Model Comparison

DeepSeek-V3.2-Exp vs Kimi K2 Base

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3.2-Exp outperforms in 3 benchmarks (GPQA, MMLU-Pro, SimpleQA), while Kimi K2 Base is better at 0 benchmarks.

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.

Fri May 15 2026 • llm-stats.com

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-Exp, making it 46.0% larger.

DeepSeek
DeepSeek-V3.2-Exp
685.0Bparameters
Moonshot AI
Kimi K2 Base
1.0Tparameters
685.0B
DeepSeek-V3.2-Exp
1000.0B
Kimi K2 Base

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2-Exp specifies input context (163,840 tokens). Only DeepSeek-V3.2-Exp specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2-Exp
Input163,840 tokens
Output65,536 tokens
Moonshot AI
Kimi K2 Base
Input- tokens
Output- tokens
Fri May 15 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-Exp

MIT

Open weights

Kimi K2 Base

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Exp was released on 2025-09-29, while Kimi K2 Base was released on 2025-07-11.

DeepSeek-V3.2-Exp is 3 months newer than Kimi K2 Base.

DeepSeek-V3.2-Exp

Sep 29, 2025

7 months ago

2mo 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 (163,840 tokens)
Higher GPQA score (79.9% vs 48.1%)
Higher MMLU-Pro score (85.0% vs 69.2%)
Higher SimpleQA score (97.1% vs 35.3%)
Moonshot AI

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Exp
Moonshot AI
Kimi K2 Base

FAQ

Common questions about DeepSeek-V3.2-Exp vs Kimi K2 Base.

Which is better, DeepSeek-V3.2-Exp or Kimi K2 Base?

DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. DeepSeek-V3.2-Exp is made by DeepSeek and Kimi K2 Base is made by Moonshot AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3.2-Exp compare to Kimi K2 Base in benchmarks?

DeepSeek-V3.2-Exp scores SimpleQA: 97.1%, AIME 2025: 89.3%, MMLU-Pro: 85.0%, HMMT 2025: 83.6%, GPQA: 79.9%. 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-Exp and Kimi K2 Base?

DeepSeek-V3.2-Exp supports 164K 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-Exp and Kimi K2 Base?

DeepSeek-V3.2-Exp is developed by DeepSeek and Kimi K2 Base is developed by Moonshot AI.