Model Comparison

Kimi K2-Thinking-0905 vs Qwen3-Coder

Comparing Kimi K2-Thinking-0905 and Qwen3-Coder across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Kimi K2-Thinking-0905 and Qwen3-Coder don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3-Coder costs less

For input processing, Kimi K2-Thinking-0905 ($0.47/1M tokens) is 2.6x more expensive than Qwen3-Coder ($0.18/1M tokens).

For output processing, Kimi K2-Thinking-0905 ($2.00/1M tokens) is 11.1x more expensive than Qwen3-Coder ($0.18/1M tokens).

In conclusion, Kimi K2-Thinking-0905 is more expensive than Qwen3-Coder.*

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

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Moonshot AI
Kimi K2-Thinking-0905
Input tokens$0.47
Output tokens$2.00
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen3-Coder
Input tokens$0.18
Output tokens$0.18
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

520.0B diff

Kimi K2-Thinking-0905 has 520.0B more parameters than Qwen3-Coder, making it 108.3% larger.

Moonshot AI
Kimi K2-Thinking-0905
1000.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-Coder
480.0Bparameters
1000.0B
Kimi K2-Thinking-0905
480.0B
Qwen3-Coder

Context Window

Maximum input and output token capacity

Kimi K2-Thinking-0905 accepts 262,144 input tokens compared to Qwen3-Coder's 256,000 tokens. Kimi K2-Thinking-0905 can generate longer responses up to 262,144 tokens, while Qwen3-Coder is limited to 256,000 tokens.

Moonshot AI
Kimi K2-Thinking-0905
Input262,144 tokens
Output262,144 tokens
Alibaba Cloud / Qwen Team
Qwen3-Coder
Input256,000 tokens
Output256,000 tokens
Wed Apr 15 2026 • llm-stats.com

License

Usage and distribution terms

Kimi K2-Thinking-0905 is licensed under MIT, while Qwen3-Coder uses Apache 2.0.

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

Kimi K2-Thinking-0905

MIT

Open weights

Qwen3-Coder

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2-Thinking-0905 was released on 2025-09-05, while Qwen3-Coder was released on 2025-01-01.

Kimi K2-Thinking-0905 is 8 months newer than Qwen3-Coder.

Kimi K2-Thinking-0905

Sep 5, 2025

7 months ago

8mo newer
Qwen3-Coder

Jan 1, 2025

1.3 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-Thinking-0905 is available from DeepInfra, Novita, Fireworks. Qwen3-Coder is available from DeepInfra, Fireworks.

Kimi K2-Thinking-0905

deepinfra logo
Deepinfra
Input Price:Input: $0.47/1MOutput Price:Output: $2.00/1M
novita logo
Novita
Input Price:Input: $0.48/1MOutput Price:Output: $2.00/1M
fireworks logo
Fireworks
Input Price:Input: $0.60/1MOutput Price:Output: $2.50/1M

Qwen3-Coder

deepinfra logo
Deepinfra
Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M
fireworks logo
Fireworks
Input Price:Input: $0.25/1MOutput Price:Output: $0.25/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Moonshot AI
Larger context window (262,144 tokens)
Alibaba Cloud / Qwen Team

Qwen3-Coder

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Moonshot AI
Kimi K2-Thinking-0905
Alibaba Cloud / Qwen Team
Qwen3-Coder

FAQ

Common questions about Kimi K2-Thinking-0905 vs Qwen3-Coder

Kimi K2-Thinking-0905 (Moonshot AI) and Qwen3-Coder (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Kimi K2-Thinking-0905 scores AIME 2025: 100.0%, HMMT 2025: 97.5%, MMLU-Redux: 94.4%, FRAMES: 87.0%, MMLU-Pro: 84.6%.
Qwen3-Coder is 2.6x cheaper for input tokens. Kimi K2-Thinking-0905 costs $0.47/M input and $2.00/M output via deepinfra. Qwen3-Coder costs $0.18/M input and $0.18/M output via deepinfra.
Kimi K2-Thinking-0905 supports 262K tokens and Qwen3-Coder supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (262K vs 256K), input pricing ($0.47 vs $0.18/M), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Kimi K2-Thinking-0905 is developed by Moonshot AI and Qwen3-Coder is developed by Alibaba Cloud / Qwen Team.