Capability · Comparison
Claude Opus 4.7 vs OpenAI o3
A comparison of two very different frontier bets: Claude Opus 4.7 — a general-purpose model tuned hard for agents and coding — and OpenAI o3, a reasoning-first model built to think for minutes before answering. The choice is rarely about raw intelligence; it's about whether your workload benefits from tools-in-the-loop or from pure deliberation.
Side-by-side
| Criterion | Claude Opus 4.7 | OpenAI o3 |
|---|---|---|
| Context window | 1,000,000 tokens | 200,000 tokens |
| Coding (SWE-bench Verified) As of 2026-04. | ≈75% | ≈70% |
| Competition math (AIME, olympiads) | Strong | Very strong — near-SOTA |
| Tool use in long loops | Industry-leading | Workable but not o3's focus |
| Latency | Moderate | Slow — 10s to minutes of thinking |
| Pricing ($/M input) As of 2026-04; o3 charges separately for reasoning tokens. | $15 | $2 |
| Pricing ($/M output) o3 reasoning tokens billed as output. | $75 | $8 |
| Multimodal | Text, vision | Text, vision |
| Best for | Agents, code, long-horizon tasks | Verifiable deliberation tasks |
Verdict
These are different shapes of model, not directly comparable on a leaderboard. Opus 4.7 is the right pick when your workload looks like an agent — many short-to-medium steps, heavy tool use, large context. o3 is the right pick when your workload looks like a proof — one or a few calls, verifiable answer, willingness to wait. On hard math and olympiad-style reasoning o3 remains the strongest publicly available option; on production agent work Opus wins.
When to choose each
Choose Claude Opus 4.7 if…
- You're building a coding agent or long-horizon tool-using system.
- You need 500k+ tokens of context regularly.
- You can't tolerate minute-level latency per step.
- You want predictable output pricing (no reasoning-token surprises).
Choose OpenAI o3 if…
- You're working on hard math, olympiad-style problems, or formal reasoning.
- You need best-in-class single-shot deliberation on verifiable tasks.
- Latency doesn't matter — the user can wait.
- You're already embedded in OpenAI infra.
Frequently asked questions
Is o3 smarter than Claude Opus 4.7?
On a single hard reasoning problem with verifiable answer, often yes. On a 50-step agentic task with tools, Opus 4.7 usually wins because reliability and tool use matter more than raw deliberation.
Can o3 drive an agent?
It can, but latency and cost make it awkward as the only model. Common pattern: Opus or Sonnet for the agent loop, call o3 only on the specific hard sub-problem that needs deliberation.
Which is cheaper?
Per input token, o3 is much cheaper. Per task, o3 can be more expensive because it emits huge numbers of reasoning tokens billed as output. Profile your workload before assuming.
Sources
- Anthropic — Models overview — accessed 2026-04-20
- OpenAI — Models — accessed 2026-04-20