LLM Comparison

Kimi K3 vs Claude Opus 4.8: benchmark scores, pricing & comparison.

Side-by-side Kimi K3 vs Claude Opus 4.8 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 #3 vs #4AskClash overall scores 82.3 vs 80.2.
Pricing $3.00/$15.0 vs $5.00/$25.0Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryMoonshot AI vs Anthropic.

Kimi K3 vs Claude Opus 4.8 benchmark comparison

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

MetricKimi K3Claude Opus 4.8
Overall Score82.380.2
Leaderboard Rank#3#4
RWT9.0
Coding Agent Index72.5
HLE43.557.9
GPQA93.593.6
IFEval62.2
SWE-bench88.6
SWE-Pro69.2
SWE-Atlas82.5
Terminal-Bench88.374.6
DeepSWE67.559.0
OSWorld83.4
MCP Atlas84.282.2
Finance Agent53.9
CharXiv84.889.9
MMMU-Pro81.6
ARC-AGI 272.1
Tau294.4
Input Price (per 1M tokens)$3.00$5.00
Output Price (per 1M tokens)$15.0$25.0
Context Window1M1M
Benchmarks Published917

Kimi K3 vs Claude Opus 4.8 head-to-head charts

Kimi K3 leads 4 and Claude Opus 4.8 leads 3 of 7 shared benchmarks. Kimi K3 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Kimi K3Claude Opus 4.8
Overall
82.3Kimi K3
80.2Claude Opus 4.8
HLE
43.5Kimi K3
57.9Claude Opus 4.8
GPQA
93.5Kimi K3
93.6Claude Opus 4.8
Terminal-Bench
88.3Kimi K3
74.6Claude Opus 4.8
DeepSWE
67.5Kimi K3
59.0Claude Opus 4.8
MCP Atlas
84.2Kimi K3
82.2Claude Opus 4.8
CharXiv
84.8Kimi K3
89.9Claude Opus 4.8
Kimi K3
Input$3.00
Output$15.0
Workload$6.00
Context1M
Claude Opus 4.8
Input$5.00
Output$25.0
Workload$10
Context1M

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

More Kimi K3 and Claude Opus 4.8 comparisons

Explore how Kimi K3 and Claude Opus 4.8 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.