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Moonshot AI (Kimi) Kimi K2.7 Code VS xAI Grok 4.5

✍️ Analysis by:the whichllmmodel Editorial Team|📅 Updated: June 2026

⚖️Our Take

If your budget allows, Grok 4.5 is the superior choice here, offering a clear benchmark advantage while carrying only a moderate price premium (1.8x). We recommend choosing Kimi K2.7 Code only if you need to optimize costs for very high-volume pipelines.
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Model Specs

Kimi K2.7 Code

Open SourceAPI Available

Benchmarks & Scores

Coding (swe-bench-pro)
58.6%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)
90%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)1.8x cheaper
$1.71Input: $0.95 | Output: $4.00
Context Window
262.14k tokens
Model Specs

Grok 4.5

Benchmarks & Scores

Coding (swe-bench-pro)Winner (+6.1%)
64.7%

excellent at multi-file repositories, autonomous agents, and industrial codebases

Reasoning (gpqa-diamond)Winner (+3.0%)
93%

graduate-level science QA

Cost & Performance

Cost (per 1M tokens)
$3.00Input: $2.00 | Output: $6.00
Context WindowLarger
500k tokens

Frequently Asked Questions about Kimi K2.7 Code vs Grok 4.5 comparison

Kimi K2.7 Code is cheaper than Grok 4.5. Kimi K2.7 Code has a blended cost of $1.71/1M tokens, which is about 1.8x cheaper than Grok 4.5 at $3.00/1M tokens.

Grok 4.5 is better for coding tasks on this benchmark. It scores 64.7% on swe-bench-pro (excellent at multi-file repositories, autonomous agents, and industrial codebases) compared to Kimi K2.7 Code which scores 58.6%.