Model Comparison

GPT OSS 120B vs Qwen3 VL 32B Thinking

GPT OSS 120B significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GPT OSS 120B outperforms in 2 benchmarks (GPQA, MMLU), while Qwen3 VL 32B Thinking is better at 0 benchmarks.

GPT OSS 120B significantly outperforms across most benchmarks.

Wed May 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

83.8B diff

GPT OSS 120B has 83.8B more parameters than Qwen3 VL 32B Thinking, making it 253.9% larger.

GPT OSS 120B

116.8Bparameters

Qwen3 VL 32B Thinking

33.0Bparameters

116.8B

GPT OSS 120B

33.0B

Qwen3 VL 32B Thinking

Context Window

Maximum input and output token capacity

Only GPT OSS 120B specifies input context (131,072 tokens). Only GPT OSS 120B specifies output context (131,072 tokens).

GPT OSS 120B

Input131,072 tokens

Output131,072 tokens

Qwen3 VL 32B Thinking

Input- tokens

Output- tokens

Wed May 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 32B Thinking supports multimodal inputs, whereas GPT OSS 120B does not.

Qwen3 VL 32B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT OSS 120B

Text

Images

Audio

Video

Qwen3 VL 32B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

GPT OSS 120B

Apache 2.0

Open weights

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT OSS 120B was released on 2025-08-05, while Qwen3 VL 32B Thinking was released on 2025-09-22.

Qwen3 VL 32B Thinking is 2 months newer than GPT OSS 120B.

GPT OSS 120B

Aug 5, 2025

9 months ago

Qwen3 VL 32B Thinking

Sep 22, 2025

7 months ago

1mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

GPT OSS 120B

View details

OpenAI

Larger context window (131,072 tokens)

Higher GPQA score (80.1% vs 73.1%)

Higher MMLU score (90.0% vs 88.7%)

Qwen3 VL 32B Thinking

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature	GPT OSS 120B	Qwen3 VL 32B Thinking

FAQ

Common questions about GPT OSS 120B vs Qwen3 VL 32B Thinking.

Which is better, GPT OSS 120B or Qwen3 VL 32B Thinking?

GPT OSS 120B significantly outperforms across most benchmarks. GPT OSS 120B is made by OpenAI and Qwen3 VL 32B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does GPT OSS 120B compare to Qwen3 VL 32B Thinking in benchmarks?

GPT OSS 120B scores MMLU: 90.0%, CodeForces: 82.1%, GPQA: 80.1%, TAU-bench Retail: 67.8%, HealthBench: 57.6%. Qwen3 VL 32B Thinking scores DocVQAtest: 96.1%, ScreenSpot: 95.7%, MMLU-Redux: 91.9%, MMBench-V1.1: 90.8%, CharXiv-D: 90.2%.

What are the context window sizes for GPT OSS 120B and Qwen3 VL 32B Thinking?

GPT OSS 120B supports 131K tokens and Qwen3 VL 32B Thinking supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT OSS 120B and Qwen3 VL 32B Thinking?

Key differences include multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT OSS 120B and Qwen3 VL 32B Thinking?

GPT OSS 120B is developed by OpenAI and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.