LLM Comparison

Grok 4.6 vs Grok 4.5: benchmark scores, pricing & comparison.

Side-by-side Grok 4.6 vs Grok 4.5 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 #5 vs #11AskClash overall scores 76.6 vs 69.7.
Pricing $2.00/$6.00 vs $2.00/$6.00Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryxAI vs xAI.

Grok 4.6 vs Grok 4.5 benchmark comparison

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

MetricGrok 4.6Grok 4.5
Overall Score76.669.7
Leaderboard Rank#5#11
RWT9.09.0
Coding Agent Index76.476.4
HLE40.340.3
GPQA94.993.1
SWE-Pro64.764.7
SWE-Atlas83.983.9
Terminal-Bench88.483.3
DeepSWE65.9
Finance Agent48.348.3
MMMU-Pro80.480.4
ARC-AGI 252.652.6
Input Price (per 1M tokens)$2.00$2.00
Output Price (per 1M tokens)$6.00$6.00
Context Window500K500K
Benchmarks Published1312

Grok 4.6 vs Grok 4.5 head-to-head charts

Grok 4.6 leads 3 and Grok 4.5 leads 0 of 11 shared benchmarks. Charts show only benchmarks both models publish.

Grok 4.6Grok 4.5
Overall
76.6Grok 4.6
69.7Grok 4.5
RWT
9.0Grok 4.6
9.0Grok 4.5
Coding Agent Index
76.4Grok 4.6
76.4Grok 4.5
HLE
40.3Grok 4.6
40.3Grok 4.5
GPQA
94.9Grok 4.6
93.1Grok 4.5
SWE-Pro
64.7Grok 4.6
64.7Grok 4.5
SWE-Atlas
83.9Grok 4.6
83.9Grok 4.5
Terminal-Bench
88.4Grok 4.6
83.3Grok 4.5
Finance Agent
48.3Grok 4.6
48.3Grok 4.5
MMMU-Pro
80.4Grok 4.6
80.4Grok 4.5
ARC-AGI 2
52.6Grok 4.6
52.6Grok 4.5
Grok 4.6
Input$2.00
Output$6.00
Workload$3.20
Context500K
Grok 4.5
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 Grok 4.6 and Grok 4.5 comparisons

Explore how Grok 4.6 and Grok 4.5 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.