head-to-head

Qwen: Qwen3.7 Flash vs MoonshotAI: Kimi K2.6

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

Qwen: Qwen3.7 Flash MoonshotAI: Kimi K2.6
Vendorqwenmoonshotai
Quality Score100100
Benchmark Score-76.7
Input Price$0.03/M$0.65/M
Output Price$0.13/M$3.41/M
Context Window1,000,000262,144
Max Output65,536235,929
Tool Calling✓✓
Structured Output✓✓
Reasoning Mode✓✓
Vision✓✓
Audio--
Benchmark Scores
ai_index-73.0
ai_index_agentic-49.9
ai_index_coding-100.0
eqbench-63.5

The verdict

For a sample job of 1 million input tokens and 250,000 output tokens, Qwen3.7 Flash costs $0.062 and Kimi K2.6 costs $1.50, so Qwen3.7 Flash is about 24.0 times cheaper for the same work.

Qwen3.7 Flash reads up to 1,000,000 tokens at once, roughly 1,500 pages of text, against about 393 pages for Kimi K2.6.

Only Qwen3.7 Flash offers video input.

Across the 20 tasks where they differ, Qwen3.7 Flash scores higher on 1 (Code Completion), Kimi K2.6 on 19 (SQL Generation, Code Review, Code Refactoring and others).

Qwen3.7 Flash was released in July 2026 and Kimi K2.6 in April 2026.

Pick Qwen3.7 Flash if you need lower cost, long documents or video input; pick Kimi K2.6 if you need 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?

TaskQwen: Qwen3.7 FlashMoonshotAI: Kimi K2.6
SQL Generation 134 168
Code Review 132 164
Code Completion 132 131
Code Refactoring 136 160
Bug Fixing 136 174
Unit Test Generation 124 152
Code Documentation 132 140
Regex Writing 120 136
CI/CD Pipelines 120 142
Frontend Component Design 122 145
Data Analysis 124 166
CSV / Spreadsheet Cleanup 134 151
ETL Scripting 128 151
JSON Extraction 132 147
Bulk Data Labeling 130 134
OCR / Document Parsing 131 144
Table Extraction from PDFs 131 144
Long-Document Summarization 138 156
Short-Form Summarization 124 131
Blog Post Writing 122 139

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

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