Model Comparison

Kimi K2 0905 vs Qwen3 VL 32B InstructWhich is better in 2026?

Kimi K2 0905 significantly outperforms across most benchmarks.

Verdict: Kimi K2 0905 vs Qwen3 VL 32B Instruct — which is better?

Kimi K2 0905 (by Moonshot AI) and Qwen3 VL 32B Instruct (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Kimi K2 0905 outperforms in 3 benchmarks (GPQA, MMLU, MMLU-Pro), while Qwen3 VL 32B Instruct is better at 0 benchmarks. Kimi K2 0905 significantly outperforms across most benchmarks.

Choose Kimi K2 0905 if…

  • you want the strongest raw capability — it leads on 3 of 3 shared benchmarks

Choose Qwen3 VL 32B Instruct if…

  • you want the most recent training data — it shipped Sep 2025
  • you need open weights you can self-host or fine-tune
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Kimi K2 0905 outperforms in 3 benchmarks (GPQA, MMLU, MMLU-Pro), while Qwen3 VL 32B Instruct is better at 0 benchmarks.

Kimi K2 0905 significantly outperforms across most benchmarks.

Thu Jun 25 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

967.0B diff

Kimi K2 0905 has 967.0B more parameters than Qwen3 VL 32B Instruct, making it 2930.3% larger.

Moonshot AI
Kimi K2 0905
1.0Tparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct
33.0Bparameters
1000.0B
Kimi K2 0905
33.0B
Qwen3 VL 32B Instruct

Context Window

Maximum input and output token capacity

Only Kimi K2 0905 specifies input context (262,144 tokens). Only Kimi K2 0905 specifies output context (262,144 tokens).

Moonshot AI
Kimi K2 0905
Input262,144 tokens
Output262,144 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct
Input- tokens
Output- tokens
Thu Jun 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 32B Instruct supports multimodal inputs, whereas Kimi K2 0905 does not.

Qwen3 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Kimi K2 0905

Text
Images
Audio
Video

Qwen3 VL 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2 0905 is licensed under a proprietary license, while Qwen3 VL 32B Instruct uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Kimi K2 0905

Proprietary

Closed source

Qwen3 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2 0905 was released on 2025-09-05, while Qwen3 VL 32B Instruct was released on 2025-09-22.

Qwen3 VL 32B Instruct is 1 month newer than Kimi K2 0905.

Kimi K2 0905

Sep 5, 2025

9 months ago

Qwen3 VL 32B Instruct

Sep 22, 2025

9 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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Moonshot AI
Larger context window (262,144 tokens)
Higher GPQA score (75.8% vs 68.9%)
Higher MMLU score (90.2% vs 86.4%)
Higher MMLU-Pro score (82.5% vs 78.6%)
Alibaba Cloud / Qwen Team

Qwen3 VL 32B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Moonshot AI
Kimi K2 0905
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct

FAQ

Common questions about Kimi K2 0905 vs Qwen3 VL 32B Instruct.

Which is better, Kimi K2 0905 or Qwen3 VL 32B Instruct?

Kimi K2 0905 significantly outperforms across most benchmarks. Kimi K2 0905 is made by Moonshot AI and Qwen3 VL 32B Instruct 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 0905 compare to Qwen3 VL 32B Instruct in benchmarks?

Kimi K2 0905 scores HumanEval: 94.5%, MMLU: 90.2%, MATH: 89.1%, MMLU-Pro: 82.5%, GPQA: 75.8%. Qwen3 VL 32B Instruct scores DocVQAtest: 96.9%, ScreenSpot: 95.8%, CharXiv-D: 90.5%, MMLU-Redux: 89.8%, AI2D: 89.5%.

What are the context window sizes for Kimi K2 0905 and Qwen3 VL 32B Instruct?

Kimi K2 0905 supports 262K tokens and Qwen3 VL 32B Instruct supports an unknown number of 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 0905 and Qwen3 VL 32B Instruct?

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

Who makes Kimi K2 0905 and Qwen3 VL 32B Instruct?

Kimi K2 0905 is developed by Moonshot AI and Qwen3 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.

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