Model Comparison

DeepSeek-R1 vs Kimi K2 Instruct

Comparing DeepSeek-R1 and Kimi K2 Instruct 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 Instruct 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

Kimi K2 Instruct costs less

For input processing, DeepSeek-R1 ($0.55/1M tokens) is 1.1x more expensive than Kimi K2 Instruct ($0.50/1M tokens).

For output processing, DeepSeek-R1 ($2.19/1M tokens) is 4.4x more expensive than Kimi K2 Instruct ($0.50/1M tokens).

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

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

Lowest available price from all providers
Mon Apr 13 2026 • llm-stats.com
DeepSeek
DeepSeek-R1
Input tokens$0.55
Output tokens$2.19
Best providerDeepSeek
Moonshot AI
Kimi K2 Instruct
Input tokens$0.50
Output tokens$0.50
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

329.0B diff

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

DeepSeek
DeepSeek-R1
671.0Bparameters
Moonshot AI
Kimi K2 Instruct
1000.0Bparameters
671.0B
DeepSeek-R1
1000.0B
Kimi K2 Instruct

Context Window

Maximum input and output token capacity

Kimi K2 Instruct accepts 200,000 input tokens compared to DeepSeek-R1's 131,072 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 tokens, while DeepSeek-R1 is limited to 131,072 tokens.

DeepSeek
DeepSeek-R1
Input131,072 tokens
Output131,072 tokens
Moonshot AI
Kimi K2 Instruct
Input200,000 tokens
Output200,000 tokens
Mon Apr 13 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-R1

MIT

Open weights

Kimi K2 Instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-R1 was released on 2025-01-20, while Kimi K2 Instruct was released on 2025-07-11.

Kimi K2 Instruct is 6 months newer than DeepSeek-R1.

DeepSeek-R1

Jan 20, 2025

1.2 years ago

Kimi K2 Instruct

Jul 11, 2025

9 months ago

5mo 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 Instruct is available from Fireworks, 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 Instruct

fireworks logo
Fireworks
Input Price:Input: $0.50/1MOutput Price:Output: $0.50/1M
novita logo
Novita
Input Price:Input: $0.57/1MOutput Price:Output: $2.30/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Moonshot AI
Larger context window (200,000 tokens)
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

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

FAQ

Common questions about DeepSeek-R1 vs Kimi K2 Instruct

DeepSeek-R1 (DeepSeek) and Kimi K2 Instruct (Moonshot AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Kimi K2 Instruct scores MATH-500: 97.4%, GSM8k: 97.3%, CBNSL: 95.6%, HumanEval: 93.3%, MMLU-Redux: 92.7%.
Kimi K2 Instruct is 1.1x cheaper for input tokens. DeepSeek-R1 costs $0.55/M input and $2.19/M output via deepseek. Kimi K2 Instruct costs $0.50/M input and $0.50/M output via fireworks.
DeepSeek-R1 supports 131K tokens and Kimi K2 Instruct supports 200K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 200K), input pricing ($0.55 vs $0.50/M). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1 is developed by DeepSeek and Kimi K2 Instruct is developed by Moonshot AI.