Model Comparison

Kimi K2 Base vs Qwen3-235B-A22B-Thinking-2507

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

Kimi K2 Base outperforms in 0 benchmarks, while Qwen3-235B-A22B-Thinking-2507 is better at 4 benchmarks (GPQA, LiveCodeBench v6, MMLU-Pro, SuperGPQA).

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks.

Wed May 20 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

765.0B diff

Kimi K2 Base has 765.0B more parameters than Qwen3-235B-A22B-Thinking-2507, making it 325.5% larger.

Kimi K2 Base

1.0Tparameters

Qwen3-235B-A22B-Thinking-2507

235.0Bparameters

1000.0B

Kimi K2 Base

235.0B

Qwen3-235B-A22B-Thinking-2507

Context Window

Maximum input and output token capacity

Only Qwen3-235B-A22B-Thinking-2507 specifies input context (262,144 tokens). Only Qwen3-235B-A22B-Thinking-2507 specifies output context (131,072 tokens).

Kimi K2 Base

Input- tokens

Output- tokens

Qwen3-235B-A22B-Thinking-2507

Input262,144 tokens

Output131,072 tokens

Wed May 20 2026 • llm-stats.com

License

Usage and distribution terms

Kimi K2 Base is licensed under MIT, while Qwen3-235B-A22B-Thinking-2507 uses Apache 2.0.

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

Kimi K2 Base

MIT

Open weights

Qwen3-235B-A22B-Thinking-2507

Apache 2.0

Open weights

Release Timeline

When each model was launched

Kimi K2 Base was released on 2025-07-11, while Qwen3-235B-A22B-Thinking-2507 was released on 2025-07-25.

Qwen3-235B-A22B-Thinking-2507 is 0 month newer than Kimi K2 Base.

Kimi K2 Base

Jul 11, 2025

10 months ago

Qwen3-235B-A22B-Thinking-2507

Jul 25, 2025

9 months ago

2w 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

Kimi K2 Base

View details

Moonshot AI

No standout differentiators in the data we have for this pair.

Qwen3-235B-A22B-Thinking-2507

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Higher GPQA score (81.1% vs 48.1%)

Higher LiveCodeBench v6 score (74.1% vs 26.3%)

Higher MMLU-Pro score (84.4% vs 69.2%)

Higher SuperGPQA score (64.9% vs 44.7%)

Detailed Comparison

AI Model Comparison Table
Feature	Kimi K2 Base	Qwen3-235B-A22B-Thinking-2507

FAQ

Common questions about Kimi K2 Base vs Qwen3-235B-A22B-Thinking-2507.

Which is better, Kimi K2 Base or Qwen3-235B-A22B-Thinking-2507?

Qwen3-235B-A22B-Thinking-2507 significantly outperforms across most benchmarks. Kimi K2 Base is made by Moonshot AI and Qwen3-235B-A22B-Thinking-2507 is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Kimi K2 Base compare to Qwen3-235B-A22B-Thinking-2507 in benchmarks?

Kimi K2 Base scores C-Eval: 92.5%, GSM8k: 92.1%, MMLU-redux-2.0: 90.2%, MMLU: 87.8%, TriviaQA: 85.1%. Qwen3-235B-A22B-Thinking-2507 scores MMLU-Redux: 93.8%, AIME 2025: 92.3%, WritingBench: 88.3%, IFEval: 87.8%, Creative Writing v3: 86.1%.

What are the context window sizes for Kimi K2 Base and Qwen3-235B-A22B-Thinking-2507?

Kimi K2 Base supports an unknown number of tokens and Qwen3-235B-A22B-Thinking-2507 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Kimi K2 Base and Qwen3-235B-A22B-Thinking-2507?

Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Kimi K2 Base and Qwen3-235B-A22B-Thinking-2507?

Kimi K2 Base is developed by Moonshot AI and Qwen3-235B-A22B-Thinking-2507 is developed by Alibaba Cloud / Qwen Team.