LLM Reference

Qwen3-32B

Released
2025-04-29
Last refreshed
2026-06-29
Status
Researched 31d ago
Open sourceCommercial use: permittedCodingClassificationJSON / Tool use

Qwen3-32B is worth evaluating for coding, classification, and json / tool use when its provider route and context window match the workload.

Use it for

  • Teams evaluating coding, classification, and json / tool use
  • Workloads that can use a 40k context window
  • Buyers comparing 4 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
Specifications
Family
Qwen3
Released
2025-04-29
Context
40k
Parameters
32B
Architecture
Decoder Only
Specialization
general
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Training
Pretrained
Created by

AI research institute of Alibaba Group.

Hangzhou, Zhejiang, China
Founded 2017
Website
Pricing
Output / 1M
$0.240
Input / 1M
$0.080

Cheapest of 6 routes · OpenRouter

About

Qwen3-32B is Alibaba's Qwen3 model. It offers a 40K-token context window.

Qwen3-32B is Alibaba's 32-billion-parameter dense language model in the Qwen3 family. Unlike the MoE siblings in the series, Qwen3-32B activates all 32 billion parameters for each inference pass, giving teams a simpler serving profile with predictable memory use and no expert-routing overhead. This LLMReference seed row carries a 40K-token model context, matching the page description and several hosted provider entries, even though some native or gateway endpoints may expose larger windows.

The model keeps the Qwen3 hybrid thinking/non-thinking behavior: it can spend extra tokens on deliberate reasoning for hard math, code, and planning prompts, or answer directly for routine chat and extraction tasks. Alibaba describes the Qwen3 generation as trained on 36 trillion tokens with broad multilingual coverage across 119 languages and dialects. For buyers, the main distinction is dense 32B quality with Qwen3 reasoning controls, positioned between the cheaper 30B-A3B MoE route and much larger Qwen3 variants.

Hosted availability in the seed includes Fireworks AI, Groq, AWS Bedrock, OpenRouter, Novita AI, and the Vercel AI Gateway. Because provider context limits differ, use this page's 40K figure as the model-row summary and verify the selected provider row before committing to long-context workloads.

Qwen3-32B has a 40k-token context window.

Qwen3-32B input tokens at $0.08/1M, output at $0.24/1M.

Top use-case fit: coding, agents, and build tasks

Coding

Q/$ B

1 relevant benchmark in the decision map.

Classification

Included by capability and metadata signals in the decision map.

JSON / Tool use

Included by capability and metadata signals in the decision map.

Capabilities

Structured Outputs

Benchmark peer barsfor Coding

Benchmark scores(2)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionSource
Aider Polyglot40.02026-04https://aider.chat/docs/leaderboards
Google-Proof Q&A66.8diamondhttps://pricepertoken.com/leaderboards/benchmark/gpqa

Migration checks

No linked migration route is available for this model yet.

Frequently asked questions

What is the context window of Qwen3-32B?

Qwen3-32B has a context window of 40k tokens.

How much does Qwen3-32B cost?

Qwen3-32B pricing ranges from $0.08/1M to $0.9/1M input tokens depending on the provider.

When was Qwen3-32B released?

Qwen3-32B was released on 2025-04-29.

Which providers offer Qwen3-32B?

Qwen3-32B is available from 6 providers: Fireworks AI, GroqCloud, AWS Bedrock, OpenRouter, Vercel AI Gateway, Novita AI.

What benchmarks has Qwen3-32B been tested on?

Qwen3-32B has been evaluated on 2 benchmarks, including Aider Polyglot, Google-Proof Q&A.