o3 vs Qwen3.5-35B-A3B
o3 and Qwen3.5-35B-A3B are closely matched at 31.0 and 30.8 on the LLM Stats Score. Qwen3.5-35B-A3B is 9.9x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
o3 and Qwen3.5-35B-A3B are closely matched on the overall LLM Stats Score at 31.0 and 30.8.
The models split the 10 individual benchmarks reported for both models evenly.
On price, Qwen3.5-35B-A3B is roughly 9.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3.5-35B-A3B 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 o3
- you want predictable pricing at $2.00/M input and $8.00/M output
Choose Qwen3.5-35B-A3B
- cost matters — it's about 9.9x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Feb 2026
- 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
22 reported for o3 · 81 for Qwen3.5-35B-A3B
o3 outperforms in 5 benchmarks (CharXiv-R, MMMU, MMMU-Pro, Multi-Challenge, VideoMMMU), while Qwen3.5-35B-A3B is better at 5 benchmarks (BrowseComp, ERQA, GPQA, Humanity's Last Exam, SWE-Bench Verified).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, o3 ($2.00/1M tokens) is 14.3x more expensive than Qwen3.5-35B-A3B ($0.14/1M tokens).
For output processing, o3 ($8.00/1M tokens) is 8.0x more expensive than Qwen3.5-35B-A3B ($1.00/1M tokens).
In conclusion, o3 is more expensive than Qwen3.5-35B-A3B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3.5-35B-A3B accepts 262,144 input tokens compared to o3's 200,000 tokens. Qwen3.5-35B-A3B can generate longer responses up to 262,144 tokens, while o3 is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
Both o3 and Qwen3.5-35B-A3B support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
o3
Qwen3.5-35B-A3B
License
Usage and distribution terms
o3 is licensed under a proprietary license, while Qwen3.5-35B-A3B 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
o3 was released on 2025-04-16, while Qwen3.5-35B-A3B was released on 2026-02-24.
Qwen3.5-35B-A3B is 10 months newer than o3.
Apr 16, 2025
1.5 years ago
Feb 24, 2026
7 months ago
10mo newerKnowledge Cutoff
When training data ends
o3 has a documented knowledge cutoff of 2024-05-31, while Qwen3.5-35B-A3B's cutoff date is not specified.
We can confirm o3's training data extends to 2024-05-31, but cannot make a direct comparison without Qwen3.5-35B-A3B's cutoff date.
May 2024
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Provider Availability
o3 is available from OpenAI. Qwen3.5-35B-A3B is available from DeepInfra, Novita.
o3
Qwen3.5-35B-A3B
Outputs Comparison
Judge for yourself.
Run your own prompts against o3 and Qwen3.5-35B-A3B side-by-side, then vote on the output you prefer.
FAQ
Common questions about o3 vs Qwen3.5-35B-A3B.