Claude Opus 4.7: Complete Guide, Pricing, Specs and Use Cases

An independent guide to Claude Opus 4.7, including verified specifications, pricing, access, capabilities, limitations and a practical evaluation framework.

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What is Claude Opus 4.7?

Claude Opus 4.7 is Anthropic’s proprietary model for reproducing older workflows, migration testing and historical Opus comparisons. It was released April 16, 2026. This guide separates documented specifications from vendor benchmark claims and gives teams a practical way to decide whether the model belongs in a real evaluation.

QUICK VERDICT: Opus 4.7 matters mainly as a migration and historical reference. Its successor corrected verbosity and tool-use issues while preserving the same base price.

Field

Verified value

Provider

Anthropic

Release date

April 16, 2026

Availability

Legacy but still documented

License

Proprietary

Context window

1 million tokens

Maximum output

128,000 tokens

Modalities

Text and image input; text output

API pricing

$5 input and $25 output per million tokens at launch

Access

Claude products, Claude API and supported cloud platforms where retained

Best fit

reproducing older workflows, migration testing and historical Opus comparisons

Last verified

September 2, 2026

What changed with Claude Opus 4.7

Claude Opus 4.7 should not be evaluated as a name change. The important differences are the model’s reasoning controls, tool behavior, context policy, access route and economic profile. Those details determine whether a benchmark result transfers to production.

Area

What changed or matters

Software engineering

Anthropic emphasized gains on difficult coding tasks

Agentic safety

Improved refusal of malicious requests and prompt-injection resistance versus 4.6

Availability

Launched across Claude products, API, Bedrock, Vertex AI and Microsoft Foundry

Behavior

Anthropic later acknowledged unusual verbosity relative to its predecessor

The correct comparison baseline is Claude Opus 4.6. Teams planning a new deployment should also include Claude Opus 4.8 and Opus 5 where access allows. Testing only the newest model or only the incumbent hides the migration cost, output-style changes and tool-use regressions that often matter more than a small benchmark gap.

Claude Opus 4.7 capabilities

The clearest fit is reproducing older workflows, migration testing and historical Opus comparisons. That does not mean every task in those categories should use the model. A production system combines the base model with prompts, retrieval, tools, permissions, memory, retry logic and human review. The model card describes only one layer of that system.

Capability

Practical implication

Long context

1 million tokens. Test retrieval accuracy at realistic lengths rather than assuming every token receives equal attention.

Output capacity

128,000 tokens. Long output is useful only when the verification process can keep up.

Modalities

Text and image input; text output. Confirm format-specific accuracy with your own files.

Agent use

Use explicit tool schemas, narrow permissions, approval gates and recoverable operations.

Reasoning

Record the exact effort level because cost, latency and quality can change materially.

For coding, evaluate repository navigation, test creation, regression rate, review burden and recovery after a failed tool call. For research, measure citation correctness, source coverage and whether the model distinguishes evidence from inference. For computer or browser use, record every unsafe click, wrong field, lost state and unapproved action.

Benchmarks and evidence

The evidence below comes from Anthropic or named launch partners. It is useful for identifying intended strengths, but it is not equivalent to an independent head-to-head test. Prompts, tools, reasoning budgets, sampling, infrastructure and scoring rules can differ.

Evidence

Reported result

How to interpret it

Advanced coding

Launch materials report gains over Opus 4.6 on difficult software work

Vendor benchmark suite

Prompt injection

System card reports stronger resistance in Claude Code and computer use

Pre-deployment safety evaluation

Production quality

Anthropic later documented verbosity and tool-calling issues

First-party post-launch evidence

Treat benchmark results as a shortlist signal. Before purchasing or migrating, reproduce representative work under one frozen protocol. Keep model snapshots, reasoning effort, tool access and token budgets constant. Report repeated-run pass rates and total cost per accepted result, not a single best attempt.

Pricing, access and deployment

Claude products, Claude API and supported cloud platforms where retained. The current pricing reference is $5 input and $25 output per million tokens at launch. Provider pricing changes frequently and can include cache rates, batch discounts, regional premiums, long-context multipliers, priority processing and tool-call fees. Recheck the official pricing page before budgeting.

