LLM Comparison

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

Side-by-side Claude Opus 4.8 vs Kimi K3 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 #4 vs #6AskClash overall scores 77.1 vs 76.8.
Pricing $5.00/$25.0 vs $3.00/$15.0Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightAnthropic vs Moonshot AI.

Claude Opus 4.8 vs Kimi K3 benchmark comparison

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

MetricClaude Opus 4.8Kimi K3
Overall Score77.176.8
Leaderboard Rank#4#6
RWT9.08.0
Coding Agent Index72.5
HLE57.943.5
GPQA93.693.5
IFEval62.2
SWE-bench88.6
SWE-Pro69.2
SWE-Atlas82.5
Terminal-Bench74.688.3
DeepSWE59.068.5
OSWorld83.4
MCP Atlas82.284.2
Finance Agent53.954.4
CharXiv89.984.8
MMMU-Pro81.6
ARC-AGI 272.1
Tau294.4
Input Price (per 1M tokens)$5.00$3.00
Output Price (per 1M tokens)$25.0$15.0
Context Window1M1M
Benchmarks Published1811

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

Claude Opus 4.8 leads 5 and Kimi K3 leads 4 of 9 shared benchmarks. Kimi K3 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Opus 4.8Kimi K3
Overall
77.1Claude Opus 4.8
76.8Kimi K3
RWT
9.0Claude Opus 4.8
8.0Kimi K3
HLE
57.9Claude Opus 4.8
43.5Kimi K3
GPQA
93.6Claude Opus 4.8
93.5Kimi K3
Terminal-Bench
74.6Claude Opus 4.8
88.3Kimi K3
DeepSWE
59.0Claude Opus 4.8
68.5Kimi K3
MCP Atlas
82.2Claude Opus 4.8
84.2Kimi K3
Finance Agent
53.9Claude Opus 4.8
54.4Kimi K3
CharXiv
89.9Claude Opus 4.8
84.8Kimi K3
Claude Opus 4.8
Input$5.00
Output$25.0
Workload$10
Context1M
Kimi K3
Input$3.00
Output$15.0
Workload$6.00
Context1M

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

More Claude Opus 4.8 and Kimi K3 comparisons

Explore how Claude Opus 4.8 and Kimi K3 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.