LLM Comparison

GPT-5.6 Sol vs Claude Sonnet 5: benchmark scores, pricing & comparison.

Side-by-side GPT-5.6 Sol vs Claude Sonnet 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 #2 vs #9AskClash overall scores 85.6 vs 76.2.
Pricing $5.00/$30.0 vs $3.00/$15.0Input and output token prices per 1M tokens when published.
Proprietary vs ProprietaryOpenAI vs Anthropic.

GPT-5.6 Sol vs Claude Sonnet 5 benchmark comparison

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

MetricGPT-5.6 SolClaude Sonnet 5
Overall Score85.676.2
Leaderboard Rank#2#9
RWT9.58.5
Coding Agent Index80.0
HLE47.257.4
GPQA94.191.1
SWE-bench85.2
SWE-Pro64.663.2
SWE-Atlas84.0
Terminal-Bench88.880.4
DeepSWE72.753.8
OSWorld81.2
Finance Agent53.8
CharXiv88.3
MMMU-Pro83.077.3
ARC-AGI 292.5
Tau285.1
MRCR91.5
Input Price (per 1M tokens)$5.00$3.00
Output Price (per 1M tokens)$30.0$15.0
Context Window1M1M
Benchmarks Published1411

GPT-5.6 Sol vs Claude Sonnet 5 head-to-head charts

GPT-5.6 Sol leads 7 and Claude Sonnet 5 leads 1 of 8 shared benchmarks. Claude Sonnet 5 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-5.6 SolClaude Sonnet 5
Overall
85.6GPT-5.6 Sol
76.2Claude Sonnet 5
RWT
9.5GPT-5.6 Sol
8.5Claude Sonnet 5
HLE
47.2GPT-5.6 Sol
57.4Claude Sonnet 5
GPQA
94.1GPT-5.6 Sol
91.1Claude Sonnet 5
SWE-Pro
64.6GPT-5.6 Sol
63.2Claude Sonnet 5
Terminal-Bench
88.8GPT-5.6 Sol
80.4Claude Sonnet 5
DeepSWE
72.7GPT-5.6 Sol
53.8Claude Sonnet 5
MMMU-Pro
83.0GPT-5.6 Sol
77.3Claude Sonnet 5
GPT-5.6 Sol
Input$5.00
Output$30.0
Workload$11
Context1M
Claude Sonnet 5
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 GPT-5.6 Sol and Claude Sonnet 5 comparisons

Explore how GPT-5.6 Sol and Claude Sonnet 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.