o1-mini vs Qwen3 Max
Qwen3 Max leads the LLM Stats Score 21.7 to 10.0. Qwen3 Max is 3.2x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 Max leads the overall LLM Stats Score 21.7 to 10.0, ranking #183 overall.
In the 1 individual benchmarks reported for both models, Qwen3 Max wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 Max is roughly 3.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 Max also accepts a larger context window (256,000 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 o1-mini
- you want predictable pricing at $3.00/M input and $12.00/M output
Choose Qwen3 Max
- overall performance matters — it scores 21.7 and ranks #183 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 3.2x cheaper per token
- you process long inputs — it offers a 256,000 token context window
- you want the most recent training data — it shipped Dec 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
6 reported for o1-mini · 6 for Qwen3 Max
o1-mini outperforms in 0 benchmarks, while Qwen3 Max is better at 1 benchmark (GPQA).
Qwen3 Max 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, o1-mini ($3.00/1M tokens) is 6.0x more expensive than Qwen3 Max ($0.50/1M tokens).
For output processing, o1-mini ($12.00/1M tokens) is 2.4x more expensive than Qwen3 Max ($5.00/1M tokens).
In conclusion, o1-mini is more expensive than Qwen3 Max.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Qwen3 Max accepts 256,000 input tokens compared to o1-mini's 128,000 tokens. Qwen3 Max can generate longer responses up to 131,072 tokens, while o1-mini is limited to 65,536 tokens.
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
o1-mini was released on 2024-09-12, while Qwen3 Max was released on 2025-12-15.
Qwen3 Max is 15 months newer than o1-mini.
Sep 12, 2024
2.0 years ago
Dec 15, 2025
9 months ago
1.3yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
o1-mini is available from OpenAI, Azure. Qwen3 Max is available from Novita, DeepInfra.
o1-mini
Qwen3 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against o1-mini and Qwen3 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about o1-mini vs Qwen3 Max.