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

MiMo-V2.6-Flash leads the LLM Stats Score 45.7 to 26.7.

Xiaomi · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

MiMo-V2.6-Flash leads the overall LLM Stats Score 45.7 to 26.7, 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 VL 235B A22B Thinking

  • you want predictable pricing at $0.45/M input and $3.49/M output

At a glance

The differences that matter most.

MiMo-V2.6-Flash
Xiaomi
Qwen3 VL 235B A22B Thinking
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
45.7
#29
26.7
#151
Reasoning
43.2
#42
26.9
#144
Agents
33.3
#25
13.1
#97
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.45 / M
Output price
— / M
$3.49 / M
Context window
—
262,144

Individual benchmarks

16 reported for MiMo-V2.6-Flash · 67 for Qwen3 VL 235B A22B Thinking

No common benchmarks found

MiMo-V2.6-Flash and Qwen3 VL 235B A22B Thinkingdon'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

73.0B diff

MiMo-V2.6-Flash has 73.0B more parameters than Qwen3 VL 235B A22B Thinking, making it 30.9% larger.

Xiaomi
MiMo-V2.6-Flash
309.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
236.0Bparameters
309.0B
MiMo-V2.6-Flash
236.0B
Qwen3 VL 235B A22B Thinking

Context Window

Maximum input and output token capacity

Only Qwen3 VL 235B A22B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 235B A22B Thinking specifies output context (262,144 tokens).

Xiaomi
MiMo-V2.6-Flash
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 235B A22B Thinking
Input262,144 tokens
Output262,144 tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both MiMo-V2.6-Flash and Qwen3 VL 235B A22B Thinking support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

MiMo-V2.6-Flash

Text
Images
Audio
Video

Qwen3 VL 235B A22B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

MiMo-V2.6-Flash is licensed under MIT, while Qwen3 VL 235B A22B Thinking 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 VL 235B A22B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

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

MiMo-V2.6-Flash is 12 months newer than Qwen3 VL 235B A22B Thinking.

MiMo-V2.6-Flash

Sep 22, 2026

-1 days ago

1.0yr newer
Qwen3 VL 235B A22B Thinking

Sep 22, 2025

12 months 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 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.

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

FAQ

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

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

MiMo-V2.6-Flash leads the LLM Stats Score 45.7 to 26.7. MiMo-V2.6-Flash is made by Xiaomi and Qwen3 VL 235B A22B Thinking 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 VL 235B A22B Thinking 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 VL 235B A22B Thinking scores ZebraLogic: 97.3%, DocVQAtest: 96.5%, ScreenSpot: 95.4%, CountBench: 93.7%, MMLU-Redux: 93.7%.

What are the context window sizes for MiMo-V2.6-Flash and Qwen3 VL 235B A22B Thinking?

MiMo-V2.6-Flash supports an unknown number of tokens and Qwen3 VL 235B A22B Thinking 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 VL 235B A22B Thinking?

Key differences include LLM Stats Score (45.7 vs 26.7), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

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

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

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