Model Comparison

DeepSeek-V3 vs Kimi K2-Thinking-0905

Kimi K2-Thinking-0905 significantly outperforms across most benchmarks. DeepSeek-V3 is 1.8x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

DeepSeek-V3 outperforms in 0 benchmarks, while Kimi K2-Thinking-0905 is better at 5 benchmarks (FRAMES, GPQA, MMLU-Pro, MMLU-Redux, SWE-Bench Verified).

Kimi K2-Thinking-0905 significantly outperforms across most benchmarks.

Thu Apr 09 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 1.7x cheaper than Kimi K2-Thinking-0905 ($0.47/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 1.8x cheaper than Kimi K2-Thinking-0905 ($2.00/1M tokens).

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

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

Lowest available price from all providers
Thu Apr 09 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Moonshot AI
Kimi K2-Thinking-0905
Input tokens$0.47
Output tokens$2.00
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

329.0B diff

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

DeepSeek
DeepSeek-V3
671.0Bparameters
Moonshot AI
Kimi K2-Thinking-0905
1000.0Bparameters
671.0B
DeepSeek-V3
1000.0B
Kimi K2-Thinking-0905

Context Window

Maximum input and output token capacity

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

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Moonshot AI
Kimi K2-Thinking-0905
Input262,144 tokens
Output262,144 tokens
Thu Apr 09 2026 • llm-stats.com

License

Usage and distribution terms

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

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-Thinking-0905

MIT

Open weights

Release Timeline

When each model was launched

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

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

DeepSeek-V3

Dec 25, 2024

1.3 years ago

Kimi K2-Thinking-0905

Sep 5, 2025

7 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-Thinking-0905 is available from DeepInfra, Novita, Fireworks.

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Kimi K2-Thinking-0905

deepinfra logo
Deepinfra
Input Price:Input: $0.47/1MOutput Price:Output: $2.00/1M
novita logo
Novita
Input Price:Input: $0.48/1MOutput Price:Output: $2.00/1M
fireworks logo
Fireworks
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
Less expensive input tokens
Less expensive output tokens
Moonshot AI
Larger context window (262,144 tokens)
Higher FRAMES score (87.0% vs 73.3%)
Higher GPQA score (84.5% vs 59.1%)
Higher MMLU-Pro score (84.6% vs 75.9%)
Higher MMLU-Redux score (94.4% vs 89.1%)
Higher SWE-Bench Verified score (71.3% vs 42.0%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Moonshot AI
Kimi K2-Thinking-0905

FAQ

Common questions about DeepSeek-V3 vs Kimi K2-Thinking-0905

Kimi K2-Thinking-0905 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Kimi K2-Thinking-0905 is made by Moonshot AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Kimi K2-Thinking-0905 scores AIME 2025: 100.0%, HMMT 2025: 97.5%, MMLU-Redux: 94.4%, FRAMES: 87.0%, MMLU-Pro: 84.6%.
DeepSeek-V3 is 1.7x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Kimi K2-Thinking-0905 costs $0.47/M input and $2.00/M output via deepinfra.
DeepSeek-V3 supports 131K tokens and Kimi K2-Thinking-0905 supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 262K), input pricing ($0.27 vs $0.47/M), licensing (MIT + Model License (Commercial use allowed) vs MIT). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Kimi K2-Thinking-0905 is developed by Moonshot AI.