Model Comparison

DeepSeek-R1 vs Kimi K2 0905

Comparing DeepSeek-R1 and Kimi K2 0905 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-R1 and Kimi K2 0905 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-R1 costs less

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 1.1x cheaper than Kimi K2 0905 ($0.60/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 1.1x cheaper than Kimi K2 0905 ($2.50/1M tokens).

In conclusion, Kimi K2 0905 is more expensive than DeepSeek-R1.*

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

Lowest available price from all providers
Thu Jun 04 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
Moonshot AI
Kimi K2 0905
Input tokens$0.60
Output tokens$2.50
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

329.0B diff

Kimi K2 0905 has 329.0B more parameters than DeepSeek-R1, making it 49.0% larger.

DeepSeek
DeepSeek-R1
671.0Bparameters
Moonshot AI
Kimi K2 0905
1.0Tparameters
671.0B
DeepSeek-R1
1000.0B
Kimi K2 0905

Context Window

Maximum input and output token capacity

Kimi K2 0905 accepts 262,144 input tokens compared to DeepSeek-R1's 131,072 tokens. Kimi K2 0905 can generate longer responses up to 262,144 tokens, while DeepSeek-R1 is limited to 131,072 tokens.

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Moonshot AI
Kimi K2 0905
Input262,144 tokens
Output262,144 tokens
Thu Jun 04 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-R1 is licensed under MIT, 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-R1

MIT

Open weights

Kimi K2 0905

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Kimi K2 0905 was released on 2025-09-05.

Kimi K2 0905 is 8 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.4 years ago

Kimi K2 0905

Sep 5, 2025

9 months ago

7mo 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-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Kimi K2 0905 is available from Novita.

DeepSeek-R1

deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.85/1MOutput Price:Output: $2.50/1M
together logo
Together
Input Price:Input: $7.00/1MOutput Price:Output: $7.00/1M
fireworks logo
Fireworks
Input Price:Input: $8.00/1MOutput Price:Output: $8.00/1M

Kimi K2 0905

novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $2.50/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Has open weights
Moonshot AI
Larger context window (262,144 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1
Moonshot AI
Kimi K2 0905

FAQ

Common questions about DeepSeek-R1 vs Kimi K2 0905.

Which is better, DeepSeek-R1 or Kimi K2 0905?

DeepSeek-R1 (DeepSeek) and Kimi K2 0905 (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-R1 compare to Kimi K2 0905 in benchmarks?

Kimi K2 0905 scores HumanEval: 94.5%, MMLU: 90.2%, MATH: 89.1%, MMLU-Pro: 82.5%, GPQA: 75.8%.

Is DeepSeek-R1 cheaper than Kimi K2 0905?

DeepSeek-R1 is 1.1x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/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-R1 and Kimi K2 0905?

DeepSeek-R1 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-R1 and Kimi K2 0905?

Key differences include context window (131K vs 262K), input pricing ($0.55 vs $0.60/M), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1 and Kimi K2 0905?

DeepSeek-R1 is developed by DeepSeek and Kimi K2 0905 is developed by Moonshot AI.