What it is: Claude Opus 4.6 is Anthropic’s flagship publicly available large language model, released February 5, 2026. It features a 1M-token context window (beta), four adaptive-thinking effort levels, agent teams in Claude Code, and leads the Terminal-Bench 2.0 agentic coding benchmark. Pricing: $5/$25 per million tokens (input/output).
Who it is for: Developers, knowledge workers, founders, and researchers who need the strongest available Claude for hard problems — long-context analysis, agentic coding, multi-step reasoning.
Best if: You hit the ceiling of Sonnet 4.6 on complex tasks and need more reasoning depth.
Skip if: Your tasks are short and simple — Sonnet 4.6 is faster and 5x cheaper. Get one issue per day of AI news in our free daily newsletter.
1-on-1 Coaching
Claude AI Crash Course
1-hour private video session with James. Bring a real problem you want Opus 4.6 to solve — complex codebase refactor, long-document synthesis, multi-step research workflow — and we work through it live. You leave with prompts and patterns calibrated to where Opus actually beats Sonnet, and where it’s overkill.
Group Format
AI Workshops for Engineering Teams
Team-format workshops covering Opus 4.6 use-case selection, model routing patterns (Sonnet vs Opus vs Haiku), 1M-context workflows, adaptive thinking modes, and agent-team design in Claude Code. Best for 3+ engineers.
What is the bottom line on Claude Opus 4.6?
Claude Opus 4.6 is Anthropic’s flagship publicly available model. It was released February 5, 2026, prices at $5 input / $25 output per million tokens (same as Opus 4.5), and adds a 1M-token context window in beta, agent teams in Claude Code, Excel/PowerPoint integration, four adaptive-thinking effort levels, and 128k token outputs. On Anthropic’s published benchmarks it outperforms Opus 4.5 by 190 Elo points on GDPval-AA, beats GPT-5.2 by 144 Elo points on the same benchmark, and leads both Terminal-Bench 2.0 and Humanity’s Last Exam — making it the strongest publicly accessible model on Anthropic’s own evaluations as of May 2026.
What are the key takeaways?
- Released February 5, 2026.
- 1M-token context window in beta on the API (the first Opus-class model to ship this).
- $5 / $25 per million tokens standard rate; $10 / $37.50 for inputs over 200k tokens.
- 128k output tokens — long enough for full reports, documents, or large code generations.
- Agent teams in Claude Code — multiple Claude agents working in parallel on different parts of a task.
- Excel + PowerPoint integration — Excel upgraded, PowerPoint in research preview for Max/Team/Enterprise.
- Adaptive thinking with four effort levels: low, medium, high, max.
- Highest Terminal-Bench 2.0 score among all frontier models on Anthropic’s published evaluation.
- Available everywhere: claude.ai, API, AWS Bedrock, Google Vertex AI, Microsoft Foundry.
What is Claude Opus 4.6 exactly?
Claude Opus 4.6 is the most capable model in Anthropic’s publicly available Claude family. It sits at the top of the Opus tier, above Sonnet (mid-tier) and Haiku (fast, cheap). Opus is designed for tasks that genuinely benefit from more reasoning depth: complex coding, multi-step planning, long-context analysis, hard analytical work.
In Anthropic’s framing, Opus 4.6 “extends the frontier of expert-level reasoning” with better planning, longer agentic task sustainability, more reliable operation in large codebases, and stronger code review and debugging skills compared to its predecessor. Above Opus 4.6 sits Claude Mythos, a restricted-access model not generally available.
What’s new in Claude Opus 4.6 vs. Opus 4.5?
| Capability | Opus 4.5 | Opus 4.6 |
|---|---|---|
| Release | Late 2025 | February 5, 2026 |
| Context window | 200k tokens | 1M tokens (beta, API) |
| Output token limit | Standard | 128k tokens |
| Adaptive thinking modes | Single effort level | Four levels (low/medium/high/max) |
| Agent teams in Claude Code | Sequential agents | Parallel coordination |
| Excel integration | Basic | Substantial upgrade |
| PowerPoint integration | None | Research preview |
| Context compaction | No | Beta — Claude can summarize its own context |
| GDPval-AA score | Baseline | +190 Elo points over Opus 4.5 |
| Pricing | $5 / $25 per M tokens | $5 / $25 per M tokens (same) |
| Over-refusal rate | Low | Matches 4.5 |
How much does Claude Opus 4.6 cost?
Standard API pricing is $5 per million input tokens and $25 per million output tokens. Two important wrinkles:
- Inputs over 200,000 tokens price at the premium rate of $10 / $37.50 per million. So if you’re using the 1M-context window heavily, factor in the higher rate for the long-context portion.
- US-only inference (data routed only through US infrastructure) is available at 1.1× token pricing. Useful for organizations with data-residency requirements.
If you access Opus 4.6 through a Claude subscription (Pro, Max, Team, Enterprise) instead of the API, usage is included in your plan’s quotas. Most individual developers find the subscription path simpler for everyday use; API access is the right choice for production workloads where you want metered costs.
