head-to-head

xAI: Grok Latest vs MoonshotAI: Kimi K2.7 Code

Side-by-side comparison of specs, pricing, benchmark scores, and task rankings. Updated 2026-11-07.

xAI: Grok Latest MoonshotAI: Kimi K2.7 Code
Vendor~x-aimoonshotai
Quality Score100100
Benchmark Score10.974.1
Input Price$2.00/M$0.60/M
Output Price$6.00/M$3.50/M
Context Window500,000262,144
Max Output450,000235,929
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index12.469.2
ai_index_agentic-48.8
ai_index_coding-100.0

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, Kimi K2.7 Code costs $1.48 and Grok Latest costs $3.50, so Kimi K2.7 Code is about 2.4 times cheaper for the same work.

Grok Latest reads up to 500,000 tokens at once, roughly 750 pages of text, against about 393 pages for Kimi K2.7 Code.

On our blended benchmark score Kimi K2.7 Code leads 74.1 to 10.9.

Across the 20 tasks where they differ, Kimi K2.7 Code on 20 (SQL Generation, Code Review, Code Completion and others).

Grok Latest was released in July 2026 and Kimi K2.7 Code in June 2026.

Pick Grok Latest if you need long documents; pick Kimi K2.7 Code if you need lower cost, benchmark performance or the stronger all-round task scores.

Costs use current list prices per million tokens; page counts assume about 0.75 words per token and 500 words per page.

Who wins by task?

TaskxAI: Grok LatestMoonshotAI: Kimi K2.7 Code
SQL Generation 134 163
Code Review 134 155
Code Completion 118 129
Code Refactoring 138 151
Bug Fixing 138 165
Unit Test Generation 125 147
Code Documentation 131 135
Regex Writing 119 133
CI/CD Pipelines 121 138
Frontend Component Design 123 142
Data Analysis 125 162
CSV / Spreadsheet Cleanup 133 147
ETL Scripting 129 144
JSON Extraction 122 147
Bulk Data Labeling 119 134
OCR / Document Parsing 131 142
Table Extraction from PDFs 131 142
Long-Document Summarization 139 147
Short-Form Summarization 115 130
Blog Post Writing 122 134

Scores reflect capability match + benchmark data + pricing for each task. Methodology →

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