Model Comparison

DeepSeek-V3 0324 vs Kimi K2 Base

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3 0324 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Kimi K2 Base is better at 0 benchmarks.

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Thu May 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

329.0B diff

Kimi K2 Base has 329.0B more parameters than DeepSeek-V3 0324, making it 49.0% larger.

DeepSeek
DeepSeek-V3 0324
671.0Bparameters
Moonshot AI
Kimi K2 Base
1.0Tparameters
671.0B
DeepSeek-V3 0324
1000.0B
Kimi K2 Base

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Moonshot AI
Kimi K2 Base
Input- tokens
Output- tokens
Thu May 14 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while Kimi K2 Base uses MIT.

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

DeepSeek-V3 0324

MIT + Model License (Commercial use allowed)

Open weights

Kimi K2 Base

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 0324 was released on 2025-03-25, while Kimi K2 Base was released on 2025-07-11.

Kimi K2 Base is 4 months newer than DeepSeek-V3 0324.

DeepSeek-V3 0324

Mar 25, 2025

1.1 years ago

Kimi K2 Base

Jul 11, 2025

10 months ago

3mo 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

DeepSeek
Larger context window (163,840 tokens)
Higher GPQA score (68.4% vs 48.1%)
Higher MMLU-Pro score (81.2% vs 69.2%)
Moonshot AI

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

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3 0324
Moonshot AI
Kimi K2 Base

FAQ

Common questions about DeepSeek-V3 0324 vs Kimi K2 Base.

Which is better, DeepSeek-V3 0324 or Kimi K2 Base?

DeepSeek-V3 0324 significantly outperforms across most benchmarks. DeepSeek-V3 0324 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 0324 compare to Kimi K2 Base in benchmarks?

DeepSeek-V3 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%. 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 0324 and Kimi K2 Base?

DeepSeek-V3 0324 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.

What are the main differences between DeepSeek-V3 0324 and Kimi K2 Base?

Key differences include licensing (MIT + Model License (Commercial use allowed) vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 0324 and Kimi K2 Base?

DeepSeek-V3 0324 is developed by DeepSeek and Kimi K2 Base is developed by Moonshot AI.