Model Comparison
Grok-2 vs Kimi K2-Thinking-0905Which is better in 2026?
Kimi K2-Thinking-0905 significantly outperforms across most benchmarks. Kimi K2-Thinking-0905 is 4.7x cheaper per token.
Verdict: Grok-2 vs Kimi K2-Thinking-0905 — which is better?
Grok-2 (by xAI) and Kimi K2-Thinking-0905 (by Moonshot AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Grok-2 outperforms in 0 benchmarks, while Kimi K2-Thinking-0905 is better at 2 benchmarks (GPQA, MMLU-Pro). Kimi K2-Thinking-0905 significantly outperforms across most benchmarks.
On price, Kimi K2-Thinking-0905 is roughly 4.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K2-Thinking-0905 also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Choose Grok-2 if…
- you want predictable pricing at $2.00/M input and $10.00/M output
Choose Kimi K2-Thinking-0905 if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 4.7x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Grok-2 outperforms in 0 benchmarks, while Kimi K2-Thinking-0905 is better at 2 benchmarks (GPQA, MMLU-Pro).
Kimi K2-Thinking-0905 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Grok-2 ($2.00/1M tokens) is 4.3x more expensive than Kimi K2-Thinking-0905 ($0.47/1M tokens).
For output processing, Grok-2 ($10.00/1M tokens) is 5.0x more expensive than Kimi K2-Thinking-0905 ($2.00/1M tokens).
In conclusion, Grok-2 is more expensive than Kimi K2-Thinking-0905.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Kimi K2-Thinking-0905 accepts 262,144 input tokens compared to Grok-2's 128,000 tokens. Kimi K2-Thinking-0905 can generate longer responses up to 262,144 tokens, while Grok-2 is limited to 8,000 tokens.
Input Capabilities
Supported data types and modalities
Grok-2 supports multimodal inputs, whereas Kimi K2-Thinking-0905 does not.
Grok-2 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Grok-2
Kimi K2-Thinking-0905
License
Usage and distribution terms
Grok-2 is licensed under a proprietary license, while Kimi K2-Thinking-0905 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Grok-2 was released on 2024-08-13, while Kimi K2-Thinking-0905 was released on 2025-09-05.
Kimi K2-Thinking-0905 is 13 months newer than Grok-2.
Aug 13, 2024
1.8 years ago
Sep 5, 2025
9 months ago
1.1yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Grok-2 is available from xAI. Kimi K2-Thinking-0905 is available from DeepInfra, Novita, Fireworks.
Grok-2
Kimi K2-Thinking-0905
Outputs Comparison
Key Takeaways
Kimi K2-Thinking-0905
View detailsMoonshot AI
Detailed Comparison
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FAQ
Common questions about Grok-2 vs Kimi K2-Thinking-0905.