Can RTX 3090 run Qwen3.6 27B?
Yes. Measured 40.2 tok/s generation (llama.cpp, llama-bench tg128 (quant per result); source).
Every measured result for Qwen3.6 27B on RTX 3090
| Build | Quant / setup | Engine | tok/s | |
|---|---|---|---|---|
| RTX 3090: 2026 models (llamabench community) | llama-bench tg128 (quant per result) | llama.cpp | 40.2 | source |
Memory: RTX 3090 has 24 GB. Qwen3.6 27B weights are about 16.7 GB at Q4_K_M (27.32B params × 4.89 bits ÷ 8, before context/KV cache). Arithmetic, not a measurement; long contexts need more. Check other quants in the VRAM calculator.
Speeds are decode (generation) tokens/sec as reported by each source; quant, engine and context differ, so small gaps are noise.
All measured speeds for Qwen3.6 27B: best home rig for Qwen3.6 27B.
Qwen3.6 27B on other hardware: RTX 4090 · RTX 5090
Other models measured on RTX 3090: DeepSeek R1 671B · Qwen3.6 35B-A3B · Qwen3.8 27B · gpt-oss 20B
Not enough VRAM? Rent before you buy. Run Qwen3.6 27B on a bigger GPU on a rented 24–96 GB cloud GPU by the hour and see the real speed before spending €1,000+. Try it on RunPod
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