When should you use Opus 4.6 vs. Sonnet 4.6?
Anthropic publishes Sonnet 4.6 as the everyday workhorse and Opus 4.6 as the heavy hitter. Rule-of-thumb mapping:
| Job | Use Sonnet 4.6 | Use Opus 4.6 |
|---|---|---|
| Quick code edits, single-file changes | Yes | Overkill |
| Multi-file refactor across a codebase | Often fine | Worth the cost |
| Long-document synthesis (500+ pages) | Slow on long context | Where Opus shines |
| Hard debugging across modules | Acceptable | Markedly better |
| Agent teams running in parallel | Works | Designed for this |
| Routine summarization | Yes — 5x cheaper | Wasteful |
| Writing standard emails / first drafts | Yes | Wasteful |
| Research synthesis across 30+ sources | Acceptable | Better recall on details |
On the long-context benchmark MRCR v2, Opus 4.6 scores 76% versus Sonnet 4.5’s 18.5% — a roughly 4× gap. That gap is the clearest argument for paying for Opus when your task genuinely involves keeping a large codebase or document in active context.
How does the 1M-token context window work?
The 1M context window is available in beta on the API only (not yet in claude.ai chat). It accepts up to roughly 750,000 words of input — the equivalent of about three full-length novels or a mid-size codebase. Practical use cases:
- Whole-codebase reviews. Drop in 50,000 lines of code; ask for an architectural critique.
- Full-document analysis. A 200-page contract plus the 800 pages of regulatory context that interpret it.
- Multi-source research synthesis. 40 PDFs in one prompt; ask for the cross-source synthesis.
- Long agentic runs. Combined with context compaction, agents can sustain longer-running tasks without bumping the context wall.
Cost note: inputs over 200k tokens move to the premium rate ($10 / $37.50). Use 1M context judiciously — chunked retrieval is often cheaper for the same outcome unless your task genuinely needs everything in context simultaneously.
What are the four adaptive thinking effort levels?
Opus 4.6 introduces explicit control over how much “thinking” the model does before responding. Four levels:
- Low — minimal extended reasoning. Fast and cheap; right for routine tasks.
- Medium — default for most use cases. Balanced.
- High — substantially more reasoning. Right for hard problems where the answer matters more than speed.
- Max — the deepest reasoning mode. Use it for the genuinely hard questions where you’d otherwise want a senior human reviewer.
Higher effort levels consume more output tokens (so cost goes up) and take longer per response. The right level is task-dependent — don’t default to “max” for everything.
What are Claude Code agent teams?
Agent teams are a Claude Code feature that ships with Opus 4.6: multiple Claude agents can work on different parts of a task in parallel rather than sequentially, with each agent coordinating directly with others. Practical use:
- Parallel code review — one agent reviews the backend changes, another reviews the frontend, a third checks for security issues, and a coordinator summarizes.
- Multi-component feature builds — one agent builds the API, another builds the database migration, a third builds the UI; all coordinate.
- Research + implementation — one agent researches the right pattern; another implements it.
For the deeper guide on running agent teams effectively see our Claude Code advanced workflows post.
How does Opus 4.6 compare to GPT-5.2?
On GDPval-AA, an Anthropic-published cross-disciplinary reasoning benchmark, Opus 4.6 outperforms GPT-5.2 by approximately 144 Elo points. On Humanity’s Last Exam — an independent multidisciplinary hard-question test — Opus 4.6 leads all evaluated frontier models. On Terminal-Bench 2.0 (agentic coding), Opus 4.6 holds the top score.
Anthropic’s benchmarks favor Anthropic, of course. Independent benchmarks like LiveBench and SWE-bench Verified tell more nuanced stories where different models lead different sub-tasks. For most practical work in 2026, Opus 4.6 and GPT-5.2 trade leadership across categories — Opus tends to lead on long-context, code review, and agentic workflows; GPT-5.2 tends to lead on web search integration and image generation. For a fuller head-to-head see our ChatGPT vs Claude 2026 comparison.
What’s new in Claude in Excel and PowerPoint?
Opus 4.6 ships with substantially upgraded Claude in Excel performance and a Claude in PowerPoint research preview available to Max, Team, and Enterprise plan users. In practice this means Claude can now read your real spreadsheet (formulas, references, named ranges, pivot tables), reason about it accurately, and make edits in place — not just suggest them in chat.
Common use cases: financial-model audits (“trace why row 47 is showing #REF!”), data-cleaning automation (“normalize all the addresses in column D”), executive-deck drafting (“turn this Excel data into a 6-slide deck with one slide per region”), and ad-hoc analysis (“what’s the seasonal pattern in revenue and what’s driving it?”). The PowerPoint preview is limited to Max/Team/Enterprise as of May 2026; broader access is expected through the year.
What is context compaction and why does it matter?
