LLM Comparison

Claude Opus 4.8 vs GPT-6 Sol: benchmark scores, pricing & comparison.

Side-by-side Claude Opus 4.8 vs GPT-6 Sol 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 #8 vs #30AskClash overall scores 67.6 vs 56.6.
Pricing $5.00/$25.0 vs $2.00/$10.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryAnthropic vs OpenAI.

Claude Opus 4.8 vs GPT-6 Sol benchmark comparison

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

MetricClaude Opus 4.8GPT-6 Sol
Overall Score67.656.6
Leaderboard Rank#8#30
ACB60.155.8
RWT9.0
Coding Agent Index72.5
HLE57.947.9
GPQA93.6
IFEval62.2
SWE-bench88.6
SWE-Pro69.2
SWE-Atlas82.5
Terminal-Bench74.6
DeepSWE59.068.8
GDPval-AA1889.81486.9
OSWorld83.4
MCP Atlas82.2
Finance Agent53.9
CharXiv89.9
MMMU-Pro83.3
ARC-AGI 272.1
Tau294.4
Input Price (per 1M tokens)$5.00$2.00
Output Price (per 1M tokens)$25.0$10.0
Context Window1M1.05M
Benchmarks Published186

Claude Opus 4.8 vs GPT-6 Sol head-to-head charts

Claude Opus 4.8 leads 4 and GPT-6 Sol leads 1 of 5 shared benchmarks. GPT-6 Sol is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

Claude Opus 4.8GPT-6 Sol
Overall
67.6Claude Opus 4.8
56.6GPT-6 Sol
ACB
60.1Claude Opus 4.8
55.8GPT-6 Sol
HLE
57.9Claude Opus 4.8
47.9GPT-6 Sol
DeepSWE
59.0Claude Opus 4.8
68.8GPT-6 Sol
GDPval-AA
1889.8Claude Opus 4.8
1486.9GPT-6 Sol
Claude Opus 4.8
Input$5.00
Output$25.0
Workload$10
Context1M
GPT-6 Sol
Input$2.00
Output$10.0
Workload$4.00
Context1.05M

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

More Claude Opus 4.8 and GPT-6 Sol comparisons

Explore how Claude Opus 4.8 and GPT-6 Sol 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.