Benchmark scores
Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.
LLM Comparison
Kimi K2.7 Code vs DeepSeek V4 Pro (Max): benchmark scores, pricing & comparison.
Side-by-side Kimi K2.7 Code vs DeepSeek V4 Pro (Max) comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.
Rank #8 vs #13AskClash overall scores 68.3 vs 59.9.
Pricing $0.95/$4.00 vs $1.74/$3.48Input and output token prices per 1M tokens when published.
Open Weight vs Open WeightMoonshot AI vs DeepSeek.
Kimi K2.7 Code vs DeepSeek V4 Pro (Max) benchmark comparison
Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.
| Metric | Kimi K2.7 Code | DeepSeek V4 Pro (Max) |
|---|---|---|
| Overall Score | 68.3 | 59.9 |
| Leaderboard Rank | #8 | #13 |
| RWT | 7.5 | 8.0 |
| HLE | 54.0 | 37.7 |
| GPQA | 90.5 | 90.1 |
| MATH-500 | — | 64.5 |
| SWE-bench | 80.2 | 80.6 |
| SWE-Pro | 58.6 | 55.4 |
| Terminal-Bench | 66.7 | 67.9 |
| LiveCodeBench | 89.6 | 93.5 |
| OSWorld | 73.1 | — |
| MCP Atlas | 76.0 | 73.6 |
| Finance Agent | 44.9 | — |
| CharXiv | 80.4 | — |
| MMMU-Pro | 79.4 | — |
| Tau2 | 90.1 | 96.2 |
| MRCR | — | 83.5 |
| Input Price (per 1M tokens) | $0.95 | $1.74 |
| Output Price (per 1M tokens) | $4.00 | $3.48 |
| Context Window | 256K | 1M |
| Benchmark Cells | 13 | 10 |
More Kimi K2.7 Code and DeepSeek V4 Pro (Max) comparisons
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How to read this comparison
Token pricing
Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.
Coverage matters
Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.
This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.