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KimivsGPT-o1

Moonshot AI vs OpenAI — Side-by-side model comparison

GPT-o1 leads 3/5 categories

Head-to-Head Comparison

MetricKimiGPT-o1
Provider
Arena Rank
#3
Context Window
2M
200K
Input Pricing
Undisclosed/1M tokens
$15.00/1M tokens
Output Pricing
Undisclosed/1M tokens
$60.00/1M tokens
Parameters
Undisclosed
Undisclosed
Open Source
No
No
Best For
Ultra-long documents, research, analysis
Complex reasoning, math, science, coding
Release Date
Mar 18, 2024
Dec 17, 2024

Kimi

Kimi is Moonshot AI's flagship model featuring an industry-leading 2 million token context window, the largest publicly available at launch. This extraordinary context length enables processing of entire books, research paper collections, and massive codebases in a single prompt. Developed by a team of former Google and Microsoft researchers in Beijing, Kimi has become one of China's most popular AI assistants, particularly valued for its ability to analyze very long documents.

View Moonshot AI profile →

GPT-o1

GPT-o1 is OpenAI's first dedicated reasoning model, introducing the concept of 'thinking tokens' where the model reasons through problems step-by-step before generating a response. This approach significantly improves performance on complex mathematics, coding challenges, and scientific reasoning compared to standard language models. With a 200K token context window, o1 can process lengthy technical documents while applying deep reasoning. It excels on competition-level math problems, PhD-level science questions, and complex coding tasks that require careful logical thinking. While slower and more expensive than GPT-4o due to the reasoning overhead, o1 delivers substantially better results on tasks that benefit from deliberate, structured problem-solving rather than quick pattern matching.

View OpenAI profile →

Key Differences: Kimi vs GPT-o1

1

Kimi supports a larger context window (2M), allowing it to process longer documents in a single request.

K

When to use Kimi

  • +You need to process long documents (2M context)
  • +Your use case involves ultra-long documents, research, analysis
View full Kimi specs →
G

When to use GPT-o1

  • +Your use case involves complex reasoning, math, science, coding
View full GPT-o1 specs →

The Verdict

GPT-o1 wins our head-to-head comparison with 3 out of 5 category wins. It's the stronger choice for complex reasoning, math, science, coding, though Kimi holds an edge in ultra-long documents, research, analysis.

Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, Kimi or GPT-o1?
In our head-to-head comparison, GPT-o1 leads in 3 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). GPT-o1 excels at complex reasoning, math, science, coding, while Kimi is better suited for ultra-long documents, research, analysis. The best choice depends on your specific requirements, budget, and use case.
How does Kimi pricing compare to GPT-o1?
Kimi charges Undisclosed per 1M input tokens and Undisclosed per 1M output tokens. GPT-o1 charges $15.00 per 1M input tokens and $60.00 per 1M output tokens. For high-volume production workloads, the pricing difference can significantly impact total cost of ownership.
What is the context window difference between Kimi and GPT-o1?
Kimi supports a 2M token context window, while GPT-o1 supports 200K tokens. Kimi can process longer documents, codebases, and conversations in a single request. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use Kimi or GPT-o1 for free?
Kimi is a paid API model starting at Undisclosed per 1M input tokens. GPT-o1 is a paid API model starting at $15.00 per 1M input tokens.
Which model has better benchmarks, Kimi or GPT-o1?
Kimi's arena rank is not yet available, while GPT-o1 holds rank #3. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Kimi or GPT-o1 better for coding?
Kimi's primary strength is ultra-long documents, research, analysis. GPT-o1 is specifically optimized for coding tasks. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.