Model Comparison

DeepSeek-V3 vs Kimi K2 0905

Kimi K2 0905 significantly outperforms across most benchmarks. DeepSeek-V3 is 2.3x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V3 outperforms in 0 benchmarks, while Kimi K2 0905 is better at 4 benchmarks (AIME 2024, GPQA, MMLU, MMLU-Pro).

Kimi K2 0905 significantly outperforms across most benchmarks.

Wed May 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3 costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 2.2x cheaper than Kimi K2 0905 ($0.60/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 2.3x cheaper than Kimi K2 0905 ($2.50/1M tokens).

In conclusion, Kimi K2 0905 is more expensive than DeepSeek-V3.*

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

Lowest available price from all providers

Wed May 13 2026 • llm-stats.com

DeepSeek-V3

Input tokens$0.27

Output tokens$1.10

Best providerDeepSeek

Kimi K2 0905

Input tokens$0.60

Output tokens$2.50

Best providerNovita

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Model Size

Parameter count comparison

329.0B diff

Kimi K2 0905 has 329.0B more parameters than DeepSeek-V3, making it 49.0% larger.

DeepSeek-V3

671.0Bparameters

Kimi K2 0905

1.0Tparameters

671.0B

DeepSeek-V3

1000.0B

Kimi K2 0905

Context Window

Maximum input and output token capacity

Kimi K2 0905 accepts 262,144 input tokens compared to DeepSeek-V3's 131,072 tokens. Kimi K2 0905 can generate longer responses up to 262,144 tokens, while DeepSeek-V3 is limited to 131,072 tokens.

DeepSeek-V3

Input131,072 tokens

Output131,072 tokens

Kimi K2 0905

Input262,144 tokens

Output262,144 tokens

Wed May 13 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Kimi K2 0905 uses a proprietary license.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Kimi K2 0905

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Kimi K2 0905 was released on 2025-09-05.

Kimi K2 0905 is 8 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.4 years ago

Kimi K2 0905

Sep 5, 2025

8 months ago

8mo 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

Provider Availability

DeepSeek-V3 is available from DeepSeek. Kimi K2 0905 is available from Novita.

DeepSeek-V3

DeepSeek

Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Kimi K2 0905

Novita

Input Price:Input: $0.60/1MOutput Price:Output: $2.50/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek-V3

View details

DeepSeek

Less expensive input tokens

Less expensive output tokens

Has open weights

Kimi K2 0905

View details

Moonshot AI

Larger context window (262,144 tokens)

Higher AIME 2024 score (72.0% vs 39.2%)

Higher GPQA score (75.8% vs 59.1%)

Higher MMLU score (90.2% vs 88.5%)

Higher MMLU-Pro score (82.5% vs 75.9%)

Detailed Comparison

AI Model Comparison Table
Feature	DeepSeek-V3	Kimi K2 0905

FAQ

Common questions about DeepSeek-V3 vs Kimi K2 0905.

Which is better, DeepSeek-V3 or Kimi K2 0905?

Kimi K2 0905 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Kimi K2 0905 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 compare to Kimi K2 0905 in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Kimi K2 0905 scores HumanEval: 94.5%, MMLU: 90.2%, MATH: 89.1%, MMLU-Pro: 82.5%, GPQA: 75.8%.

Is DeepSeek-V3 cheaper than Kimi K2 0905?

DeepSeek-V3 is 2.2x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Kimi K2 0905 costs $0.60/M input and $2.50/M output via novita.

What are the context window sizes for DeepSeek-V3 and Kimi K2 0905?

DeepSeek-V3 supports 131K tokens and Kimi K2 0905 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 DeepSeek-V3 and Kimi K2 0905?

Key differences include context window (131K vs 262K), input pricing ($0.27 vs $0.60/M), licensing (MIT + Model License (Commercial use allowed) vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3 and Kimi K2 0905?

DeepSeek-V3 is developed by DeepSeek and Kimi K2 0905 is developed by Moonshot AI.