What Is Claude Opus 5?

Claude Opus 5 is Anthropic's latest flagship model for complex reasoning, autonomous coding, and long-running agent tasks. Released on July 24, 2026, it is the most capable model in the Opus tier — Anthropic's premium line positioned between the frontier Fable/Mythos class and the value-oriented Sonnet and Haiku models.

Anthropic's current model hierarchy runs from top to bottom: Mythos 5 (restricted, for advanced research) → Fable 5 (most capable public model) → Opus 5 (near-frontier, half the price) → Sonnet 5 (value workhorse) → Haiku (speed and cost). Opus 5 sits in the sweet spot: it matches or exceeds Fable 5 on several key benchmarks — particularly agentic coding and novel reasoning — while costing half as much per token.

The launch came as Anthropic's fourth model release in under two months. Opus 5 is now the default model on Claude Max and the strongest model available on Claude Pro, meaning most paying subscribers receive the upgrade without changing a setting.

Key Features of Claude Opus 5

1M-Token Context Window

Opus 5 accepts up to 1 million tokens of input with up to 128,000 tokens of synchronous output — one of the largest context windows available in a managed API. In practice, this means you can pass entire codebases, lengthy legal documents, full research paper corpora, or multi-month email threads in a single request without chunking or retrieval workarounds. For agent workflows that accumulate long conversation histories and tool outputs, the 1M context window removes a meaningful architectural constraint.

Agentic Capabilities and Effort Control

Opus 5 is designed for long-running, multi-step tasks. Anthropic highlights a key behavioral improvement: the model verifies its own work and iterates until it succeeds, requiring fewer correction prompts from the user. In one documented example, the model wrote its own test suite, identified a failure, and looped back autonomously — behavior more aligned with a capable junior engineer than a chat completion endpoint.

A new effort toggle (low / medium / high) allows developers to trade thoroughness against token spend on a per-request basis. Routine tasks can run on low effort; complex multi-step analysis can run at max. This gives teams meaningful cost control without model-switching.

Coding Performance

Opus 5 posts 96.0% on SWE-bench Verified — effectively saturating the standard software engineering benchmark. On the harder SWE-bench Pro variant, it scores 79.2%, trailing Mythos 5 (80.3%) and Fable 5 (80.0%) by under a point. On Frontier-Bench v0.1, which measures end-to-end agentic coding in real repositories, Opus 5 actually leads the entire field at 43.3%, ahead of both Fable 5 (33.7%) and GPT-5.6 Sol (34.4%).

Opus 5 integrates with Claude Code and supports function calling, tool use, and multi-turn agentic loops for automated software development workflows.

Safety and Alignment

Anthropic describes Opus 5 as its most aligned model to date, with the lowest rates of deceptive behavior in its internal evaluations. It complies with Anthropic's Responsible Scaling Policy and has undergone red-teaming and adversarial testing. Notably, Anthropic maintains Opus 4.8 as a fallback model for requests where Opus 5's safety classifiers flag a concern — the two models are intended to complement, not replace, each other on safety-sensitive tasks.

Claude Opus 5 Benchmarks

Anthropic published a comprehensive benchmark suite at launch. These are the headline numbers — all scores are vendor-reported unless otherwise noted. Independent testing from MindStudio, Vellum, and Codersera largely corroborates the Anthropic figures, with minor variations by methodology.

The number that generates the most discussion is ARC-AGI-3 at 30.2% — roughly three times GPT-5.6 Sol's 7.8% and twenty times Opus 4.8's 1.5%. ARC-AGI-3 is specifically designed to resist memorization, testing genuinely novel problem-solving in interactive environments the model cannot have seen in training. A result this separated from competitors suggests a meaningful architectural change in how Opus 5 handles out-of-distribution reasoning, not just benchmark overfitting.

Claude Opus 5 Pricing

Opus 5 launched at the same token price as Opus 4.8 — making it a direct, cost-neutral upgrade for anyone already on the Opus tier. The "half the price" framing in most coverage refers to the comparison with Fable 5 ($10/$50 per million tokens), not a price cut relative to the previous Opus model.

No data retention requirements apply to general access — the same as Opus 4.8. For teams on zero-data-retention contracts, Opus 5 is a clean upgrade.

The practical cost comparison that matters most for production teams: on Frontier-Bench and OSWorld, Opus 5 needed fewer tokens and turns than Fable 5 to complete the same tasks, so the per-task cost advantage is larger than the per-token comparison alone suggests.

Claude Opus 5 vs GPT-5.6 Sol vs Claude Fable 5

Bottom line: For agentic coding and novel reasoning, Opus 5 is the current public leader. GPT-5.6 Sol remains competitive on cost-per-task for teams already invested in the OpenAI ecosystem — switching costs are real, and a 9-point Frontier-Bench lead doesn't automatically justify a migration. Fable 5 is still Anthropic's recommendation for the most advanced long-running autonomous work, particularly tasks with safety-sensitive dual-use potential.

How to Use Claude Opus 5 via AICC API

The fastest way to start using Claude Opus 5 — especially if you're already building with OpenAI's SDK — is through the AICC unified API. AICC gives you access to Claude Opus 5 and 300+ other models through a single API key with an OpenAI-compatible format. No code changes needed beyond swapping the base URL and key.

Python Example

The AICC API is fully OpenAI-compatible. If your codebase already uses the openai Python library, the only changes are base_url, api_key, and the model string. Feature parity is maintained: function calling, tool use, streaming, and the effort toggle all work through the AICC layer.

When to Use the Effort Toggle

Claude Opus 5 introduces a per-request effort level. Use it to manage cost vs. quality at the task level:

• Low effort — Quick classification, short summaries, simple Q&A. Fastest and cheapest.
• Medium effort — Default for most tasks. Document analysis, code review, multi-step reasoning with moderate complexity.
• High effort — Complex agent loops, novel problem-solving, large codebase analysis. Uses more tokens but produces the most thorough, verified output.

Frequently Asked Questions

Conclusion

Claude Opus 5 is the model most teams building with AI should default to right now. The benchmark profile is the strongest Anthropic has published for a mid-tier model — leading the field on agentic coding and novel reasoning, near the top on software engineering, and ahead of both Fable 5 and GPT-5.6 Sol on knowledge-work quality. The price hasn't moved from Opus 4.8, so there's no cost reason to stay on the older model.

The honest caveats: Fable 5 and Mythos 5 still lead on dual-use safety and specialized science tasks; GPT-5.6 Sol wins one coding benchmark outright; and benchmarks are always vendor-reported until independently replicated at scale. Run your own evaluation before committing.

For developers who want to access Claude Opus 5 without managing separate Anthropic, Bedrock, or Vertex credentials, AICC's unified API is the most practical path — OpenAI-compatible format, volume-based pricing savings, and a single integration point for every model you'll compare Opus 5 against.