LLM Comparison

MiniMax-M3 vs Kimi K2.7: benchmark scores, pricing & comparison.

Side-by-side MiniMax-M3 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.

Verdict: MiniMax-M3 ranks higher (#118 vs #119); MiniMax-M3 costs less ($0.30/$1.20 vs $0.95/$4.00 per 1M tokens).

Rank #118 vs #119AskClash overall scores 38.5 vs 37.8.
Pricing $0.30/$1.20 vs $0.95/$4.00Input and output token prices per 1M tokens when published.
Open Weight vs Open WeightMiniMax vs Moonshot AI.

MiniMax-M3 vs Kimi K2.7 benchmark comparison

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

MetricMiniMax-M3Kimi K2.7
Overall Score38.537.8
Leaderboard Rank#118#119
ACB29.843.0
RWT8.57.5
HLE37.135.0
GPQA92.989.6
IFEval82.963.1
SWE-bench80.5—
SWE-Pro59.0—
DeepSWE—30.5
GDPval-AA58.41037.5
OSWorld70.1—
MCP Atlas74.276.0
Finance Agent48.3—
MMMU-Pro78.1—
Tau288.990.1
Input Price (per 1M tokens)$0.30$0.95
Output Price (per 1M tokens)$1.20$4.00
Context Window1M256K
Benchmarks Published119

MiniMax-M3 vs Kimi K2.7 head-to-head charts

MiniMax-M3 leads 5 and Kimi K2.7 leads 4 of 9 shared benchmarks. MiniMax-M3 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

MiniMax-M3Kimi K2.7
Overall
38.5MiniMax-M3
37.8Kimi K2.7
ACB
29.8MiniMax-M3
43.0Kimi K2.7
RWT
8.5MiniMax-M3
7.5Kimi K2.7
HLE
37.1MiniMax-M3
35.0Kimi K2.7
GPQA
92.9MiniMax-M3
89.6Kimi K2.7
IFEval
82.9MiniMax-M3
63.1Kimi K2.7
GDPval-AA
58.4MiniMax-M3
1037.5Kimi K2.7
MCP Atlas
74.2MiniMax-M3
76.0Kimi K2.7
Tau2
88.9MiniMax-M3
90.1Kimi K2.7
MiniMax-M3
Input$0.30
Output$1.20
Workload$0.54
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 MiniMax-M3 and Kimi K2.7 comparisons

Explore how MiniMax-M3 and Kimi K2.7 stack up against other top-ranked LLMs.

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.