Agentic coding has become the primary arena where frontier models differentiate themselves. As of early July 2026, Anthropic’s Claude Opus 5 and OpenAI’s GPT-5.6 Sol sit at the top of the leaderboard but optimize for different things: Opus 5 leads on broad intelligence rankings, while GPT-5.6 Sol has taken the lead on coding-agent-specific benchmarks. Choosing between them depends on whether your workflow values raw general capability, terminal-driven task completion, cost per task, or immediate availability.
| Model / Configuration | Artificial Analysis Intelligence Index | BenchAlign v5.2 | Coding Agent Index | TerminalBench 2.1 | List Pricing (per 1M tokens) |
|---|---|---|---|---|---|
| Claude Opus 5 (Max Effort) | 61 (#1) | 82.81 (#2) | Not reported | Not reported | Not stated |
| Claude Opus 5 (Xhigh Effort) | 60 (#2) | — | — | — | Not stated |
| Claude Fable 5 (Max Effort) | 60 (#3) | 82.75 (#3) | Not reported | 84.3% | Not stated |
| GPT-5.6 Sol (max) | 59 (#4) | 81.39 (#4) | 80 (#1) | 88.8% | $5 / $30 |
General intelligence: Opus 5 holds the top spot
On aggregate intelligence benchmarks, Claude Opus 5 is ahead. It scores 61 on the Artificial Analysis Intelligence Index, two points above GPT-5.6 Sol (max) at 59, and ranks first overall. The Xhigh Effort variant ties Claude Fable 5 at 60. BenchAlign v5.2 tells a similar story: Opus 5 scores 82.81 versus 81.39 for GPT-5.6 Sol. If your agentic workflow mixes coding with research, analysis, document synthesis, or open-ended reasoning, Opus 5’s higher general score is a meaningful signal.
That said, the gap is narrow. GPT-5.6 Sol is one point behind Fable 5 and only two points behind Opus 5 on the Intelligence Index, while Source 2 notes it achieves that at roughly one third of Fable 5’s per-task cost in that benchmark. So the headline “Opus 5 wins on general intelligence” comes with a caveat: Sol is competitive at a lower per-task spend.
Agentic coding: GPT-5.6 Sol takes the lead
Where the comparison flips is coding-specific agentic evaluation. The Artificial Analysis Coding Agent Index combines three frontier coding evaluations—DeepSWE, Terminal-Bench v2, and SWE-Atlas-QnA—under agentic harnesses. GPT-5.6 Sol (max) scores 80 and leads all three sub-evaluations, tying Grok 4.5 on SWE-Atlas-QnA. This is the strongest direct evidence that Sol is currently the best model for multi-step coding agents.
TerminalBench 2.1 reinforces that conclusion. GPT-5.6 Sol (max) scores 88.8%, clearing Claude Mythos 5 (88.0%) and