LLM Comparison

Kimi K3 vs Grok 4.7: benchmark scores, pricing & comparison.

Side-by-side Kimi K3 vs Grok 4.7 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 #16 vs #21AskClash overall scores 63.9 vs 61.7.
Pricing $3.00/$15.0 vs $2.00/$6.00Input and output token prices per 1M tokens when published.
Open Weight vs ProprietaryMoonshot AI vs xAI.

Kimi K3 vs Grok 4.7 benchmark comparison

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

MetricKimi K3Grok 4.7
Overall Score63.961.7
Leaderboard Rank#16#21
ACB57.766.4
RWT8.0
Coding Agent Index51.956.0
HLE43.543.1
GPQA93.5
SWE-Atlas66.163.0
Terminal-Bench88.376.0
DeepSWE68.573.0
GDPval-AA1668.01695.2
MCP Atlas84.2
Finance Agent54.449.2
CharXiv84.8
MMMU-Pro81.6
Input Price (per 1M tokens)$3.00$2.00
Output Price (per 1M tokens)$15.0$6.00
Context Window1M500K
Benchmarks Published139

Kimi K3 vs Grok 4.7 head-to-head charts

Kimi K3 leads 5 and Grok 4.7 leads 4 of 9 shared benchmarks. Grok 4.7 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Kimi K3Grok 4.7
Overall
63.9Kimi K3
61.7Grok 4.7
ACB
57.7Kimi K3
66.4Grok 4.7
Coding Agent Index
51.9Kimi K3
56.0Grok 4.7
HLE
43.5Kimi K3
43.1Grok 4.7
SWE-Atlas
66.1Kimi K3
63.0Grok 4.7
Terminal-Bench
88.3Kimi K3
76.0Grok 4.7
DeepSWE
68.5Kimi K3
73.0Grok 4.7
GDPval-AA
1668.0Kimi K3
1695.2Grok 4.7
Finance Agent
54.4Kimi K3
49.2Grok 4.7
Kimi K3
Input$3.00
Output$15.0
Workload$6.00
Context1M
Grok 4.7
Input$2.00
Output$6.00
Workload$3.20
Context500K

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

More Kimi K3 and Grok 4.7 comparisons

Explore how Kimi K3 and Grok 4.7 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.