LLM Comparison

Claude Sonnet 5.5 vs Kimi K3.1 Pro: benchmark scores, pricing & comparison.

Side-by-side Claude Sonnet 5.5 vs Kimi K3.1 Pro 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: Claude Sonnet 5.5 ranks higher (#3 vs #4); Kimi K3.1 Pro wins 5 of 5 shared benchmarks.

Rank #3 vs #4AskClash overall scores 76.0 vs 75.5.
Pricing $2.00/$10.0 vs $2.00/$10.0Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightAnthropic vs Moonshot AI.

Claude Sonnet 5.5 vs Kimi K3.1 Pro benchmark comparison

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

MetricClaude Sonnet 5.5Kimi K3.1 Pro
Overall Score76.075.5
Leaderboard Rank#3#4
ACB76.6—
HLE64.570.0
GPQA—94.2
SWE-Pro81.3—
Terminal-Bench63.665.7
DeepSWE71.075.5
GDPval-AA1844.21846.0
Finance Agent58.158.6
CharXiv—89.0
MMMU-Pro—84.1
Input Price (per 1M tokens)$2.00$2.00
Output Price (per 1M tokens)$10.0$10.0
Context Window1M1M
Benchmarks Published109

Claude Sonnet 5.5 vs Kimi K3.1 Pro head-to-head charts

Claude Sonnet 5.5 leads 1 and Kimi K3.1 Pro leads 5 of 6 shared benchmarks. Charts show only benchmarks both models publish.

Claude Sonnet 5.5Kimi K3.1 Pro
Overall
76.0Claude Sonnet 5.5
75.5Kimi K3.1 Pro
HLE
64.5Claude Sonnet 5.5
70.0Kimi K3.1 Pro
Terminal-Bench
63.6Claude Sonnet 5.5
65.7Kimi K3.1 Pro
DeepSWE
71.0Claude Sonnet 5.5
75.5Kimi K3.1 Pro
GDPval-AA
1844.2Claude Sonnet 5.5
1846.0Kimi K3.1 Pro
Finance Agent
58.1Claude Sonnet 5.5
58.6Kimi K3.1 Pro
Claude Sonnet 5.5
Input$2.00
Output$10.0
Workload$4.00
Context1M
Kimi K3.1 Pro
Input$2.00
Output$10.0
Workload$4.00
Context1M

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

More Claude Sonnet 5.5 and Kimi K3.1 Pro comparisons

Explore how Claude Sonnet 5.5 and Kimi K3.1 Pro 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.