estimate
Can I run Qwen3.8-27B on an RTX 4090?
Yes, fully in VRAM (estimate)
Can I run Qwen3.8-27B on an RTX 4090? Yes, fully in VRAM (estimate). About 17.8 GB at Q4_K_M (estimate).
VRAM per quant for Qwen3.8-27B
Updated . The later of the hardware price date and the formula date.
| Quant | Context | Weights | KV | Overhead | Total | Usable | Fit | Est. tok/s |
|---|---|---|---|---|---|---|---|---|
| Q4 Q4_K_M | 8,192 tokens | 16.5 GB measured GGUF file size | 0.5 GB estimate | 0.8 GB estimate | 17.8 GB estimate | 23.4 GB estimate | full | 46 tok/s estimate |
| Q5 Q5 (~0.71 bytes/param) | 8,192 tokens | 19.7 GB estimate | 0.5 GB estimate | 0.8 GB estimate | 21.1 GB estimate | 23.4 GB estimate | full | 39 tok/s estimate |
| Q8 Q8 | 8,192 tokens | 29.7 GB estimate | 0.5 GB estimate | 0.8 GB estimate | 31.1 GB estimate | 23.4 GB estimate | no | — |
| FP16 FP16 | 8,192 tokens | 55.6 GB estimate | 0.5 GB estimate | 0.8 GB estimate | 56.9 GB estimate | 23.4 GB estimate | no | — |
| Q4, longer context | 32,768 tokens | 16.5 GB measured GGUF file size | 2.1 GB estimate | 0.8 GB estimate | 19.4 GB estimate | 23.4 GB estimate | full | 42 tok/s estimate |
Formula estimate, not a benchmark. Method →
community measurement, not ours
Canonical single-GPU figures on that results page: mean of five runs, one RTX 3090, the other replica stopped, the ~1K-token prompt column, 512-token greedy completions, reasoning disabled, 250 W power cap. The page says every rung is the same 4-bit checkpoint. llama.cpp out of the box 27.6 tokens per second; llama.cpp tuned (FA + q8 KV + MTP) 42.6; stock vLLM + MTP k=4 85.6; patched vLLM + MTP k=4 167.8; patched vLLM + DFlash2 k=7 212.1. The page dates the single-replica correction 31 August. results.html was last committed on 18 September 2026, which is the published date stored here. Not a localLLMrig measurement. Calculator estimates keep benchmarkSourceUrl null.
| Hardware | Tokens per second |
|---|---|
| RTX 3090, llama.cpp out of the box | 27.6 tok/s community measurement, not ours |
| RTX 3090, llama.cpp tuned (FA + q8 KV + MTP) | 42.6 tok/s community measurement, not ours |
| RTX 3090, stock vLLM + MTP k=4 | 85.6 tok/s community measurement, not ours |
| RTX 3090, patched vLLM + MTP k=4 | 167.8 tok/s community measurement, not ours |
| RTX 3090, patched vLLM + DFlash2 k=7 | 212.1 tok/s community measurement, not ours |
Qwen3.8-27B on RTX 3090, published 2026-09-18
This measurement stays separate from the formula estimate above.
Cheapest catalog option that fits at Q4
GeForce RTX 3090 24GB, used (median of sold listings), €1,224, dated 2026-10-16. No buy link.
This hardware
$2,446€2,185
used (median of sold listings)
price as of 16 Oct 2026
new (lowest in-stock EU): $4,243€3,790. GPU PRIX. Current low €3,790, MSI Gaming X Slim, Belgium. Page last updated 15 Oct 2026, checked 16 Oct 2026. In-stock boards in that table start at €3,990.
pcprice.watchUsed median €2,185, typical €2,074–€2,290, 111 sales, updated 16 Oct 2026. Not an EU retail listing.
Embed this
Qwen3.8-27B on RTX 4090
[](https://localllmrig.com/can-i-run/qwen3.8-27b/rtx-4090?utm_source=badge)
Questions
- Can I run Qwen3.8-27B on an RTX 4090?
- Yes, fully in VRAM (estimate).
- How much memory does Qwen3.8-27B need at Q4?
- About 17.8 GB at 8,192 tokens (estimate): 16.5 GB weights (measured GGUF file size), 0.5 GB KV cache, 0.8 GB overhead.
- How fast is Qwen3.8-27B on RTX 4090 (estimate)?
- About 46 tok/s at Q4 (estimate, not a benchmark).
Rig Report waitlist
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Read next: Building a local LLM rig in the RAMageddon.