Model Comparison

DeepSeek-R1-0528 vs Kimi K2 Instruct

DeepSeek-R1-0528 significantly outperforms across most benchmarks. Kimi K2 Instruct is 1.8x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

11 benchmarks

DeepSeek-R1-0528 outperforms in 9 benchmarks (Aider-Polyglot, AIME 2024, AIME 2025, GPQA, HMMT 2025, Humanity's Last Exam, MMLU-Pro, MMLU-Redux, SimpleQA), while Kimi K2 Instruct is better at 2 benchmarks (SWE-bench Multilingual, Terminal-Bench).

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Thu May 21 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Kimi K2 Instruct costs less

For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) costs the same as Kimi K2 Instruct ($0.50/1M tokens).

For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 4.3x more expensive than Kimi K2 Instruct ($0.50/1M tokens).

In conclusion, DeepSeek-R1-0528 is more expensive than Kimi K2 Instruct.*

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

Lowest available price from all providers
Thu May 21 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
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-R1-0528, making it 49.0% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Moonshot AI
Kimi K2 Instruct
1.0Tparameters
671.0B
DeepSeek-R1-0528
1000.0B
Kimi K2 Instruct

Context Window

Maximum input and output token capacity

Kimi K2 Instruct accepts 200,000 input tokens compared to DeepSeek-R1-0528's 131,072 tokens. Kimi K2 Instruct can generate longer responses up to 200,000 tokens, while DeepSeek-R1-0528 is limited to 131,072 tokens.

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Moonshot AI
Kimi K2 Instruct
Input200,000 tokens
Output200,000 tokens
Thu May 21 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-R1-0528

MIT

Open weights

Kimi K2 Instruct

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Kimi K2 Instruct was released on 2025-07-11.

Kimi K2 Instruct is 1 month newer than DeepSeek-R1-0528.

DeepSeek-R1-0528

May 28, 2025

11 months ago

Kimi K2 Instruct

Jul 11, 2025

10 months ago

1mo 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-R1-0528 is available from DeepInfra, DeepSeek, Novita. Kimi K2 Instruct is available from Fireworks, Novita.

DeepSeek-R1-0528

deepinfra logo
Deepinfra
Input Price:Input: $0.50/1MOutput Price:Output: $2.15/1M
deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.70/1MOutput Price:Output: $2.50/1M

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
Higher Aider-Polyglot score (71.6% vs 60.0%)
Higher AIME 2024 score (91.4% vs 69.6%)
Higher AIME 2025 score (87.5% vs 49.5%)
Higher GPQA score (81.0% vs 75.1%)
Higher HMMT 2025 score (79.4% vs 38.8%)
Higher Humanity's Last Exam score (17.7% vs 4.7%)
Higher MMLU-Pro score (85.0% vs 81.1%)
Higher MMLU-Redux score (93.4% vs 92.7%)
Higher SimpleQA score (92.3% vs 31.0%)
Moonshot AI
Larger context window (200,000 tokens)
Less expensive output tokens
Higher SWE-bench Multilingual score (47.3% vs 30.5%)
Higher Terminal-Bench score (30.0% vs 5.7%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Moonshot AI
Kimi K2 Instruct

FAQ

Common questions about DeepSeek-R1-0528 vs Kimi K2 Instruct.

Which is better, DeepSeek-R1-0528 or Kimi K2 Instruct?

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Kimi K2 Instruct is made by Moonshot AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-R1-0528 compare to Kimi K2 Instruct in benchmarks?

DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Kimi K2 Instruct scores MATH-500: 97.4%, GSM8k: 97.3%, CBNSL: 95.6%, HumanEval: 93.3%, MMLU-Redux: 92.7%.

Is DeepSeek-R1-0528 cheaper than Kimi K2 Instruct?

Both models cost $0.50 per million input tokens.

What are the context window sizes for DeepSeek-R1-0528 and Kimi K2 Instruct?

DeepSeek-R1-0528 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.

What are the main differences between DeepSeek-R1-0528 and Kimi K2 Instruct?

Key differences include context window (131K vs 200K). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1-0528 and Kimi K2 Instruct?

DeepSeek-R1-0528 is developed by DeepSeek and Kimi K2 Instruct is developed by Moonshot AI.