LLM Comparison

Grok 4.6 vs Kimi K3: benchmark scores, pricing & comparison.

Side-by-side Grok 4.6 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 #5AskClash overall scores 78.3 vs 77.7.
Pricing $2.00/$6.00 vs $3.00/$15.0Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightxAI vs Moonshot AI.

Grok 4.6 vs Kimi K3 benchmark comparison

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

MetricGrok 4.6Kimi K3
Overall Score78.377.7
Leaderboard Rank#4#5
ACB69.057.7
RWT9.08.0
Coding Agent Index76.4
HLE40.343.5
GPQA94.993.5
SWE-Pro64.7
SWE-Atlas83.9
Terminal-Bench88.488.3
DeepSWE65.968.5
MCP Atlas84.2
Finance Agent48.354.4
CharXiv84.8
MMMU-Pro80.481.6
ARC-AGI 252.6
Input Price (per 1M tokens)$2.00$3.00
Output Price (per 1M tokens)$6.00$15.0
Context Window500K1M
Benchmarks Published1311

Grok 4.6 vs Kimi K3 head-to-head charts

Grok 4.6 leads 5 and Kimi K3 leads 4 of 9 shared benchmarks. Grok 4.6 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Grok 4.6Kimi K3
Overall
78.3Grok 4.6
77.7Kimi K3
ACB
69.0Grok 4.6
57.7Kimi K3
RWT
9.0Grok 4.6
8.0Kimi K3
HLE
40.3Grok 4.6
43.5Kimi K3
GPQA
94.9Grok 4.6
93.5Kimi K3
Terminal-Bench
88.4Grok 4.6
88.3Kimi K3
DeepSWE
65.9Grok 4.6
68.5Kimi K3
Finance Agent
48.3Grok 4.6
54.4Kimi K3
MMMU-Pro
80.4Grok 4.6
81.6Kimi K3
Grok 4.6
Input$2.00
Output$6.00
Workload$3.20
Context500K
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 Grok 4.6 and Kimi K3 comparisons

Explore how Grok 4.6 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.