Qwen 3 32B
32B sweet-spot Qwen 3, Apache 2.0. Reasoning-mode toggle inherited from smaller siblings; strong on math, code and agentic tool use. Fits on a single H100 in fp16 and on a 4090 at Q4.
- Parameters
- 32B
- Context length
- 33K
- Modality
- text
- Released
- 2025-04-29
Memory & hardware
- VRAM (fp16)
- 64 GB
- VRAM (Q4)
- 19.2 GB
- Recommended
- H100 80GB (fp16) or RTX 4090 (Q4)
- Quantizations
- fp16, fp8, q8_0, q5_k_m, q4_k_m
Benchmarks
Hosted inference pricing
USD per million tokens.
| Provider | Input | Output | |
|---|---|---|---|
| together | $0.40 | $0.40 | |
| deepinfraCheapest | $0.10 | $0.30 |
Run it yourself
Drop-in commands for the three most common open-source inference paths. The Ollama tag is a best-effort match against the registry; verify the size variant before pulling.
vllm serve Qwen/Qwen3-32B
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-32B")
model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen3-32B", device_map="auto", torch_dtype="auto"
)Qwen/Qwen3-32B Related models
Same family or similar size — useful when shopping around.
32B sweet-spot model: strong reasoning, fits on one H100 in fp16, on a 4090 at Q4. The 32B size in particular hits a quality/cost knee — quality scales with parameters faster than cost up to ~32B, and slower afterwards. Favoured for production chat where 7B isn't sharp enough and where 70B+ would over-spec the hardware budget. Apache 2.0 licence.
- Context
- 128K
- License
- apache-2-0
- VRAM Q4
- 19.2 GB
Coding-specialised Qwen2.5 32B fine-tune. GPT-4o-class on HumanEval and BigCodeBench at the time of release. Trained on additional code-heavy data with extended pre-training. Apache 2.0. Natural pick for self-hosted coding assistants, code-review automation, and any agent loop that primarily writes code.
- Context
- 128K
- License
- apache-2-0
- VRAM Q4
- 19.2 GB
Qwen's reasoning-focused 'thinking' model. Generates long chains-of-thought before answering, similar to OpenAI's o1 and DeepSeek R1 lineage. Optimised for math and competition-style problem solving. The Preview tag means Qwen is iterating quickly; later versions may obsolete this one. Useful today for math-heavy workloads where a slow, careful answer is preferred to a fast wrong one.
- Context
- 33K
- License
- apache-2-0
- VRAM Q4
- 19.2 GB
Bilingual EN/中 34B chat model. Apache 2.0 licensed with strong Chinese-language performance and competitive English chat quality. Good default for bilingual production workloads.
- Context
- 33K
- License
- apache-2-0
- VRAM Q4
- 20.4 GB
Vision-language variant of Yi 34B. Image-text reasoning via an MLP adapter on a CLIP encoder. Useful for bilingual EN/中 multimodal workloads where the major Western vision-language models underperform on Chinese text in images.
- Context
- 4K
- License
- apache-2-0
- VRAM Q4
- 20.4 GB
Cohere's 35B model tuned for RAG and tool use. The open weights are released under CC-BY-NC (commercial use requires the Cohere API). Strong multilingual coverage and a fine-grained RAG-mode output format that makes downstream citation easier.
- Context
- 128K
- License
- mrl
- VRAM Q4
- 21 GB