Head-to-head · frontier vs frontier

o3 Reasoning vs Qwen3-Max Max: which model should you choose?

We compared o3 Reasoning and Qwen3-Max Max on price, context window and 12 benchmarks. Qwen3-Max Max has the stronger average benchmark score; o3 Reasoning is cheaper on a blended 3:1 basis.

OpenAI

o3 Reasoning

o3 Reasoning is a frontier model from OpenAI. It offers a 200,000-token context window, costs $18.07 per million input tokens and $70.65 per million output tokens, and averages 85.3 across the index's benchmark suite.

Input
$18.07 / 1M
Output
$70.65 / 1M
Context
200,000
Avg score
85.3
Open weights
No
Full o3 Reasoning page
Alibaba Cloud

Qwen3-Max Max

Qwen3-Max Max is a frontier model from Alibaba Cloud. It offers a 400,000-token context window, costs $18.53 per million input tokens and $74.05 per million output tokens, and averages 85.9 across the index's benchmark suite.

Input
$18.53 / 1M
Output
$74.05 / 1M
Context
400,000
Avg score
85.9
Open weights
No
Full Qwen3-Max Max page

Specification comparison

Speco3 ReasoningQwen3-Max MaxEdge
Input price / 1M$18.07$18.53A
Output price / 1M$70.65$74.05A
Context window200,000400,000B
Max output16,38465,536B
Average score85.385.9B
Arena Elo1456.91467.7B
Open weightsNoNoTie

Benchmark comparison

o3 Reasoning wins 3, Qwen3-Max Max wins 9, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.

Benchmarko3 ReasoningQwen3-Max MaxGapWinner
MMLU-Pro87.785.22.5o3 Reasoning
GPQA Diamond79.683.84.2Qwen3-Max Max
SWE-bench Verified74.174.30.2Qwen3-Max Max
HumanEval91.390.21.1o3 Reasoning
MATH-50092.092.80.8Qwen3-Max Max
AIME 202580.582.72.2Qwen3-Max Max
LiveCodeBench82.782.80.1Qwen3-Max Max
IFEval90.693.73.1Qwen3-Max Max
TruthfulQA86.589.32.8Qwen3-Max Max
HellaSwag90.991.40.5Qwen3-Max Max
MMMU82.378.93.4o3 Reasoning
Arena Elo1456.91467.710.8Qwen3-Max Max

Price analysis

On a blended 3:1 input-to-output basis, o3 Reasoning costs about $31.22 per million tokens and Qwen3-Max Max costs about $32.41. o3 Reasoning is roughly 4% cheaper than Qwen3-Max Max. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.

Qwen3-Max Max has the larger context window at 400,000 tokens, compared with 200,000 for o3 Reasoning. That matters for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, o3 Reasoning wins 3, Qwen3-Max Max wins 9, and 0 are tied. On the index average, Qwen3-Max Max leads o3 Reasoning by 0.6 points (85.9 versus 85.3).

The price picture favours o3 Reasoning. The context picture favours Qwen3-Max Max. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.

If you need a single default, start with Qwen3-Max Max for quality-sensitive work and o3 Reasoning for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

Choose o3 Reasoning if

  • Unit cost matters and you want the cheaper blended price.

Choose Qwen3-Max Max if

  • You want the higher average benchmark score in this index.
  • You need the larger 400,000-token context window.
  • You need the larger 65,536-token output limit.

FAQ

Is o3 Reasoning better than Qwen3-Max Max?

On the index average, Qwen3-Max Max leads o3 Reasoning by 0.6 points (85.9 versus 85.3). The better choice depends on price, context and your task. o3 Reasoning wins 3 benchmarks, Qwen3-Max Max wins 9.

Which is cheaper, o3 Reasoning or Qwen3-Max Max?

o3 Reasoning is cheaper on a blended 3:1 basis at about $31.22 per million tokens, versus $32.41 for Qwen3-Max Max.

Which has the larger context window?

Qwen3-Max Max has the larger context window at 400,000 tokens. o3 Reasoning has 200,000 tokens.

Are these models open weights?

o3 Reasoning is proprietary; Qwen3-Max Max is proprietary.

Which should I choose for production?

If you need a single default, start with Qwen3-Max Max for quality-sensitive work and o3 Reasoning for high-volume, well-scoped tasks. Run both on a sample of your own traffic before locking in a choice.

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