head-to-head

MoonshotAI: Kimi K2.6 vs OpenAI: GPT-5.3-Codex

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

MoonshotAI: Kimi K2.6 OpenAI: GPT-5.3-Codex
Vendormoonshotaiopenai
Quality Score100100
Benchmark Score76.773.4
Input Price$0.65/M$1.75/M
Output Price$3.41/M$14.00/M
Context Window262,144400,000
Max Output235,929128,000
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index73.073.0
ai_index_agentic49.9-
ai_index_coding100.0-
eqbench63.5-

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, Kimi K2.6 costs $1.50 and GPT-5.3-Codex costs $5.25, so Kimi K2.6 is about 3.5 times cheaper for the same work.

GPT-5.3-Codex reads up to 400,000 tokens at once, roughly 600 pages of text, against about 393 pages for Kimi K2.6.

On our blended benchmark score Kimi K2.6 leads 76.7 to 73.4.

Across the 20 tasks where they differ, Kimi K2.6 scores higher on 20 (SQL Generation, Code Review, Code Completion and others).

Kimi K2.6 was released in April 2026 and GPT-5.3-Codex in February 2026.

Pick Kimi K2.6 if you need lower cost, benchmark performance or the stronger all-round task scores; pick GPT-5.3-Codex if you need long documents.

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?

TaskMoonshotAI: Kimi K2.6OpenAI: GPT-5.3-Codex
SQL Generation 168 141
Code Review 164 145
Code Completion 131 118
Code Refactoring 160 147
Bug Fixing 174 149
Unit Test Generation 152 132
Code Documentation 140 135
Regex Writing 136 124
CI/CD Pipelines 142 128
Frontend Component Design 145 130
Data Analysis 166 134
CSV / Spreadsheet Cleanup 151 135
ETL Scripting 151 138
JSON Extraction 147 120
Bulk Data Labeling 134 117
OCR / Document Parsing 144 134
Table Extraction from PDFs 144 134
Long-Document Summarization 156 148
Short-Form Summarization 131 116
Blog Post Writing 139 129

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

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