How much does each one actually cost to run?
Input is a wash: $5/Mtok on both. Output is where they split, $25/Mtok for Opus 4.7 against $30/Mtok for GPT-5.5, a 20% premium on GPT-5.5.
Here's what that looks like on a realistic agent workload of 1M input tokens and 200K output tokens per day. Opus 4.7 runs $10/day, about $300/month. GPT-5.5 runs $11/day, about $330/month. A $30/month gap at this usage level. If your workload is output-heavy (long reports, generated documents), the gap widens; if it's input-heavy (huge prompts, short answers), it nearly disappears.
Both providers offer prompt caching, and at flagship prices caching is not optional. A well-cached agent loop routinely cuts effective input spend by half or more, which matters far more than the $5/Mtok output difference.
Which is better for agentic coding?
This is the tier you buy for hard, multi-step work, and it's where the models differentiate beyond the spec sheet. In our use, Opus 4.7 stays coherent deeper into long agentic sessions: it keeps track of what it already tried, and its tool calls degrade less as context fills. That reliability is the main reason to pay flagship prices at all.
GPT-5.5 is no slouch on code, and it has one concrete spec advantage: the same 128K output ceiling as Opus, plus a marginally larger context window (1.05M vs 1M tokens). Nobody will ever feel that context difference in practice. Both models take images and PDFs as input, both support reasoning, and both do structured tool calling.
What about ecosystem and lock-in?
By this point most teams are not choosing a model, they're choosing a stack. OpenAI's ecosystem is broader: more third-party tooling assumes an OpenAI-compatible API shape first. Anthropic's tooling is narrower but deep on exactly this tier's use case, long-running agents and coding.
The honest advice: if you're already running one of these providers in production, with caching, evals, and monitoring wired up, stay put unless you have a measured quality problem. Migrating a production agent stack to save $5/Mtok on output is a bad trade.
Which should you pick?
Pick Claude Opus 4.7 if:
- Your workload is long agentic coding or multi-file refactors
- Session coherence over hours matters more than raw speed
- You're already on Anthropic's SDK and caching
Pick GPT-5.5 if:
- Your stack is built around OpenAI-compatible tooling
- You need the broadest third-party integration surface
- Your tasks are shorter and benefit from the wider ecosystem
Either way, run your own eval set before committing. At $300+/month per seat-equivalent of traffic, an afternoon of benchmarking pays for itself immediately.