DeepSeek-V4-ProvsKimi K2.6
Across 9 shared benchmarks, Kimi K2.6 leads overall: DeepSeek-V4-Pro wins 1, Kimi K2.6 wins 8, with 0 ties and an average score difference of -19.42.
DeepSeek-V4-Pro
DeepSeek-AI · 2026-04-24 · Reasoning model
Kimi K2.6
Moonshot AI · 2026-04-20 · Reasoning model
DeepSeek-V4-Pro1 win(11%)(89%)8 winsKimi K2.6
Benchmark scores
Grouped by capability, sorted by largest gap within each. 9 shared benchmarks.
Coding and Software Engineer
Kimi K2.6 4/4| Benchmark | DeepSeek-V4-Pro | Kimi K2.6 | Diff |
|---|---|---|---|
| LiveCodeBench | 56.8075 / 120Normal (No Tools) | 89.607 / 120Thinking (No Tools) | -32.80 |
| SWE-bench Multilingual | 69.8015 / 20Normal (With Tools) | 76.704 / 20Thinking (With Tools) | -6.90 |
| SWE-bench Verified | 73.6041 / 108Normal (With Tools) | 80.2013 / 108Thinking (With Tools) | -6.60 |
| SWE-Bench Pro - Public | 52.1028 / 43Normal (With Tools) | 58.607 / 43Thinking (With Tools) | -6.50 |
General Knowledge
Kimi K2.6 2/2| Benchmark | DeepSeek-V4-Pro | Kimi K2.6 | Diff |
|---|---|---|---|
| HLE | 7.70141 / 157Normal (No Tools) | 549 / 157Thinking (With Tools + Internet) | -46.30 |
| GPQA Diamond | 72.90102 / 178Normal (No Tools) | 90.5016 / 178Thinking (No Tools) | -17.60 |
AI Agent - Information Search
DeepSeek-V4-Pro 1/1| Benchmark | DeepSeek-V4-Pro | Kimi K2.6 | Diff |
|---|---|---|---|
| BrowseComp | 83.409 / 45极高强度思考（工具） | 83.2010 / 45Thinking (With Tools + Internet) | +0.20 |
AI Agent - Tool Usage
Kimi K2.6 1/1| Benchmark | DeepSeek-V4-Pro | Kimi K2.6 | Diff |
|---|---|---|---|
| Terminal Bench 2.0 | 59.1022 / 46Normal (With Tools) | 66.7010 / 46Thinking (With Tools) | -7.60 |
Math and Reasoning
Kimi K2.6 1/1| Benchmark | DeepSeek-V4-Pro | Kimi K2.6 | Diff |
|---|---|---|---|
| IMO-AnswerBench | 35.3019 / 19Normal (No Tools) | 866 / 19Thinking (No Tools) | -50.70 |
Specs
| Field | DeepSeek-V4-Pro | Kimi K2.6 |
|---|---|---|
| Publisher | DeepSeek-AI | Moonshot AI |
| Release date | 2026-04-24 | 2026-04-20 |
| Model type | Reasoning model | Reasoning model |
| Architecture | MoE | MoE |
| Parameters | 1.6T | 1T |
| Context length | 1M | 256K |
| Max output | 375K | Not available |
API pricing
Prices use DataLearner records when available; missing fields are not inferred.
| Item | DeepSeek-V4-Pro | Kimi K2.6 |
|---|---|---|
| Text input | $0.435 / 1M tokens | $0.95 / 1M tokens |
| Text output | $0.87 / 1M tokens | $4 / 1M tokens |
| Cache read | $0.87 / 1M tokens | $0.16 / 1M tokens |
| Cache write | $0.003625 / 1M tokens | $0.95 / 1M tokens |
Summary
- DeepSeek-V4-Proleads in:AI Agent - Information Search (1/1)
- Kimi K2.6leads in:Coding and Software Engineer (4/4), General Knowledge (2/2), AI Agent - Tool Usage (1/1), Math and Reasoning (1/1)
On average across the 9 shared benchmarks, Kimi K2.6 scores 19.42 higher.
Largest single-benchmark gap: IMO-AnswerBench — DeepSeek-V4-Pro 35.30 vs Kimi K2.6 86 (-50.70).
Page generated from structured model, pricing and benchmark records. No real-time LLM is used to write the prose.