Model Comparison

Kimi K2.5 vs Qwen3.5-9B

Kimi K2.5 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

Kimi K2.5 outperforms in 6 benchmarks (AA-LCR, GPQA, HMMT 2025, LiveCodeBench v6, LongBench v2, MMLU-Pro), while Qwen3.5-9B is better at 0 benchmarks.

Kimi K2.5 significantly outperforms across most benchmarks.

Fri Apr 10 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Fri Apr 10 2026 • llm-stats.com
Moonshot AI
Kimi K2.5
Input tokens$0.60
Output tokens$2.50
Best providerFireworks
Alibaba Cloud / Qwen Team
Qwen3.5-9B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

991.0B diff

Kimi K2.5 has 991.0B more parameters than Qwen3.5-9B, making it 11011.1% larger.

Moonshot AI
Kimi K2.5
1000.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.5-9B
9.0Bparameters
1000.0B
Kimi K2.5
9.0B
Qwen3.5-9B

Context Window

Maximum input and output token capacity

Only Kimi K2.5 specifies input context (262,100 tokens). Only Kimi K2.5 specifies output context (262,100 tokens).

Moonshot AI
Kimi K2.5
Input262,100 tokens
Output262,100 tokens
Alibaba Cloud / Qwen Team
Qwen3.5-9B
Input- tokens
Output- tokens
Fri Apr 10 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Kimi K2.5 and Qwen3.5-9B support multimodal inputs.

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

Kimi K2.5

Text
Images
Audio
Video

Qwen3.5-9B

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2.5 is licensed under MIT, while Qwen3.5-9B uses Apache 2.0.

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

Kimi K2.5

MIT

Open weights

Qwen3.5-9B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2.5 was released on 2026-01-27, while Qwen3.5-9B was released on 2026-03-02.

Qwen3.5-9B is 1 month newer than Kimi K2.5.

Kimi K2.5

Jan 27, 2026

2 months ago

Qwen3.5-9B

Mar 2, 2026

1 months ago

1mo 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

Moonshot AI
Larger context window (262,100 tokens)
Higher AA-LCR score (70.0% vs 63.0%)
Higher GPQA score (87.6% vs 81.7%)
Higher HMMT 2025 score (95.4% vs 83.2%)
Higher LiveCodeBench v6 score (85.0% vs 65.6%)
Higher LongBench v2 score (61.0% vs 55.2%)
Higher MMLU-Pro score (87.1% vs 82.5%)
Alibaba Cloud / Qwen Team

Qwen3.5-9B

View details

Alibaba Cloud / Qwen Team

Detailed Comparison

AI Model Comparison Table
Feature
Moonshot AI
Kimi K2.5
Alibaba Cloud / Qwen Team
Qwen3.5-9B

FAQ

Common questions about Kimi K2.5 vs Qwen3.5-9B

Kimi K2.5 significantly outperforms across most benchmarks. Kimi K2.5 is made by Moonshot AI and Qwen3.5-9B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Kimi K2.5 scores AIME 2025: 96.1%, HMMT 2025: 95.4%, InfoVQAtest: 92.6%, OCRBench: 92.3%, MathVista-Mini: 90.1%. Qwen3.5-9B scores IFEval: 91.5%, MMLU-Redux: 91.1%, C-Eval: 88.2%, MAXIFE: 83.4%, Global PIQA: 83.2%.
Kimi K2.5 supports 262K tokens and Qwen3.5-9B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Kimi K2.5 is developed by Moonshot AI and Qwen3.5-9B is developed by Alibaba Cloud / Qwen Team.