Model Comparison

Kimi K2-Instruct-0905 vs Qwen3 VL 235B A22B Thinking

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

Kimi K2-Instruct-0905 outperforms in 1 benchmarks (IFEval), while Qwen3 VL 235B A22B Thinking is better at 8 benchmarks (AIME 2025, Humanity's Last Exam, MMLU, MMLU-Pro, MMLU-Redux, SimpleQA, SuperGPQA, ZebraLogic).

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.

Thu May 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

764.0B diff

Kimi K2-Instruct-0905 has 764.0B more parameters than Qwen3 VL 235B A22B Thinking, making it 323.7% larger.

Kimi K2-Instruct-0905

1.0Tparameters

Qwen3 VL 235B A22B Thinking

236.0Bparameters

1000.0B

Kimi K2-Instruct-0905

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).

Kimi K2-Instruct-0905

Input- tokens

Output- tokens

Qwen3 VL 235B A22B Thinking

Input262,144 tokens

Output262,144 tokens

Thu May 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas Kimi K2-Instruct-0905 does not.

Qwen3 VL 235B A22B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

Kimi K2-Instruct-0905

Text

Images

Audio

Video

Qwen3 VL 235B A22B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

Kimi K2-Instruct-0905 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.

Kimi K2-Instruct-0905

MIT

Open weights

Qwen3 VL 235B A22B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2-Instruct-0905 was released on 2025-09-05, while Qwen3 VL 235B A22B Thinking was released on 2025-09-22.

Qwen3 VL 235B A22B Thinking is 1 month newer than Kimi K2-Instruct-0905.

Kimi K2-Instruct-0905

Sep 5, 2025

8 months ago

Qwen3 VL 235B A22B Thinking

Sep 22, 2025

7 months ago

2w newer

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

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Key Takeaways

Kimi K2-Instruct-0905

View details

Moonshot AI

Higher IFEval score (89.8% vs 88.2%)

Qwen3 VL 235B A22B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Supports multimodal inputs

Higher AIME 2025 score (89.7% vs 49.5%)

Higher Humanity's Last Exam score (13.6% vs 4.7%)

Higher MMLU score (90.6% vs 89.5%)

Higher MMLU-Pro score (83.8% vs 81.1%)

Higher MMLU-Redux score (93.7% vs 92.7%)

Higher SimpleQA score (44.4% vs 31.0%)

Higher SuperGPQA score (64.3% vs 57.2%)

Higher ZebraLogic score (97.3% vs 89.0%)

Detailed Comparison

AI Model Comparison Table
Feature	Kimi K2-Instruct-0905	Qwen3 VL 235B A22B Thinking

FAQ

Common questions about Kimi K2-Instruct-0905 vs Qwen3 VL 235B A22B Thinking.

Which is better, Kimi K2-Instruct-0905 or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Kimi K2-Instruct-0905 is made by Moonshot AI and Qwen3 VL 235B A22B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Kimi K2-Instruct-0905 compare to Qwen3 VL 235B A22B Thinking in benchmarks?

Kimi K2-Instruct-0905 scores MATH-500: 97.4%, MMLU-Redux: 92.7%, IFEval: 89.8%, AutoLogi: 89.5%, MMLU: 89.5%. 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 Kimi K2-Instruct-0905 and Qwen3 VL 235B A22B Thinking?

Kimi K2-Instruct-0905 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 Kimi K2-Instruct-0905 and Qwen3 VL 235B A22B Thinking?

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

Who makes Kimi K2-Instruct-0905 and Qwen3 VL 235B A22B Thinking?

Kimi K2-Instruct-0905 is developed by Moonshot AI and Qwen3 VL 235B A22B Thinking is developed by Alibaba Cloud / Qwen Team.