QwenReleased on Apr 29, 2025

Qwen3 32B: Benchmarks, Pricing & Context Window

Qwen3 32B is a language model from Qwen, released in April 2025.

Qwen3-32B is a large language model from Alibaba's Qwen3 series. It features 32.8 billion parameters, a 128k token context window, support for 119 languages, and hybrid thinking modes allowing switching between deep reasoning and fast

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Qwen3 32B pricing

Providers

Qwen3 32B starts at $0.100 per million input tokens and $0.300 per million output tokens via DeepInfra. See all 3 providers below with their per-token pricing, latency, throughput, and modality support.

ProviderInput $/MOutput $/MMax InputMax OutputLatency sThroughputQuantInputOutput
DeepInfra logoDeepInfra
$0.100$0.300128.0K128.0K
0.84
57 c/s
Novita logoNovita
$0.100$0.440128.0K128.0K
0.93
32 c/s
Sambanova logoSambanova
$0.400$0.800128.0K128.0K
1.08
328 c/s
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Qwen3 32B API

API access coming soon

Qwen3 32B will be available through our gateway shortly.

Qwen3 32B examples

Recent arena outputs from Qwen3 32B, picked from the highest-ranked matchups.

Qwen3 32B license

Qwen3 32B is released under the Apache 2.0 license, which permits commercial use, has 32.8B parameters.

License
Apache 2.0
Commercial use allowed
Parameters
32.8B

Apache License 2.0 - allows commercial use

FAQ

Common questions about Qwen3 32B.

When was Qwen3 32B released?

Qwen3 32B was released on April 29, 2025 by Qwen. This is the official Qwen3 32B release date tracked on LLM Stats.

How many parameters does Qwen3 32B have?

Qwen3 32B has 32.8 billion parameters. It ships as an open-weight model, so you can download and run it on your own hardware.

Who created Qwen3 32B?

Qwen3 32B was created by Qwen.

What is the license for Qwen3 32B?

Qwen3 32B is released under the Apache 2.0 license. This is an open-source / open-weight license that permits self-hosting.

Where can I use Qwen3 32B?

Qwen3 32B is available through 3 providers including DeepInfra, Novita, Sambanova.

Where is the Qwen3 32B paper or technical report?

Qwen3 32B has a paper or technical report available at https://qwenlm.github.io/blog/qwen3/. Use that source for architecture, training, release and evaluation details.