Model Comparison

Kimi K2.5 vs Qwen2.5-Coder 32B Instruct

Kimi K2.5 significantly outperforms across most benchmarks. Qwen2.5-Coder 32B Instruct is 11.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Kimi K2.5 outperforms in 1 benchmarks (MMLU-Pro), while Qwen2.5-Coder 32B Instruct is better at 0 benchmarks.

Kimi K2.5 significantly outperforms across most benchmarks.

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen2.5-Coder 32B Instruct costs less

For input processing, Kimi K2.5 ($0.60/1M tokens) is 6.7x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).

For output processing, Kimi K2.5 ($2.50/1M tokens) is 27.8x more expensive than Qwen2.5-Coder 32B Instruct ($0.09/1M tokens).

In conclusion, Kimi K2.5 is more expensive than Qwen2.5-Coder 32B Instruct.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
Moonshot AI
Kimi K2.5
Input tokens$0.60
Output tokens$2.50
Best providerFireworks
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
Input tokens$0.09
Output tokens$0.09
Best providerLambda
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Model Size

Parameter count comparison

968.0B diff

Kimi K2.5 has 968.0B more parameters than Qwen2.5-Coder 32B Instruct, making it 3025.0% larger.

Moonshot AI
Kimi K2.5
1000.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
32.0Bparameters
1000.0B
Kimi K2.5
32.0B
Qwen2.5-Coder 32B Instruct

Context Window

Maximum input and output token capacity

Kimi K2.5 accepts 262,100 input tokens compared to Qwen2.5-Coder 32B Instruct's 128,000 tokens. Kimi K2.5 can generate longer responses up to 262,100 tokens, while Qwen2.5-Coder 32B Instruct is limited to 128,000 tokens.

Moonshot AI
Kimi K2.5
Input262,100 tokens
Output262,100 tokens
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
Input128,000 tokens
Output128,000 tokens
Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Kimi K2.5 supports multimodal inputs, whereas Qwen2.5-Coder 32B Instruct 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

Qwen2.5-Coder 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Kimi K2.5 is licensed under MIT, while Qwen2.5-Coder 32B Instruct 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

Qwen2.5-Coder 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2.5 was released on 2026-01-27, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.

Kimi K2.5 is 17 months newer than Qwen2.5-Coder 32B Instruct.

Kimi K2.5

Jan 27, 2026

2 months ago

1.4yr newer
Qwen2.5-Coder 32B Instruct

Sep 19, 2024

1.6 years ago

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

Provider Availability

Kimi K2.5 is available from Fireworks. Qwen2.5-Coder 32B Instruct is available from Lambda, DeepInfra, Hyperbolic, Fireworks.

Kimi K2.5

fireworks logo
Fireworks
Input Price:Input: $0.60/1MOutput Price:Output: $2.50/1M

Qwen2.5-Coder 32B Instruct

lambda logo
Lambda
Input Price:Input: $0.09/1MOutput Price:Output: $0.09/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Moonshot AI
Larger context window (262,100 tokens)
Supports multimodal inputs
Higher MMLU-Pro score (87.1% vs 50.4%)
Alibaba Cloud / Qwen Team
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Moonshot AI
Kimi K2.5
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct

FAQ

Common questions about Kimi K2.5 vs Qwen2.5-Coder 32B Instruct

Kimi K2.5 significantly outperforms across most benchmarks. Kimi K2.5 is made by Moonshot AI and Qwen2.5-Coder 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.
Kimi K2.5 scores AIME 2025: 96.1%, HMMT 2025: 95.4%, InfoVQAtest: 92.6%, OCRBench: 92.3%, MathVista-Mini: 90.1%. Qwen2.5-Coder 32B Instruct scores HumanEval: 92.7%, GSM8k: 91.1%, MBPP: 90.2%, HellaSwag: 83.0%, Winogrande: 80.8%.
Qwen2.5-Coder 32B Instruct is 6.7x cheaper for input tokens. Kimi K2.5 costs $0.60/M input and $2.50/M output via fireworks. Qwen2.5-Coder 32B Instruct costs $0.09/M input and $0.09/M output via lambda.
Kimi K2.5 supports 262K tokens and Qwen2.5-Coder 32B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (262K vs 128K), input pricing ($0.60 vs $0.09/M), 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 Qwen2.5-Coder 32B Instruct is developed by Alibaba Cloud / Qwen Team.