GB 1.97 GB left Speed 33–44
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Context length 131,072 Estimated 23.3 GB 2.46 GB left Speed 34–45
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Context length 65,536 Estimated 25.3 GB 0.45 GB left (tight) Speed not estimated (MoE)
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Ternary-Bonsai-2-27B Q2_0Context length 131,072 Estimated 17.4 GB 8.35 GB left Speed 79–106
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Context length 131,072 Estimated 21.9 GB 3.86 GB left Speed 50–67
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Context length 262,144 Estimated 18.4 GB 7.42 GB left Speed 70–93
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Ornith-1.0-35B Q4_K_MContext length 131,072 Estimated 25.0 GB 0.78 GB left (tight) Speed not estimated (MoE)
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Context length 8,192 Estimated 25.3 GB 0.45 GB left (tight) Speed 26–34
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Context length 32,768 Estimated 25.3 GB 0.44 GB left (tight) Speed 28–37
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Wan2.1 Q4_K_MContext length 65,536 Estimated 22.3 GB 3.43 GB left Speed 36–48
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Context length 131,072 Estimated 21.9 GB 3.86 GB left Speed 50–67
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Context length 65,536 Estimated 12.5 GB 13.3 GB left Speed 148–197
Frequently asked questions
- Which local LLMs run on GeForce RTX 4090?
- On this site, 944 models have a quantization that fits in 24 GB at 8,192 tokens (estimated). Popular ones include Qwen3.8-27B, Ornith-1.5-9B, Huihui-Qwen3.6-35B-A3B-abliterated-MTP, Ornith-1.5-35B-A3B, Huihui-Qwen3.8-27B-abliterated.
- What is the largest model that runs on GeForce RTX 4090?
- Among the models listed here, Ling-3.0-flash (about 127.5B); Q1_0 fits in 24 GB (estimated at 8,192 tokens).
- How fast does GeForce RTX 4090 generate text?
- With 1,008 GB/s of memory bandwidth, Qwen3.8-27B at Q6_K (23.9 GB) runs at an estimated 25–34 tokens per second (60–80% of bandwidth ÷ file size; prompt processing not included).