Qwen3-32B on RTX 5090: Fits (Sep 2026)

Conditional memory judgement for one configuration. Change context, quant, or engine and the conclusion can change. Configuration used on this page: GGUF Q5_K_M (Qwen), 8,192 cached tokens, 1 sequence, engine llama.cpp. Status: Likely fits. Software: Not verified..

Likely fitsNot verifiedThis result is an estimate, not a measured trace.

Verdict on GeForce RTX 5090 32GB (desktop)

Yes, run Q5_K_M. The calculator puts it at 23.7 GiB–24.7 GiB at 8,192 tokens, inside 30.0 GiB of usable VRAM (after the driver reserve). Q8_0 is the next step up and does not clear the bar (34.6 GiB–35.7 GiB).

With Q5_K_M, the longest context that still counts as a fit is about 17,023 tokens of a 40,960-token native window, one sequence, fp16 KV cache.

Published GGUF quants for Qwen3-32B on GeForce RTX 5090 32GB (desktop) at 8,192 tokens
GGUF quantFile weightsKV cacheEstimated totalVerdict
Q8_032.4 GiB2.0 GiB34.6 GiB–35.7 GiBDoes not fit
Q6_K25.0 GiB2.0 GiB27.2 GiB–28.2 GiBTight
Q5_K_M (recommended)21.6 GiB2.0 GiB23.7 GiB–24.7 GiBFits
Q4_K_M18.4 GiB2.0 GiB20.5 GiB–21.4 GiBFits

Engine llama.cpp, one sequence, fp16 KV. File weights are the published GGUF sizes in the catalog. Totals come from the same calculator that powers the tool below; they are estimates, not a measurement of this setup.

Fixed page configuration

GGUF Q5_K_M needs 23.7 GiB-24.7 GiB at 8,192 tokens against 30.00 GiB net on GeForce RTX 5090 32GB (desktop). Q8_0, Q6_K are tight or over budget.

Technical identifiers and share data
  • Modelqwen3-32b
  • Hardwarenvidia-geforce-rtx-5090-32gb-desktop
  • Quantizationgguf-q5_k_m
  • Share fragment for this identityv2.eyJzY2hlbWFWZXJzaW9uIjoyLCJjYWxjdWxhdG9yVmVyc2lvbiI6IjAuMy4wIiwiZGF0YXNldFZlcnNpb24iOiIyMDI2LTEwLTAyLjEiLCJjb25maWciOnsibW9kZWxJZCI6InF3ZW4zLTMyYiIsImhhcmR3YXJlSWQiOiJudmlkaWEtZ2Vmb3JjZS1ydHgtNTA5MC0zMmdiLWRlc2t0b3AiLCJkZXZpY2VDb3VudCI6MSwicXVhbnRpemF0aW9uSWQiOiJnZ3VmLXE1X2tfbSIsImNvbnRleHRUb2tlbnMiOjgxOTIsImNvbmN1cnJlbnRTZXF1ZW5jZXMiOjEsImVuZ2luZSI6ImxsYW1hLmNwcCIsImt2VHlwZSI6ImZwMTYifX0

Memory breakdown

Weight artifact
21.62 GiB (23,214,831,232 bytes)
Raw KV cache
2.00 GiB (2,147,483,648 bytes)
Engine extras / workspace
0.13 GiB–1.07 GiB
Total estimated demand
23.75 GiB–24.69 GiB
Net calculator budget
30.00 GiB
OS / display reserve
2.00 GiB
Remaining vs net budget
5.31 GiB–6.25 GiB

24.69 GiB high estimate vs 30.00 GiB net

Enough memory does not mean this engine, quant, and OS will run. Support does not mean it will be fast.

Other published files on this device

Same model, device and context (8,192 tokens, 1 sequence, FP16 KV). Each row is one published weight-file set with its usual engine, sorted by memory.

QuantizationEngineEstimated memoryFit
BF16 safetensorsvllm63.65 GiB–65.58 GiBDoes not fit
GGUF Q8_0 (Qwen)llama.cpp34.55 GiB–35.72 GiBDoes not fit
GGUF Q6_K (Qwen)llama.cpp27.16 GiB–28.18 GiBTight fit
GGUF Q5_K_M (Qwen) This pagellama.cpp23.75 GiB–24.69 GiBFits
GGUF Q4_K_Mllama.cpp20.53 GiB–21.41 GiBFits

Assumptions that affect this result

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