Model Comparison

DeepSeek-V3.2 (Non-thinking) vs Kimi K2 Base

Comparing DeepSeek-V3.2 (Non-thinking) and Kimi K2 Base across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2 (Non-thinking) and Kimi K2 Base don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

315.0B diff

Kimi K2 Base has 315.0B more parameters than DeepSeek-V3.2 (Non-thinking), making it 46.0% larger.

DeepSeek
DeepSeek-V3.2 (Non-thinking)
685.0Bparameters
Moonshot AI
Kimi K2 Base
1.0Tparameters
685.0B
DeepSeek-V3.2 (Non-thinking)
1000.0B
Kimi K2 Base

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2 (Non-thinking) specifies input context (131,072 tokens). Only DeepSeek-V3.2 (Non-thinking) specifies output context (8,192 tokens).

DeepSeek
DeepSeek-V3.2 (Non-thinking)
Input131,072 tokens
Output8,192 tokens
Moonshot AI
Kimi K2 Base
Input- tokens
Output- tokens
Sat May 23 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V3.2 (Non-thinking)

MIT

Open weights

Kimi K2 Base

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Non-thinking) was released on 2025-12-01, while Kimi K2 Base was released on 2025-07-11.

DeepSeek-V3.2 (Non-thinking) is 5 months newer than Kimi K2 Base.

DeepSeek-V3.2 (Non-thinking)

Dec 1, 2025

5 months ago

4mo newer
Kimi K2 Base

Jul 11, 2025

10 months 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

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Moonshot AI

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Non-thinking)
Moonshot AI
Kimi K2 Base

FAQ

Common questions about DeepSeek-V3.2 (Non-thinking) vs Kimi K2 Base.

Which is better, DeepSeek-V3.2 (Non-thinking) or Kimi K2 Base?

DeepSeek-V3.2 (Non-thinking) (DeepSeek) and Kimi K2 Base (Moonshot AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V3.2 (Non-thinking) compare to Kimi K2 Base 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%.

What are the context window sizes for DeepSeek-V3.2 (Non-thinking) and Kimi K2 Base?

DeepSeek-V3.2 (Non-thinking) supports 131K tokens and Kimi K2 Base supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Who makes DeepSeek-V3.2 (Non-thinking) and Kimi K2 Base?

DeepSeek-V3.2 (Non-thinking) is developed by DeepSeek and Kimi K2 Base is developed by Moonshot AI.