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Can the NVIDIA GeForce RTX 5090 run Qwen1.5 32B Chat?

73 ptsGreat (A) · 73 of 100 points: Model quality 18.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q4_K_M it needs about 24.2 GB of 32.0 GB usable, with an estimated speed of 67.7 tok/s.

Best quant
Q4_K_M
Generation speed
67.7 tok/s
Prompt processing
2,321 tok/s
First token (1K prompt)
0.4 s
Largest safe context
32K

Download Qwen1.5 32B Chat

Recommended for the NVIDIA GeForce RTX 5090: Q4_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run qwen:32b-chat-v1.5-q4_K_M

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q4_K_M file (opens in a new tab)

huggingface.co/Qwen/Qwen1.5-32B-Chat-GGUF (opens in a new tab)

ollama run hf.co/Qwen/Qwen1.5-32B-Chat-GGUF:Q4_K_M

Original weights · Hugging Face

Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.

huggingface.co/Qwen/Qwen1.5-32B-Chat (opens in a new tab)

No sign-in needed.

Links checked 1 week ago against Hugging Face, Ollama and GitHub.

How the A grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.18.8 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total73.8 / 10073 ptsGreat (A) · 73 of 100 points: Model quality 18.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the NVIDIA GeForce RTX 5090

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 17.4 GB 32.0 GB 111 tok/s Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 13.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.5/15 GGUF (opens in a new tab)
Q3_K_M 20.3 GB 32.0 GB 87.5 tok/s Runs well 71 ptsGood (B) · 71 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.6/15 GGUF (opens in a new tab)
Q4_K_M 24.2 GB 32.0 GB 67.7 tok/s Runs well 73 ptsGreat (A) · 73 of 100 points: Model quality 18.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 27.4 GB 32.0 GB 55.9 tok/s Tight fit 73 ptsGreat (A) · 73 of 100 points: Model quality 19.2/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 31.0 GB 32.0 GB 46.9 tok/s Tight fit 73 ptsGreat (A) · 73 of 100 points: Model quality 19.6/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 38.8 GB 32.0 GB 5.6 tok/s Runs with offload 50 ptsUsable (C) · 50 of 100 points: Model quality 19.8/45, Memory fit 10.0/25, Speed 5.6/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 69.4 GB 32.0 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.