Qwen3 32B
Standard benchmarks
Performance across standard evaluations
| Benchmark | Score |
|---|---|
| MMLU | 83.4 |
| HumanEval | 82.9 |
| MT-Bench | 8.7 |
| GSM8K | 94 |
Will it run on your hardware?
Pick your GPU memory - see which quantizations fit, and the cheapest card for the rest
Need an exact figure for your context length? Use the VRAM calculator.
Run it locally
Copy-paste - running in under a minute
ollama run qwen3:32bvllm serve Qwen/Qwen3-32BNew to this? Start with Ollama · serve to many users with vLLM.
Deep dive
Notes, sources, and the full write-up
Qwen3 32B
Qwen3 32B is Alibaba's flagship dense model in the Qwen3 lineup. At 32.8 billion parameters, it achieves 83.4 MMLU while fitting on a single RTX 4090 at Q4_K_M - making it the best quality-per-card model available.
Why Qwen3 32B is special
- 83.4 MMLU - highest of any 32B model, competitive with 70B models
- Fits on RTX 4090 - 19 GB at Q4_K_M
- Thinking mode - with adjustable thinking budget (0-8192 tokens)
- 4.8M+ monthly downloads - extremely popular
- 132K max context with YaRN extension
- 92 token support for batch inference
Benchmarks
| Benchmark | Qwen3 32B | R1 32B | Qwen3 14B | Llama 3.3 70B |
|---|---|---|---|---|
| MMLU | 83.4 | 72.6 | 77.0 | 86.0 |
| HumanEval | 82.9 | 57.2 | 80.5 | 81.7 |
| GSM8K | 94.0 | 94.3 | 88.0 | 95.1 |
| MT-Bench | 8.7 | 8.4 | 8.5 | 8.8 |
VRAM math
| Quant | VRAM | Recommended Hardware |
|---|---|---|
| Q4_K_M | ~19 GB | RTX 4090 (24GB) |
| Q5_K_M | ~23 GB | RTX 4090 (tight) |
| Q8_0 | ~34 GB | RTX 5090 |
| FP16 | ~64 GB | Dual RTX 5090 |
How to run
ollama run qwen3:32bWhat the community says
"Qwen3-32B on a single 4090 is the best local AI setup money can buy right now. 83 MMLU with thinking mode is insane for 32B."
- r/LocalLLaMA, 267 upvotes
Frequently asked
Quick answers to common questions
How much VRAM does Qwen3 32B need?
Qwen3 32B with 32B parameters needs approximately 19 GB at Q4_K_M quantization. Use our VRAM calculator for an exact estimate.
Is Qwen3 32B better than other Qwen models?
Qwen3 32B scores 83.4 on MMLU and 82.9 on HumanEval. It has 32B parameters with 32,768 context - a strong choice for general-purpose, coding, agents.
What license is Qwen3 32B under?
Qwen3 32B is released under the Apache 2.0 license, making it suitable for most commercial and personal projects.
What hardware runs Qwen3 32B well?
With 32B parameters, Qwen3 32B requires adequate VRAM. High-end GPUs like the RTX 4090 (24GB), RTX 5090 (32GB), or Mac Studio with unified memory are good options. Check our hardware directory for specific recommendations.
What is the best quantization for Qwen3 32B?
Q4_K_M is the recommended sweet spot - ~98% of FP16 quality at ~27% of the size. Q5_K_M (~23 GB) is an option if you have spare VRAM. Use our VRAM calculator to compare.
How long can Qwen3 32B's context window handle?
Qwen3 32B supports a 32,768-token context window - enough for most medium-length documents and conversations. Real-world usable context may vary by implementation.
What models compete with Qwen3 32B?
Qwen3 32B competes with other 16B–48B. Browse our model directory for comparisons, benchmarks, and community reviews to find the best fit.
Compare & pair with
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