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localllm

Discrete GPU

GeForce RTX 4090

Data as of

Memory bandwidth
1,008 GB/s

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).

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).