Cost driver

What to measure

Input tokens

Prompt, retrieved context, tool results and repeated history

Output tokens

Visible answer plus any billable reasoning or generated artifacts

Caching

Eligible repeated prefixes, cache-read price and expiration policy

Tools

Search, computer use, code execution and third-party API fees

Retries

Failed runs, verifier loops and human rework

Success-adjusted cost

Total spend divided by deliverables that pass review

A cheaper token price can lose to a more expensive model if it takes more steps, retries more often or produces work that needs heavy correction. Conversely, a frontier model can be wasteful when a smaller model already passes the task rubric. Route by measured task difficulty rather than brand prestige.

Claude Opus 4.7 limitations

  • It is no longer the current Opus model.
  • Verbose behavior can raise latency and token cost.
  • Later models improved tool-call cleanliness.
  • Exact availability may differ by platform.
  • Migration testing must use locked snapshots when possible.

High-stakes medical, legal, financial, security and scientific work requires qualified review. Store the exact model identifier, prompt version, tools, source documents and approvals for each consequential run. Build a rollback path before granting write access to repositories, browsers, databases or cloud infrastructure.

Risk

Minimum control

Hallucination

Require source checks or executable tests

Prompt injection

Separate untrusted content from instructions and restrict tools

Over-permission

Use least privilege and approval gates

Silent model change

Pin snapshots where possible and run regression tests

Data exposure

Review retention, regional processing and provider terms

Runaway cost

Set token, time, tool-call and retry budgets

How to evaluate Claude Opus 4.7

Create 20 to 50 tasks from real work. Freeze the tasks and rubric before testing. Include easy tasks, normal tasks, edge cases and adversarial inputs. Give each model equivalent tools and enough budget to finish, but cap time and retries. Repeat non-deterministic runs so one lucky result does not decide the winner.

Test area

Record

Task completion

Pass or fail plus rubric score

Reliability

Repeated-run success and variance

Quality

Factuality, instruction adherence and usefulness

Tool use

Wrong calls, retries, recovery and permission errors

Efficiency

Wall time, tokens, cache use, tool fees and human review

Safety

Unsafe actions, injection response and sensitive-data handling

Migration

Prompt changes, integration work and output-style regressions

Compare Claude Opus 4.7 with Claude Opus 4.6 and Claude Opus 4.8 and Opus 5. Choose the least expensive configuration that meets the acceptance threshold with an adequate safety margin. Re-run the suite after any model snapshot, system prompt, retrieval or tool change.

Frequently asked questions

Is Claude Opus 4.7 available now?

Legacy but still documented. The documented access routes are Claude products, Claude API and supported cloud platforms where retained. Availability can differ by region, plan and partner platform.

Is Claude Opus 4.7 open source?

No. Claude Opus 4.7 is proprietary. Access is controlled by Anthropic and supported distribution partners.

How much does Claude Opus 4.7 cost?

$5 input and $25 output per million tokens at launch. Budget with measured end-to-end workloads because token rates alone omit retries, tools, caching, long-context multipliers and review time.

What is Claude Opus 4.7 best used for?

Its strongest documented fit is reproducing older workflows, migration testing and historical Opus comparisons. Start with a supervised pilot and keep human sign-off for consequential work.

Should I migrate from Claude Opus 4.6?

Only after a side-by-side evaluation. Measure pass rate, total cost, latency, output style, tool reliability and the engineering work required to migrate. A newer model is not automatically the better operational choice.

Related model guides

Start with the broader Best AI Models directory.

Compare with the Claude Opus 4.8 guide.

Official sources and update policy

Anthropic Opus 4.7 announcement.

Claude Opus product page.

Anthropic quality postmortem.

Checked September 2, 2026. We update this guide when the provider changes the model specification, pricing, access, licensing or safety documentation. Vendor benchmarks are attributed and are not presented as independent testing. No vendor payment or affiliate relationship determined inclusion.

Author

Dr. Rajesh Patel

PhD in Electrical Engineering and Computer Science, MIT (2016); Postdoctoral research, UC Berkeley BAIR. Research on efficient training algorithms, multimodal architectures, and model robustness.