NVIDIA · 24 GB GDDR6X · 1008 GB/s bandwidth ·
Alibaba · 7.6B · model ctx up to 32K
Yes — the RTX 4090 24GB (24 GB GDDR6X) can run Qwen2.5-Coder-7B-Instruct. At Q4 with the default 8K context it needs ≈ 6.7 GB VRAM (weights 4.18 GB + KV cache 1.52 GB + 1 GB runtime overhead), which fits within 24 GB. Decode at Q4/8K: ≈ 84.4 tok/s (estimated, batch 1). FP16 (≈ 17.72 GB) also fits, at ≈ 23.2 tok/s (estimated). 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
Quant
Context
VRAM needed
Fits?
tok/s (decode)
Q4
4K
5.94 GB
Yes
84.4est.
Q4
8K default
6.7 GB
Yes
84.4est.
Q4
32K
11.26 GB
Yes
84.4est.
FP16
4K
16.96 GB
Yes
23.2est.
FP16
8K default
17.72 GB
Yes
23.2est.
FP16
32K
22.28 GB
Yes
23.2est.
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).