Can an NVIDIA GeForce RTX 3090 run Qwen2.5-14B-Instruct?
Yes. Qwen2.5-14B-Instruct needs 17.8GB at Q8_0 with llama.cpp and 8K context; the NVIDIA GeForce RTX 3090 has 24GB of VRAM (23.5GB usable) — grade B, with decode speed in the interactive tier.
NVIDIA GeForce RTX 3090 · Qwen2.5-14B-Instruct · Q8_0
✅ Fits — grade B
assumes llama.cpp · batch 1 · 8K context · fp16 KV cache
Also runs with: Ollama (one-line install) · LM Studio (GUI) · KoboldCpp (GUI)
$1,499 MSRP · as of 2026-07-08
Also good for gaming — 1440p-class (estimated from FP32 compute, not a game benchmark).
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Every quant, graded
NVIDIA GeForce RTX 3090 × Qwen2.5-14B-Instruct, llama.cpp, 8K context.
| Quant | File size | Fit | Speed tier |
|---|---|---|---|
| Q8_0 | 15.7 GB | Fits · B | interactive |
| Q6_K | 12.1 GB | Fits · A | interactive |
| Q5_K_M | 10.5 GB | Fits · A | interactive |
| Q4_K_M | 9.0 GB | Fits · A | interactive |
More models on the NVIDIA GeForce RTX 3090
Verdict computed from published specs and measured GGUF file sizes — see how the math works.