Grok 4.6 vs Kimi K2.7 Code
Grok 4.6 leads the LLM Stats Score 47.0 to 39.6. Kimi K2.7 Code is 2.1x cheaper per token.
xAI · Moonshot AI · Updated for 2026
Which is better?
Grok 4.6 leads the overall LLM Stats Score 47.0 to 39.6, ranking #18 overall.
In the 1 individual benchmarks reported for both models, Grok 4.6 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Kimi K2.7 Code is roughly 2.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Grok 4.6 also accepts a larger context window (500,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Grok 4.6
- overall performance matters — it scores 47.0 and ranks #18 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 500,000 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Kimi K2.7 Code
- cost matters — it's about 2.1x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
10 reported for Grok 4.6 · 9 for Kimi K2.7 Code
Grok 4.6 outperforms in 1 benchmarks (DeepSWE 1.1), while Kimi K2.7 Code is better at 0 benchmarks.
Grok 4.6 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Grok 4.6 ($2.00/1M tokens) is 2.7x more expensive than Kimi K2.7 Code ($0.74/1M tokens).
For output processing, Grok 4.6 ($6.00/1M tokens) is 1.7x more expensive than Kimi K2.7 Code ($3.50/1M tokens).
In conclusion, Grok 4.6 is more expensive than Kimi K2.7 Code.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Grok 4.6 accepts 500,000 input tokens compared to Kimi K2.7 Code's 262,144 tokens. Only Kimi K2.7 Code specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Both Grok 4.6 and Kimi K2.7 Code support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Grok 4.6
Kimi K2.7 Code
License
Usage and distribution terms
Grok 4.6 is licensed under a proprietary license, while Kimi K2.7 Code uses Modified MIT License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Modified MIT License
Open weights
Release Timeline
When each model was launched
Grok 4.6 was released on 2026-08-12, while Kimi K2.7 Code was released on 2026-06-12.
Grok 4.6 is 2 months newer than Kimi K2.7 Code.
Aug 12, 2026
2 weeks ago
2mo newerJun 12, 2026
2 months ago
Knowledge Cutoff
When training data ends
Grok 4.6 has a documented knowledge cutoff of 2026-02-01, while Kimi K2.7 Code's cutoff date is not specified.
We can confirm Grok 4.6's training data extends to 2026-02-01, but cannot make a direct comparison without Kimi K2.7 Code's cutoff date.
Feb 2026
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Provider Availability
Grok 4.6 is available from xAI. Kimi K2.7 Code is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
Grok 4.6
Kimi K2.7 Code
Outputs Comparison
Judge for yourself.
Run your own prompts against Grok 4.6 and Kimi K2.7 Code side-by-side, then vote on the output you prefer.
FAQ
Common questions about Grok 4.6 vs Kimi K2.7 Code.