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Can RTX 4090 24GB run Llama-4-Scout-17B-16E-Instruct?

NVIDIA · 24 GB GDDR6X · 1008 GB/s bandwidth · Meta · 109.0B (active 17.0B) · MoE · model ctx up to 10240K

No — Llama-4-Scout-17B-16E-Instruct at Q4 needs ≈ 62.65 GB even at 4K context, beyond the RTX 4090 24GB's 24 GB GDDR6X. It would only run with heavy CPU/disk offload. Decode at Q4/8K: ≈ 15.0 tok/s (estimated, batch 1). FP16 needs ≈ 222.4 GB — does not fit on this card. Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology.

Fit & speed by quant and context

QuantContextVRAM neededFits?tok/s (decode)
Q44K62.65 GBNo15.8 est.
Q48K default64.35 GBNo15.0 est.
Q432K74.55 GBNo11.2 est.
FP164K220.7 GBNo
FP168K default222.4 GBNo
FP1632K232.6 GBNo

Fits = weights + KV(ctx) + 1 GB overhead ≤ 95% of VRAM. Measured anchors are context-agnostic; the fit verdict is recomputed per context. A missing tok/s means the model is far beyond this card (offload-only territory).

VRAM breakdown at 8K context

QuantWeightsKV cacheOverheadTotal neededRTX 4090 24GB VRAM
Q459.95 GB3.4 GB1 GB64.35 GB24 GB
FP16218.0 GB3.4 GB1 GB222.4 GB24 GB

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