LLM Comparison

Kimi K3 vs LongCat 2.0: benchmark scores, pricing & comparison.

Side-by-side Kimi K3 vs LongCat 2.0 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: Kimi K3 ranks higher (#28 vs #60) and wins 3 of 3 shared benchmarks; LongCat 2.0 costs less ($0.75/$2.95 vs $3.00/$15.0 per 1M tokens).

Rank #28 vs #60AskClash overall scores 55.7 vs 30.6.
Pricing $3.00/$15.0 vs $0.75/$2.95Input and output token prices per 1M tokens when published.
Open Weight vs Open WeightMoonshot AI vs Meituan.

Kimi K3 vs LongCat 2.0 benchmark comparison

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

MetricKimi K3LongCat 2.0
Overall Score55.730.6
Leaderboard Rank#28#60
ACB57.7—
RWT8.0—
Coding Agent Index51.9—
HLE43.533.7
GPQA93.588.9
IFEval—90.0
SWE-Pro—59.5
SWE-Atlas66.1—
Terminal-Bench12.6—
DeepSWE68.5—
GDPval-AA1668.0869.4
MCP Atlas84.2—
Finance Agent53.1—
CharXiv84.8—
MMMU-Pro81.6—
ARC-AGI 260.4—
Tau2—88.2
Input Price (per 1M tokens)$3.00$0.75
Output Price (per 1M tokens)$15.0$2.95
Context Window1M1M
Benchmarks Published167

Kimi K3 vs LongCat 2.0 head-to-head charts

Kimi K3 leads 4 and LongCat 2.0 leads 0 of 4 shared benchmarks. LongCat 2.0 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Kimi K3LongCat 2.0
Overall
55.7Kimi K3
30.6LongCat 2.0
HLE
43.5Kimi K3
33.7LongCat 2.0
GPQA
93.5Kimi K3
88.9LongCat 2.0
GDPval-AA
1668.0Kimi K3
869.4LongCat 2.0
Kimi K3
Input$3.00
Output$15.0
Workload$6.00
Context1M
LongCat 2.0
Input$0.75
Output$2.95
Workload$1.34
Context1M

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

More Kimi K3 and LongCat 2.0 comparisons

Explore how Kimi K3 and LongCat 2.0 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.