Model Comparison

Qwen3 32B vs GPT-OSS 20B

Compare the listed model data for Qwen3 32B by Qwen and GPT-OSS 20B by Microsoft / OpenAI. Benchmark and pricing records are not a controlled test and may change.

Data last updated: 2026-10-16. Verify current model details with each provider.

What the listed data says

Qwen3 32B: 128K tokens; GPT-OSS 20B: 128K tokens. The listed context-window values are equal. Qwen3 32B is listed for coding, reasoning, agentic workflows, long-context tasks; GPT-OSS 20B is listed for no specific capability flags. Shared catalog benchmark entries: MMLU: Qwen3 32B 92.0%; GPT-OSS 20B 78.3%; HumanEval: Qwen3 32B 92.7%; GPT-OSS 20B 76.1%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.

Catalog source links

Use these model and provider links to verify current specifications, pricing, and availability.

Computed differences from catalog data

  • The listed context windows are 128K tokens and 128K tokens; the larger is 1× the smaller.
  • On shared numeric benchmark entries, MMLU: Qwen3 32B − GPT-OSS 20B = +13.7 percentage points (92.0% vs 78.3%); HumanEval: Qwen3 32B − GPT-OSS 20B = +16.6 percentage points (92.7% vs 76.1%).
  • The first listed parameter quantities are 32B and 20B; the larger quantity is 1.6× the smaller. Total and active MoE parameters are not directly equivalent.
  • A release-date gap cannot be calculated from the catalog values (Qwen3 32B: April 2025; GPT-OSS 20B: 2025).

Cost example: 1M input and 1M output tokens

A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.

Choose Qwen3 32B if…

Choose Qwen3 32B when your task aligns with catalog-listed uses or strengths such as Production coding assistants for enterprise software teams, Mathematical reasoning and data science, Complex document analysis and long-form reporting, Multilingual enterprise applications.

Choose GPT-OSS 20B if…

Choose GPT-OSS 20B when your task aligns with catalog-listed uses or strengths such as Applications needing OpenAI research quality open-weight, Research with MIT-licensed OpenAI model, OpenAI's first truly open-source model, MIT license — free commercial use.

Qwen3 32B

Browse Qwen models

32B dense Qwen3 — excels at complex coding, mathematics, and deep multi-step reasoning. Top performer in its size class.

Parameters: 32B

Context: 128K tokens

Catalog pricing: Open source — free. Third-party API ~$0.14-0.30/MTok

Qwen Coding · Reasoning · Agentic · Long Context Open Source

View Qwen3 32B model profile

GPT-OSS 20B

Browse Microsoft / OpenAI models

Microsoft/OpenAI's open-source GPT model — 20B params optimized for chat, Q&A, and coding tasks.

Parameters: 20B

Context: 128K tokens

Catalog pricing: MIT — free

Microsoft / OpenAI General Purpose Open Source

View GPT-OSS 20B model profile

Feature Comparison — Qwen3 32B vs GPT-OSS 20B

Catalog specifications for Qwen3 32B and GPT-OSS 20B
Specification Qwen3 32B GPT-OSS 20B
Provider Qwen Microsoft / OpenAI
Parameters 32B 20B
Context window 128K tokens 128K tokens
Maximum output Not listed Not listed
Catalog pricing Open source — free. Third-party API ~$0.14-0.30/MTok MIT — free
Listed input/output cost per 1M tokens input $0.3, output $0.7 per 1M tokens Separate numeric input/output rates not listed
License Apache 2.0 MIT
Coding support Listed Not listed
Reasoning support Listed Not listed
Vision input Not listed Not listed
Multimodal Not listed Not listed
Open weights Yes Yes
Benchmark: MMLU 92.0% 78.3%
Benchmark: HumanEval 92.7% 76.1%

Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.

Frequently Asked Questions

What is different between Qwen3 32B and GPT-OSS 20B?
Qwen3 32B: 128K tokens; GPT-OSS 20B: 128K tokens. The listed context-window values are equal. Qwen3 32B is listed for coding, reasoning, agentic workflows, long-context tasks; GPT-OSS 20B is listed for no specific capability flags. Shared catalog benchmark entries: MMLU: Qwen3 32B 92.0%; GPT-OSS 20B 78.3%; HumanEval: Qwen3 32B 92.7%; GPT-OSS 20B 76.1%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for Qwen3 32B and GPT-OSS 20B?
MMLU: Qwen3 32B 92.0%; GPT-OSS 20B 78.3%; HumanEval: Qwen3 32B 92.7%; GPT-OSS 20B 76.1%. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
Which model has the larger listed context window?
Qwen3 32B: 128K tokens; GPT-OSS 20B: 128K tokens. The listed context-window values are equal.
What are the listed costs per million tokens for Qwen3 32B and GPT-OSS 20B?
Qwen3 32B: input $0.3, output $0.7 per 1M tokens (Open source — free. Third-party API ~$0.14-0.30/MTok). GPT-OSS 20B: Separate numeric input/output rates not listed (MIT — free). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for Qwen3 32B and GPT-OSS 20B?
The catalog lists Qwen3 32B as April 2025 and GPT-OSS 20B as 2025; a release-date gap cannot be calculated from both records.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between Qwen3 32B and GPT-OSS 20B?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.

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