Context compaction is a beta API feature that lets Claude summarize its own working context mid-task, freeing up token budget for continued work without losing the thread of what it’s doing. Without compaction, long-running agentic tasks eventually hit the context wall and have to be restarted or chunked manually.
With compaction enabled, an agent can run substantially longer in a single coherent task. Practical impact: a code refactor that touches 200 files, a research synthesis that ingests 60 sources, or a multi-day operations workflow can now complete without context-related interruptions. Compaction is opt-in via API flag — you decide when the trade-off (some detail loss in compacted segments) is worth the extended runtime.
How do you access Claude Opus 4.6?
- claude.ai — web and mobile, included with Claude Pro and above.
- Claude API — pay-as-you-go via Anthropic Console. Model identifier:
claude-opus-4-6. - AWS Bedrock — available for enterprise customers on Amazon’s cloud.
- Google Vertex AI — available on Google Cloud.
- Microsoft Foundry (on Azure) — available for enterprise customers.
- Claude Code — automatically routed for tasks that benefit from Opus.
Frequently asked questions
What’s the API model ID for Opus 4.6?claude-opus-4-6. Use this in the model field of your API requests.
Is Claude Opus 4.6 better than ChatGPT?
It depends on the task. Opus 4.6 leads on Anthropic’s published benchmarks for long-context, agentic coding, and complex reasoning. ChatGPT (GPT-5.2) leads on web search, image generation, and the broadest ecosystem of plugins. See our full comparison.
Is there a Claude Opus 4.7?
Yes — Opus 4.7 is the model that powers Claude Code as of 2026. It’s a Claude Code-specific iteration on the 4.6 base. The chat product on claude.ai uses Sonnet 4.6 and Opus 4.6.
How do I enable the 1M context window?
Use the beta header context-1m-2026-02-05 on your API request. The 1M context is API-only as of May 2026; not yet available in claude.ai chat.
Why does Opus cost 5x more than Sonnet?
Opus is a larger model that performs more reasoning per token. The right framing isn’t “Opus is expensive” but “Opus is overkill for routine tasks and underpriced for hard ones.” Pick the model that fits the job.
Can Opus 4.6 generate images?
No. Claude is text-and-code-first. Use Claude Design or pair Claude with an image model (DALL-E, Midjourney, Stable Diffusion) if you need image generation in a workflow.
Does Opus 4.6 hallucinate less than older Claude versions?
On Anthropic’s published evals, yes — particularly on long-context retrieval (76% on MRCR v2 vs. 18.5% for Sonnet 4.5). Hallucinations aren’t zero, but on the kinds of tasks where older Claude models would fabricate, Opus 4.6 is markedly more reliable.
Will Opus 4.6 be replaced soon?
Claude model versions ship roughly every 3–6 months. Expect a 4.7 chat update (analogous to the Claude Code 4.7) and eventually a 5.0 family. Opus 4.6 has been stable for several months as of May 2026, suggesting a meaningful runway before the next major release.
How does Opus 4.6 handle code in 50+ programming languages?
Anthropic doesn’t publish per-language benchmarks, but in practice Opus 4.6 is strongest in Python, TypeScript/JavaScript, Go, Rust, Java, and C++; competent across mainstream languages; weaker on niche languages where training data is sparse. The model can also work in plain-English specifications and produce equivalent code in multiple languages from one prompt.
Can I fine-tune Claude Opus 4.6?
Not currently. Anthropic offers fine-tuning on Haiku tier models via select cloud providers; Opus tier is closed for fine-tuning. The practical alternative is well-designed system prompts and retrieval-augmented generation (RAG).
What does the “6” in 4.6 mean?
Anthropic’s version numbering: the major number (4) reflects architectural family; the minor number (6) reflects training iteration. 4.5 to 4.6 was an iteration on the same architecture with improved data and training. A 5.0 release will likely indicate a significant architectural change.
Is Claude Opus 4.6 safe to use in production?
Yes, with the same caveats as any frontier LLM: validate outputs on high-stakes tasks, don’t grant unconstrained tool access on production systems, and review the model’s responses where correctness matters. Anthropic publishes safety evaluations including a low over-refusal rate and six new cybersecurity probes for Opus 4.6 specifically. The model behaves consistently across long-running agentic tasks, which is a meaningful improvement over earlier Opus versions for production reliability.
Does Opus 4.6 support voice or audio input?
Not natively. Opus 4.6 is text-and-image multimodal but does not directly process audio. Pair it with a speech-to-text service (Whisper, Deepgram, AssemblyAI) for voice workflows, or use Anthropic-built voice features on the Claude consumer apps where available.
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Sources
- Introducing Claude Opus 4.6 — Anthropic (Feb 5, 2026)
- Claude models overview — Anthropic documentation
- Expanding Vertex AI with Claude Opus 4.6 — Google Cloud Blog
- Claude Opus 4.6 in Microsoft Foundry — Microsoft Azure Blog
- Claude Opus 4.6 model card — AWS Bedrock
- Anthropic launches Claude Opus 4.6 — CNBC
- Anthropic pricing