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MiMo-V2.6-Flash vs Qwen3-235B-A22B-Thinking-2507

MiMo-V2.6-Flash leads the LLM Stats Score 45.7 to 28.1.

Xiaomi · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

MiMo-V2.6-Flash leads the overall LLM Stats Score 45.7 to 28.1, ranking #29 overall.

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

Choose MiMo-V2.6-Flash

  • overall performance matters — it scores 45.7 and ranks #29 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

Choose Qwen3-235B-A22B-Thinking-2507

  • you want predictable pricing at $0.30/M input and $3.00/M output

At a glance

The differences that matter most.

MiMo-V2.6-Flash
Xiaomi
Qwen3-235B-A22B-Thinking-2507
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
45.7
#29
28.1
#138
Reasoning
43.2
#42
28.4
#130
Agents
33.3
#25
11.4
#111
Cost, coverage & limits
Benchmark wins
—
—
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

1 shared
Index
MiMo-V2.6-Flash
Qwen3-235B-A22B-Thinking-2507
Tool use
28.1#22
10.8#121
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for MiMo-V2.6-Flash · 25 for Qwen3-235B-A22B-Thinking-2507

No common benchmarks found

MiMo-V2.6-Flash and Qwen3-235B-A22B-Thinking-2507don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

74.0B diff

MiMo-V2.6-Flash has 74.0B more parameters than Qwen3-235B-A22B-Thinking-2507, making it 31.5% larger.

Xiaomi
MiMo-V2.6-Flash
309.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
235.0Bparameters
309.0B
MiMo-V2.6-Flash
235.0B
Qwen3-235B-A22B-Thinking-2507

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).

Xiaomi
MiMo-V2.6-Flash
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3-235B-A22B-Thinking-2507
Input262,144 tokens
Output131,072 tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

MiMo-V2.6-Flash supports multimodal inputs, whereas Qwen3-235B-A22B-Thinking-2507 does not.

MiMo-V2.6-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

MiMo-V2.6-Flash

Text
Images
Audio
Video

Qwen3-235B-A22B-Thinking-2507

Text
Images
Audio
Video

License

Usage and distribution terms

MiMo-V2.6-Flash is licensed under MIT, 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.

MiMo-V2.6-Flash

MIT

Open weights

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

MiMo-V2.6-Flash was released on 2026-09-22, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

MiMo-V2.6-Flash is 14 months newer than Qwen3-235B-A22B-Thinking-2507.

MiMo-V2.6-Flash

Sep 22, 2026

-1 days ago

1.2yr newer
Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

1.2 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 MiMo-V2.6-Flash and Qwen3-235B-A22B-Thinking-2507 side-by-side, then vote on the output you prefer.

MiMo-V2.6-Flash
✓ Preferred
Qwen3-235B-A22B-Thinking-2507
Open in Playground

FAQ

Common questions about MiMo-V2.6-Flash vs Qwen3-235B-A22B-Thinking-2507.

Which is better, MiMo-V2.6-Flash or Qwen3-235B-A22B-Thinking-2507?

MiMo-V2.6-Flash leads the LLM Stats Score 45.7 to 28.1. MiMo-V2.6-Flash is made by Xiaomi 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 MiMo-V2.6-Flash compare to Qwen3-235B-A22B-Thinking-2507 in benchmarks?

MiMo-V2.6-Flash scores CyberGym: 95.1%, Terminal-Bench 2.1: 87.6%, OSWorld-Verified: 80.8%, MiMo Cyber Bench: 77.2%, Toolathlon-Verified: 73.6%. 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 MiMo-V2.6-Flash and Qwen3-235B-A22B-Thinking-2507?

MiMo-V2.6-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 MiMo-V2.6-Flash and Qwen3-235B-A22B-Thinking-2507?

Key differences include LLM Stats Score (45.7 vs 28.1), multimodal support (yes vs no), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes MiMo-V2.6-Flash and Qwen3-235B-A22B-Thinking-2507?

MiMo-V2.6-Flash is developed by Xiaomi and Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.

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