Model Comparison
Kimi K2 0905 vs Qwen3 VL 235B A22B ThinkingWhich is better in 2026?
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks. Kimi K2 0905 is 1.1x cheaper per token.
Verdict: Kimi K2 0905 vs Qwen3 VL 235B A22B Thinking — which is better?
Kimi K2 0905 (by Moonshot AI) and Qwen3 VL 235B A22B Thinking (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 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (MMLU, MMLU-Pro). Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
On price, Kimi K2 0905 is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose Kimi K2 0905 if…
- cost matters — it's about 1.1x cheaper per token
Choose Qwen3 VL 235B A22B Thinking if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Kimi K2 0905 outperforms in 0 benchmarks, while Qwen3 VL 235B A22B Thinking is better at 2 benchmarks (MMLU, MMLU-Pro).
Qwen3 VL 235B A22B Thinking significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Kimi K2 0905 ($0.60/1M tokens) is 1.3x more expensive than Qwen3 VL 235B A22B Thinking ($0.45/1M tokens).
For output processing, Kimi K2 0905 ($2.50/1M tokens) is 1.4x cheaper than Qwen3 VL 235B A22B Thinking ($3.49/1M tokens).
In conclusion, Qwen3 VL 235B A22B Thinking is more expensive than Kimi K2 0905.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2 0905 has 764.0B more parameters than Qwen3 VL 235B A22B Thinking, making it 323.7% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 262,144 tokens. Both models can generate responses up to 262,144 tokens.
Input Capabilities
Supported data types and modalities
Qwen3 VL 235B A22B Thinking supports multimodal inputs, whereas Kimi K2 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 0905
Qwen3 VL 235B A22B Thinking
License
Usage and distribution terms
Kimi K2 0905 is licensed under a proprietary license, 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.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Kimi K2 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 0905.
Sep 5, 2025
10 months ago
Sep 22, 2025
10 months ago
2w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Kimi K2 0905 is available from Novita. Qwen3 VL 235B A22B Thinking is available from DeepInfra, Novita.
Kimi K2 0905
Qwen3 VL 235B A22B Thinking
Outputs Comparison
Key Takeaways
Kimi K2 0905
View detailsMoonshot AI
Qwen3 VL 235B A22B Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Kimi K2 0905 and Qwen3 VL 235B A22B Thinking side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Kimi K2 0905 vs Qwen3 VL 235B A22B Thinking.