Claude Sonnet 5.5 vs GPT-6.1 Sol: Which is Better in 2026?

Claude Sonnet 5.5 (Anthropic) and GPT-6.1 Sol (OpenAI) are both frontier-class models competing for the same developer and enterprise audience in 2026. This page compiles benchmarks, task grades, and practical guidance to help you decide which model fits your workflow.

Last updated: October 2, 2026

Quick Verdict

Across the benchmarks where both models have published scores, Claude Sonnet 5.5 leads on 1 of 3 shared evaluation tasks. GPT-6.1 Sol remains competitive, particularly in areas aligned with its training focus. For general-purpose quality, Claude Sonnet 5.5 currently holds an edge — but the right choice depends heavily on your specific use case, budget, and whether you need API access or self-hosted deployment.

Side-by-Side Comparison

The table below covers every benchmark for which at least one model has a published score. Higher scores are better on all metrics except where noted. Bold values indicate the higher score in each row.

Benchmark Claude Sonnet 5.5 GPT-6.1 Sol Winner
GPQA Diamond 95.6 95.4 Claude Sonnet 5.5
AIME 2024–25 (Epoch AI) 100 100 Tie
SimpleQA Verified 46.5 73.9 GPT-6.1 Sol

Task Performance

Per-task grades are sourced from the id8 LLM leaderboard evaluations. Each grade reflects observed output quality across real-world prompts in that category. A dash (—) means grades are not yet published for that model.

Task Claude Sonnet 5.5 GPT-6.1 Sol
Coding S S
Math S S
Content Writing S S
Reasoning S S
Studying S S
Chat / Conversation S S
Summarization S S
Agents / Tool Use S S
Vision / Multimodal S S
Data Analysis A A
Hindi / Multilingual B B
Interview Prep S S
overall S S
tool_calling S S
long_context A A

Grade scale: S = Exceptional   A = Strong   B = Good   C = Fair   D = Weak

Key Differences

Which Should You Choose?

Choose Claude Sonnet 5.5 if your primary use cases involve overall, Coding, Math. Claude Sonnet 5.5 scores highly on these tasks and is especially well-suited for teams that need consistent, high-quality outputs at scale through Anthropic's API.

Choose GPT-6.1 Sol if your work centres on overall, Coding, Math. It offers a strong value proposition for those use cases.

Still unsure? The LLM Leaderboard lets you sort and filter models by benchmark — useful for narrowing down the right model for a specific workload.

Explore Further

Use these tools to dig deeper into either model's hardware requirements and leaderboard ranking.

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