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MAI-Code-1-Flash vs Qwen3-235B-A22B-Thinking-2507

MAI-Code-1-Flash and Qwen3-235B-A22B-Thinking-2507 are closely matched at 29.3 and 28.1 on the LLM Stats Score.

Microsoft · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

MAI-Code-1-Flash and Qwen3-235B-A22B-Thinking-2507 are closely matched on the overall LLM Stats Score at 29.3 and 28.1.

In the 3 individual benchmarks reported for both models, MAI-Code-1-Flash wins 2; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose MAI-Code-1-Flash

  • you value its reported benchmark strengths — it wins 2 of 3 exact shared results
  • you want the most recent training data — it shipped Jun 2026

Choose Qwen3-235B-A22B-Thinking-2507

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

MAI-Code-1-Flash
Microsoft
Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
29.3
#122
28.1
#127
Reasoning
29.0
#115
28.5
#118
Agents
10.9
#102
11.3
#100
Cost, coverage & limits
Benchmark wins
2 of 3
1 of 3
Input price
— / M
$0.30 / M
Output price
— / M
$3.00 / M
Context window
—
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
MAI-Code-1-Flash
Qwen3-235B-A22B-Thinking-2507
Math
21.6#139
31.3#65
Tool use
10.6#119
11.3#113
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

15 reported for MAI-Code-1-Flash · 25 for Qwen3-235B-A22B-Thinking-2507

3 shared

MAI-Code-1-Flash outperforms in 2 benchmarks (GPQA, Tau2 Telecom), while Qwen3-235B-A22B-Thinking-2507 is better at 1 benchmark (Humanity's Last Exam).

MAI-Code-1-Flash shows notably better performance in the majority of benchmarks.

Fri Sep 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only Qwen3-235B-A22B-Thinking-2507 specifies input context (262,144 tokens). Only Qwen3-235B-A22B-Thinking-2507 specifies output context (131,072 tokens).

Microsoft
MAI-Code-1-Flash
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input262,144 tokens
Output131,072 tokens
Fri Sep 04 2026 • llm-stats.com

License

Usage and distribution terms

MAI-Code-1-Flash 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.

MAI-Code-1-Flash

Proprietary

Closed source

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

MAI-Code-1-Flash was released on 2026-06-02, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

MAI-Code-1-Flash is 10 months newer than Qwen3-235B-A22B-Thinking-2507.

MAI-Code-1-Flash

Jun 2, 2026

3 months ago

10mo newer
Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

1.1 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against MAI-Code-1-Flash and Qwen3-235B-A22B-Thinking-2507 side-by-side, then vote on the output you prefer.

MAI-Code-1-Flash
✓ Preferred
Qwen3-235B-A22B-Thinking-2507
Open in Playground

FAQ

Common questions about MAI-Code-1-Flash vs Qwen3-235B-A22B-Thinking-2507.

Which is better, MAI-Code-1-Flash or Qwen3-235B-A22B-Thinking-2507?

MAI-Code-1-Flash and Qwen3-235B-A22B-Thinking-2507 are closely matched on the LLM Stats Score at 29.3 and 28.1. MAI-Code-1-Flash is made by Microsoft and Qwen3-235B-A22B-Thinking-2507 is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does MAI-Code-1-Flash compare to Qwen3-235B-A22B-Thinking-2507 in benchmarks?

MAI-Code-1-Flash scores AIME 2026: 92.5%, GPQA: 84.6%, IFBench: 75.0%, Tau2 Telecom: 71.7%, SWE-Bench Verified: 71.6%. Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%.

What are the context window sizes for MAI-Code-1-Flash and Qwen3-235B-A22B-Thinking-2507?

MAI-Code-1-Flash supports an unknown number of tokens and Qwen3-235B-A22B-Thinking-2507 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between MAI-Code-1-Flash and Qwen3-235B-A22B-Thinking-2507?

Key differences include LLM Stats Score (29.3 vs 28.1), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes MAI-Code-1-Flash and Qwen3-235B-A22B-Thinking-2507?

MAI-Code-1-Flash is developed by Microsoft and Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.

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