Today, Anthropic released Claude Opus 5. It replaces Claude Opus 4.8 as the Opus-tier flagship. Pricing is unchanged at $5 per million input tokens and $25 per million output tokens.
The Anthropic team positions Opus 5 as approaching the intelligence of Claude Fable 5 at half the price. It is now the default model on Claude Max and the strongest model on Claude Pro.
What actually changed at the API level
Three changes are quite important before any benchmark does:
- Thinking is on by default. On Opus 4.8, requests ran without thinking unless you set
thinking: {"type": "adaptive"}. On Opus 5 the same request thinks, and the effort parameter controls depth. Becausemax_tokenscaps thinking plus response text, existing values need review. - There is a breaking change. Setting
thinking: {"type": "disabled"}with effortxhighormaxnow returns a 400 error. The restriction is enforced per request. You either cap effort athighor drop thethinkingfield. - Anthropic tells developers to delete their verification prompts. Instructions like “include a final verification step” now cause over-verification, because the model already verifies its own work. The Opus 5 prompting guide covers the tuning patterns.
The model ID is claude-opus-5. Context is 1M tokens as both default and maximum, with no smaller variant. Maximum output is 128k tokens on the synchronous Messages API. The Message Batches API reaches 300k with the output-300k-2026-03-24 beta header. The minimum cacheable prompt drops to 512 tokens, down from 1,024.
Coding and agentic results
On FrontierBench v0.1, a 74-task successor to Terminal-Bench 2.1, Opus 5 scored 43.3% at max effort. Opus 4.8 scored 18.7%. Fable 5 reached 33.7% and GPT-5.6 Sol reached 37.5%. At xhigh effort Opus 5 reaches 44.4% mean reward, its best result.
One detail from that run is worth noting. Opus 5 safety classifiers flagged and refused 5% of API calls, across 4% of trials. Fable 5 classifiers flagged 42% of calls across 26% of trials.
Opus 5 scored 96.0% on SWE-bench Verified and 79.2% on SWE-bench Pro. Fable 5 still edges it on Pro at 80.0%. On SWE-bench Multimodal the jump is larger, from 38.4% to 59.4%.
The agentic numbers are the clearest wins. Opus 5 reached 70.57% on OSWorld 2.0 against 55.7% for Opus 4.8. On Zapier AutomationBench it scored 26.0%, against 17.0% for Opus 4.8 and 17.4% for Fable 5. At medium effort it still scores 24% at $0.89 per task.
On Artificial Analysis GDPval-AA v2, Opus 5 takes the top two leaderboard spots at ELO 1861 and 1827. The xhigh setting beats every other model while using 25% fewer output tokens than max.
Reasoning, and the ARC-AGI-3 result
Anthropic prompted Opus 5 on all six IMO 2026 problems without tools or an agent harness. A three-model judge panel scored all 24 generated solutions correct. Human experts independently graded one pre-specified solution per problem at 7/7. The final 42/42 is gold-medal level, above the 29/42 cutoff.
The ARC Prize Foundation reports a verified 30.16% on ARC-AGI-3 at high effort. That is roughly four times the best previously reported leaderboard score. GPT-5.6 Sol reached 7.78% and Opus 4.8 reached 1.52%. Opus 5 results at max effort were unavailable at release.
On Humanity’s Last Exam, Opus 5 scored 56.3% without tools and 64.7% with them.
The multimodal section carries a practical lesson. Agentic tool use scales test-time compute more cost-effectively than adaptive thinking alone.
On Chartography, Opus 5 scored 29.6% without tools and 83.0% with a container and an image-cropping tool. On BenchCAD Vision2Code, voxel IoU moves from 0.366 to 0.821. With tools, that beats Claude Mythos 5 at 0.678 by a wide margin.
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