Model Comparison
GPT OSS 120B vs Qwen3 VL 235B A22B ThinkingWhich is better in 2026?
Both models are evenly matched across the benchmarks. GPT OSS 120B is 6.7x cheaper per token.
Verdict: GPT OSS 120B vs Qwen3 VL 235B A22B Thinking — which is better?
GPT OSS 120B (by OpenAI) and Qwen3 VL 235B A22B Thinking (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
GPT OSS 120B outperforms in 1 benchmarks (Humanity's Last Exam), while Qwen3 VL 235B A22B Thinking is better at 1 benchmark (MMLU). Both models are evenly matched across the benchmarks.
On price, GPT OSS 120B is roughly 6.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 235B A22B Thinking also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT OSS 120B if…
- cost matters — it's about 6.7x cheaper per token
Choose Qwen3 VL 235B A22B Thinking if…
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
GPT OSS 120B outperforms in 1 benchmarks (Humanity's Last Exam), while Qwen3 VL 235B A22B Thinking is better at 1 benchmark (MMLU).
Both models are evenly matched across the benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GPT OSS 120B ($0.09/1M tokens) is 5.0x cheaper than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).
For output processing, GPT OSS 120B ($0.45/1M tokens) is 7.8x cheaper than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).
In conclusion, Qwen3 VL 235B A22B Thinking is more expensive than GPT OSS 120B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 VL 235B A22B Thinking has 119.2B more parameters than GPT OSS 120B, making it 102.1% larger.
Context Window
Maximum input and output token capacity
Qwen3 VL 235B A22B Thinking accepts 262,144 input tokens compared to GPT OSS 120B's 131,072 tokens. Qwen3 VL 235B A22B Thinking can generate longer responses up to 262,144 tokens, while GPT OSS 120B is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas GPT OSS 120B does not.
Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT OSS 120B
Qwen3 VL 235B A22B Thinking
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT OSS 120B was released on 2025-08-05, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.
Qwen3 VL 235B A22B Thinking is 2 months newer than GPT OSS 120B.
Aug 5, 2025
11 months ago
Sep 22, 2025
9 months ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT OSS 120B is available from DeepInfra, Novita, OpenAI, Fireworks, Groq. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.
GPT OSS 120B
Qwen3 VL 235B A22B Thinking
Outputs Comparison
Key Takeaways
GPT OSS 120B
View detailsOpenAI
Qwen3 VL 235B A22B Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GPT OSS 120B and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GPT OSS 120B vs Qwen3 VL 235B A22B Thinking.