o4-mini vs Qwen3-235B-A22B-Thinking-2507
o4-mini and Qwen3-235B-A22B-Thinking-2507 are closely matched at 27.5 and 28.1 on the LLM Stats Score. Qwen3-235B-A22B-Thinking-2507 is 2.0x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
o4-mini and Qwen3-235B-A22B-Thinking-2507 are closely matched on the overall LLM Stats Score at 27.5 and 28.1.
In the 5 individual benchmarks reported for both models, o4-mini wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3-235B-A22B-Thinking-2507 is roughly 2.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3-235B-A22B-Thinking-2507 also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose o4-mini
- you value its reported benchmark strengths — it wins 4 of 5 exact shared results
Choose Qwen3-235B-A22B-Thinking-2507
- cost matters — it's about 2.0x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Jul 2025
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
14 reported for o4-mini · 25 for Qwen3-235B-A22B-Thinking-2507
o4-mini outperforms in 4 benchmarks (AIME 2025, GPQA, TAU-bench Airline, TAU-bench Retail), while Qwen3-235B-A22B-Thinking-2507 is better at 1 benchmark (Humanity's Last Exam).
o4-mini significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, o4-mini ($1.10/1M tokens) is 3.7x more expensive than Qwen3-235B-A22B-Thinking-2507 ($0.30/1M tokens).
For output processing, o4-mini ($4.40/1M tokens) is 1.5x more expensive than Qwen3-235B-A22B-Thinking-2507 ($3.00/1M tokens).
In conclusion, o4-mini is more expensive than Qwen3-235B-A22B-Thinking-2507.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3-235B-A22B-Thinking-2507 accepts 262,144 input tokens compared to o4-mini's 200,000 tokens. Qwen3-235B-A22B-Thinking-2507 can generate longer responses up to 131,072 tokens, while o4-mini is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
o4-mini supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.
o4-mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
o4-mini
Qwen3-235B-A22B-Thinking-2507
License
Usage and distribution terms
o4-mini is licensed under a proprietary license, while Qwen3-235B-A22B-Thinking-2507 uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
o4-mini was released on 2025-04-16, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.
Qwen3-235B-A22B-Thinking-2507 is 3 months newer than o4-mini.
Apr 16, 2025
1.4 years ago
Jul 25, 2025
1.1 years ago
3mo newerKnowledge Cutoff
When training data ends
o4-mini has a documented knowledge cutoff of 2024-05-31, while Qwen3-235B-A22B-Thinking-2507's cutoff date is not specified.
We can confirm o4-mini's training data extends to 2024-05-31, but cannot make a direct comparison without Qwen3-235B-A22B-Thinking-2507's cutoff date.
May 2024
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Provider Availability
o4-mini is available from OpenAI. Qwen3-235B-A22B-Thinking-2507 is available from Fireworks, Novita.
o4-mini
Qwen3-235B-A22B-Thinking-2507
Outputs Comparison
Judge for yourself.
Run your own prompts against o4-mini and Qwen3-235B-A22B-Thinking-2507 side-by-side, then vote on the output you prefer.
FAQ
Common questions about o4-mini vs Qwen3-235B-A22B-Thinking-2507.