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Anthropic · Claude Opus 5 · July 2026

Claude Opus 5 — Anthropic’s strongest model for coding and agent work

Q: Is the name here the same as in Agent?

Yes. Choosing Claude Opus 5 in Agent is the model this page describes.

Q: What are the key specs?

1M tokens of context, 128K max output, deep thinking built in, tunable depth tiers. Plan long jobs against these ceilings.

Q: What changes when moving from Claude Opus 4.8?

Claude Opus 5 has deep thinking built in, so it spends more steps organizing a path before answering. Extra repeated verification prompts can usually be simplified; leave enough output room for thinking and text.

Q: How do I choose vs Claude Fable 5 and GPT-5.6 Sol?

Long-horizon coding, multi-step agents, and knowledge work: prefer Claude Opus 5. Top-of-Claude capability with higher load: Claude Fable 5. Team already on OpenAI’s depth stack: GPT-5.6 Sol.

Q: Can outputs be used commercially?

Yes. Content you create on iMini has commercial use rights under the product terms.

Million-token context
Extra-long single replies
Deep thinking built in
Tunable depth tiers

What is Claude Opus 5?

Claude Opus 5 is Anthropic’s Opus flagship, released in July 2026. It’s built for work you can’t half-finish: changing features in a large repo, hunting root causes, and driving tools step by step until the job is done. Deep thinking is built in; context and output are sized for long jobs; tune depth when you need more or less. Versus Claude Opus 4.8, long-horizon coding, multi-step tools, and knowledge work are steadier, with fewer half-finished patches. On iMini Agent, pick Claude Opus 5 to use it.

Vendor: Anthropic
Released: July 2026
Context: 1M tokens
Max output: 128K tokens
Deep thinking: On by design · tunable
Best as: Primary for long-horizon coding & agents

What’s new versus Claude Opus 4.8

Out-of-the-box behavior, long-horizon completion, context, and multi-step tools—the four changes to understand before making it your everyday primary.

Deep thinking on out of the box

Deep thinking is built in: it organizes constraints and a path before acting. Tune depth when you need more or less. Complex jobs see fewer “write first, discover problems later” failures.

Higher long-horizon coding completion

On cross-file features, large refactors, and root-cause work, it leaves fewer unfinished changes and fewer symptom-only fixes—better as an everyday engineering primary.

Steadier progress under long context

Long specs, multi-turn history, and tool traces can stay in one conversation. Large-repo changes and long migration plans don’t need to be fragmented early.

More complete multi-step tool workflows

On jobs that call tools repeatedly and finish end to end, it holds goals and abort conditions better—fewer mid-run drifts or half stops—suited as an Agent primary.

Official evaluations and alignment audits

Evaluations and alignment results Anthropic published with Claude Opus 5—covering software engineering, knowledge work, business automation, and behavioral audits.

Claude Opus 5 multi-task evaluation overview — Multi-task overview. Putting software engineering, knowledge work, business automation, and computer use on one board shows where Claude Opus 5 sits versus Claude Opus 4.8, Claude Fable 5, and peers—not a single score in isolation.

Frontier-Bench: agent coding performance by depth tier — Frontier-Bench focuses on agent coding. The chart shows how scores move with depth: Claude Opus 5 clearly beats Claude Opus 4.8, and it’s a core signal for long-horizon coding, terminal, and tool-collaboration work.

CursorBench: IDE coding performance by depth tier — CursorBench is closer to everyday IDE coding and agent collaboration. Scores vary by depth; at the top tier it approaches Claude Fable 5—useful when editing a repo and making multi-step changes inside an editor.

GDPval-AA: knowledge-work performance by depth tier — GDPval-AA measures real knowledge-work performance; the curve rises with depth. It covers research synthesis, table work, and numeric reasoning—watching whether Claude Opus 5 stays checkable under long materials and hard constraints.

AutomationBench: end-to-end business task pass rate — AutomationBench measures whether end-to-end business workflows finish. Claude Opus 5 sits near the front of the pack; even at lower depth it keeps high completion—an important reference for multi-step business agents.

ARC-AGI-3: novel problem-solving performance — ARC-AGI-3 tests solving under uncommon constraints and novel problems. Claude Opus 5 sits well above on-screen peers—still able to decompose and keep reasoning when no ready template exists.

Behavioral alignment audit: misalignment score — Behavioral alignment audits count deception, induced misuse, and related misalignment—lower is better. Claude Opus 5 scores 2.3, below recent same-family peers—a production-primary signal alongside capability scores.

OSS-Fuzz: vulnerability discovery vs exploit generation — OSS-Fuzz separates finding vulnerabilities from writing usable exploits. Claude Opus 5 is close to Mythos 5 on discovery but clearly weaker on exploit generation—keep those two measures separate in security workflows.

Three common workflows

Claude Opus 5 fits work that must keep moving and end with a deliverable result.

Repo changes & code review

For cross-file feature work, hard-to-reproduce bugs, and evidence-based PR review. The point isn’t a fast opinion—it’s clear root cause, blast radius, and verification so merges don’t bounce back.

Research synthesis & decision memos

For collapsing long materials into a one-page decision: the problem, options, recommendation, and risks. Suited to knowledge work with tables, numbers, and explicit constraints.

Multi-step agent jobs

For workflows that call tools repeatedly and advance step by step to a result. Agree inputs, done criteria, and stop conditions per step so the job can run end to end.

How to choose vs Claude Fable 5 and GPT-5.6 Sol

All three are current flagships. The differences are out-of-the-box depth, product stack, and which jobs you run most.

Dimension	Claude Opus 5	Claude Fable 5	GPT-5.6 Sol
Context	1M tokens	Top Claude long-context tier	OpenAI Sol flagship context
Reasoning	Deep thinking built in, tunable	Top of the Claude capability ladder	OpenAI maximum-depth tier
Coding / agents	Everyday primary for long-horizon coding & multi-step agents	When you need top-of-Claude capability	Better when the team is bound to OpenAI’s depth stack
Long tool runs	Stronger goal holding and completion	Heavier, top-tier agent scenarios	Available on iMini Agent; stack leans OpenAI
Speed posture	Completion quality and stability first	Heavier; cost and latency usually higher	Maximum depth first
Prefer when	New long-horizon coding, multi-step agents, knowledge work	Top-of-Claude capability and you can accept higher load	Org standard is already OpenAI Sol

Using Claude Opus 5 on iMini

Free quota, model naming, key specs, and how it differs from Claude Fable 5 and GPT-5.6 Sol.

Can I try it free?

Is the name here the same as in Agent?

What are the key specs?

What changes when moving from Claude Opus 4.8?

How do I choose vs Claude Fable 5 and GPT-5.6 Sol?

Can outputs be used commercially?

Use Claude Opus 5 free on iMini Agent

Million-token context, deep thinking built in, tunable depth tiers.

Open Claude Opus 5

No Anthropic API key required.