LLM Comparison

Claude Opus 4.8 vs Grok 4.5: benchmark scores, pricing & comparison.

Side-by-side Claude Opus 4.8 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 #4 vs #5AskClash overall scores 80.4 vs 78.7.
Pricing $5.00/$25.0 vs $2.00/$6.00Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryAnthropic vs xAI.

Claude Opus 4.8 vs Grok 4.5 benchmark comparison

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

MetricClaude Opus 4.8Grok 4.5
Overall Score80.478.7
Leaderboard Rank#4#5
RWT9.09.0
Coding Agent Index72.576.4
HLE57.940.3
GPQA93.693.1
IFEval62.2
SWE-bench88.6
SWE-Pro69.264.7
SWE-Atlas82.583.9
Terminal-Bench74.683.3
DeepSWE59.0
OSWorld83.4
MCP Atlas82.2
Finance Agent53.9
CharXiv89.9
MMMU-Pro80.4
ARC-AGI 272.1
Tau294.4
Input Price (per 1M tokens)$5.00$2.00
Output Price (per 1M tokens)$25.0$6.00
Context Window1M500K
Benchmarks Published179

Claude Opus 4.8 vs Grok 4.5 head-to-head charts

Claude Opus 4.8 leads 4 and Grok 4.5 leads 3 of 8 shared benchmarks. Grok 4.5 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Opus 4.8Grok 4.5
Overall
80.4Claude Opus 4.8
78.7Grok 4.5
RWT
9.0Claude Opus 4.8
9.0Grok 4.5
Coding Agent Index
72.5Claude Opus 4.8
76.4Grok 4.5
HLE
57.9Claude Opus 4.8
40.3Grok 4.5
GPQA
93.6Claude Opus 4.8
93.1Grok 4.5
SWE-Pro
69.2Claude Opus 4.8
64.7Grok 4.5
SWE-Atlas
82.5Claude Opus 4.8
83.9Grok 4.5
Terminal-Bench
74.6Claude Opus 4.8
83.3Grok 4.5
Claude Opus 4.8
Input$5.00
Output$25.0
Workload$10
Context1M
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 Claude Opus 4.8 and Grok 4.5 comparisons

Explore how Claude Opus 4.8 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.