Model Comparison

Kimi K2.5 vs QwQ-32B

Kimi K2.5 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Kimi K2.5 outperforms in 1 benchmarks (GPQA), while QwQ-32B is better at 0 benchmarks.

Kimi K2.5 significantly outperforms across most benchmarks.

Tue Apr 14 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
Tue Apr 14 2026 • llm-stats.com
Moonshot AI
Kimi K2.5
Input tokens$0.60
Output tokens$2.50
Best providerFireworks
Alibaba Cloud / Qwen Team
QwQ-32B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

967.5B diff

Kimi K2.5 has 967.5B more parameters than QwQ-32B, making it 2976.9% larger.

Moonshot AI
Kimi K2.5
1000.0Bparameters
Alibaba Cloud / Qwen Team
QwQ-32B
32.5Bparameters
1000.0B
Kimi K2.5
32.5B
QwQ-32B

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
QwQ-32B
Input- tokens
Output- tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Kimi K2.5 supports multimodal inputs, whereas QwQ-32B does not.

Kimi K2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.

Kimi K2.5

Text
Images
Audio
Video

QwQ-32B

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2.5 is licensed under MIT, while QwQ-32B 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

QwQ-32B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2.5 was released on 2026-01-27, while QwQ-32B was released on 2025-03-05.

Kimi K2.5 is 11 months newer than QwQ-32B.

Kimi K2.5

Jan 27, 2026

2 months ago

10mo newer
QwQ-32B

Mar 5, 2025

1.1 years ago

Knowledge Cutoff

When training data ends

QwQ-32B has a documented knowledge cutoff of 2024-11-28, while Kimi K2.5's cutoff date is not specified.

We can confirm QwQ-32B's training data extends to 2024-11-28, but cannot make a direct comparison without Kimi K2.5's cutoff date.

Kimi K2.5

—

QwQ-32B

Nov 2024

Outputs Comparison

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Key Takeaways

Moonshot AI
Larger context window (262,100 tokens)
Supports multimodal inputs
Higher GPQA score (87.6% vs 65.2%)
Alibaba Cloud / Qwen Team

QwQ-32B

View details

Alibaba Cloud / Qwen Team

Detailed Comparison

AI Model Comparison Table
Feature
Moonshot AI
Kimi K2.5
Alibaba Cloud / Qwen Team
QwQ-32B

FAQ

Common questions about Kimi K2.5 vs QwQ-32B

Kimi K2.5 significantly outperforms across most benchmarks. Kimi K2.5 is made by Moonshot AI and QwQ-32B 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%. QwQ-32B scores MATH-500: 90.6%, IFEval: 83.9%, AIME 2024: 79.5%, LiveBench: 73.1%, BFCL: 66.4%.
Kimi K2.5 supports 262K tokens and QwQ-32B 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 multimodal support (yes vs no), 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 QwQ-32B is developed by Alibaba Cloud / Qwen Team.