> ## Documentation Index
> Fetch the complete documentation index at: https://documentation.deepmask.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Opus (4.6, 4.5)

> Claude Opus 4.5 and 4.6 from Anthropic. Up to 91.3% GPQA, 1M context, adaptive reasoning. Best for demanding coding, research, and agents.

The Opus family represents the ceiling of Anthropic's model intelligence within DeepMask. Both Opus 4.5 and Opus 4.6 are designed for the most demanding agentic, research, and software engineering tasks — where accuracy, long-horizon coherence, and the ability to handle ambiguity without losing goal-state are non-negotiable. If your task is complex, high-stakes, and requires sustained autonomous effort, Opus is the right choice.

## About Opus 4.5 and Opus 4.6

**Opus 4.5** is Anthropic's heavyweight frontier model, optimized for heavy-duty agentic workflows, complex software engineering, and deep research. It introduces a dynamic "Effort Control" parameter so you can minimize token spend on standard tasks or maximize reasoning depth for difficult problems — with state-of-the-art results at GPQA Diamond 88.9%. It handles context windows up to 500K tokens and excels at 3D visualization, financial modeling, and sustained autonomous coding sessions.

**Opus 4.6** (released February 4, 2026) takes the series further with "Adaptive Thinking" toggles across four effort levels (Low, Medium, High, Max), "Context Compaction" for near-infinite agent sessions, and native parallel sub-agent orchestration. Its GPQA Diamond score reaches 91.3%, and it introduces the ability to spin up independent sub-tasks in parallel — making it uniquely suited for cybersecurity investigations, complex codebase refactors, and high-stakes research where edge-case analysis is mandatory.

## Key Capabilities

<CardGroup cols={2}>
  <Card title="State-of-the-Art Software Engineering" icon="code">
    Outperforms human candidates on elite engineering exams. Handles codebase migrations, complex refactoring, and 30-minute autonomous coding sessions.
  </Card>

  <Card title="Adaptive Thinking and Effort Control" icon="sliders">
    Opus 4.5 and 4.6 both offer configurable reasoning depth — minimize cost for routine tasks, maximize capability for demanding problems.
  </Card>

  <Card title="Parallel Sub-Agent Orchestration" icon="diagram-project">
    Opus 4.6 natively spins up independent sub-tasks to run tools in parallel — essential for cybersecurity and large-scale coding investigations.
  </Card>

  <Card title="Context Compaction" icon="compress">
    Opus 4.6 automatically summarizes older context to sustain "infinite-feeling" agent sessions without losing the original goal-state.
  </Card>
</CardGroup>

## Best For

Choose **Opus 4.5** for deep research, large-scale document analysis, enterprise automation, and production-grade coding agents — particularly where you need a balance of maximum capability and cost efficiency. Choose **Opus 4.6** for the most complex tasks in your stack: multi-day codebase refactors, high-stakes legal or financial research, and cybersecurity defense workflows where parallel sub-agent execution makes a meaningful difference. For tasks that don't require Opus-level intelligence, Sonnet 4.5 or 4.6 offers strong performance at lower cost.

<Tip>
  For long-running agentic sessions, Opus 4.6's Context Compaction feature prevents context-window exhaustion automatically. Enable it explicitly in your agent loop rather than relying on manual context management.
</Tip>

## Use Cases

* **Deep research and analysis** — Digest massive datasets, financial documents, and technical reports using up to 500K (4.5) or 1M (4.6) context.
* **Production-grade coding agents** — Build autonomous agents that create, test, and iterate on entire codebases with up to 75% fewer build/lint errors.
* **Enterprise automation** — Automate complex Excel workflows, financial modeling, and multi-agent systems that refine their own capabilities.
* **Cybersecurity defense** — Perform end-to-end vulnerability investigations with 90%+ success rates in blind tests (Opus 4.6).
* **High-stakes research** — Legal, financial, and scientific discovery where edge-case analysis and multi-step verification are mandatory.

## Specifications

| Specification  | Opus 4.5                                          | Opus 4.6                                      |
| -------------- | ------------------------------------------------- | --------------------------------------------- |
| Provider       | Anthropic                                         | Anthropic                                     |
| Context Window | 200K–500K tokens                                  | 1.0M tokens                                   |
| Reasoning      | Adaptive (Standard/High)                          | Adaptive (Low/Medium/High/Max)                |
| GPQA Diamond   | 88.9%                                             | 91.3%                                         |
| Latency (TTFT) | 0.10s                                             | —                                             |
| Throughput     | 22 tokens/sec                                     | 22 tokens/sec                                 |
| Key use cases  | Expert logic, legal analysis, scientific research | PhD-level research, code review, legal audits |

[Try Opus in DeepMask →](https://chat.deepmask.io/)