LLM Comparison

DeepSeek V4.1 Flash vs Kimi K2.7: benchmark scores, pricing & comparison.

Side-by-side DeepSeek V4.1 Flash vs Kimi K2.7 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.

Open live leaderboardDeepSeek V4.1 Flash model pageKimi K2.7 model page
Rank #22 vs #49AskClash overall scores 61.7 vs 45.3.
Pricing $0.15/$0.60 vs $0.95/$4.00Input and output token prices per 1M tokens when published.
API vs Open WeightDeepSeek vs Moonshot AI.

DeepSeek V4.1 Flash vs Kimi K2.7 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricDeepSeek V4.1 FlashKimi K2.7
Overall Score61.745.3
Leaderboard Rank#22#49
ACB—43.0
RWT—7.5
HLE36.835.0
GPQA90.989.6
IFEval—63.1
Terminal-Bench90.644.7
DeepSWE74.230.5
GDPval-AA—1114.5
MCP Atlas—76.0
Tau2—90.1
Input Price (per 1M tokens)$0.15$0.95
Output Price (per 1M tokens)$0.60$4.00
Context Window1M256K
Benchmarks Published410

DeepSeek V4.1 Flash vs Kimi K2.7 head-to-head charts

DeepSeek V4.1 Flash leads 5 and Kimi K2.7 leads 0 of 5 shared benchmarks. DeepSeek V4.1 Flash is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

DeepSeek V4.1 FlashKimi K2.7
Overall
61.7DeepSeek V4.1 Flash
45.3Kimi K2.7
HLE
36.8DeepSeek V4.1 Flash
35.0Kimi K2.7
GPQA
90.9DeepSeek V4.1 Flash
89.6Kimi K2.7
Terminal-Bench
90.6DeepSeek V4.1 Flash
44.7Kimi K2.7
DeepSWE
74.2DeepSeek V4.1 Flash
30.5Kimi K2.7
DeepSeek V4.1 Flash
Input$0.15
Output$0.60
Workload$0.27
Context1M
Kimi K2.7
Input$0.95
Output$4.00
Workload$1.75
Context256K

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More DeepSeek V4.1 Flash and Kimi K2.7 comparisons

Explore how DeepSeek V4.1 Flash and Kimi K2.7 stack up against other top-ranked LLMs.

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How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

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.