What it is
Astra for Law is OpenAI’s legal configuration of GPT-6 Astra, announced on 17 September 2026. It is not a separately trained model. It is GPT-6 Astra plus three additions: a Legal Search Index over US primary law, custom instructions for legal analysis and drafting, and a set of legal plugins inside ChatGPT. It ships through ChatGPT and Codex, not as its own app. It is unrelated to Agiloft’s contract product of the same name.
Access is the first thing to know. Astra for Law is limited to selected Am Law 200 firms in OpenAI’s Trusted Access Program, which OpenAI designed with Latham & Watkins. API access is announced but undated. Sullivan & Cromwell, Ropes & Gray, Cooley, and Latham are the firms named in launch coverage. If your firm is not on that list, what you can buy today is ChatGPT Enterprise and the plugins, not Astra for Law itself.
What you actually get
The Legal Search Index. More than 230 million URLs of US case law, statutes, regulations, court rules, and administrative decisions, updated daily. The case-law core comes from Free Law Project’s CourtListener, which OpenAI says covers more than 99.9% of published US precedential opinions. There is no coverage outside the US and no stated plan for it.
The plugins. 26 partner-built plugins at launch, including Thomson Reuters, Harvey, Legora, iManage, Intapp, Relativity, Clio, and DeepJudge, plus community-built plugins and skills. ChatGPT for Word went generally available alongside it.
Firm-built tools. The launch examples show where the value sits. Sullivan & Cromwell built an agreement analyzer on its negotiating playbooks, Ropes & Gray a data-room diligence system, and Cooley a “GO Public” tool for IPO preparation. Each one is the firm’s own knowledge wired into the model, not an off-the-shelf feature.
Data controls. Eligible firms get Zero Data Retention on the API, and their ChatGPT Enterprise usage is excluded from human review by default.
The benchmark, read properly
OpenAI reports 54.0% correctness on 200 questions from Vals AI’s Legal Research Bench, against 38.7% for GPT-6 Astra with web search: a 40% relative gain, plus 24% more reference cases found. Two caveats change how to read that. The check is all-or-nothing, so 46% of answers still failed it. And the baseline is OpenAI’s own model, not Westlaw, Lexis, or any competing legal research product. No independent run has been published. That 54% figure is what r/legaltech argued about within two days of launch.
The scoped use case that justifies it
A 600-lawyer Am Law firm with a capital markets practice, already on ChatGPT Enterprise and iManage. Associates spend days pulling precedent filings and checking state-law questions for each IPO. With Astra for Law in the Trusted Access tier, the practice group builds its own drafting and risk tool, as Cooley did, that reads prior deals from iManage through the plugin, researches the open questions against the Legal Search Index, and drafts issue memos for partner review. Nothing leaves under the ZDR terms. That is the job a frontier lab plus the firm’s own playbooks does better than a generic seat.
Pricing reality
OpenAI has published no price for Astra for Law, not per seat and not per token. What you can anchor on is ChatGPT Enterprise, which is also quote-only. 2026 procurement reports put it at roughly $45 to $75 per seat per month, around $60 typical, with a reported 150-seat minimum on an annual prepay. That puts the floor near $108,000 a year before any legal premium. The plugins run on licences you already hold: the Thomson Reuters, iManage, Relativity, Harvey, and Legora plugins do nothing without those contracts. Harvey, by comparison, is reported near $1,200 per seat per month on a 20-seat minimum.
Best for
The CIO, innovation partner, or head of knowledge management at an Am Law 200 firm that already runs ChatGPT Enterprise and has engineers or legal technologists who can build firm-specific tools on the model. It fits US research and transactional work where the firm’s own playbooks are the differentiator.
Versus the alternatives
Harvey is the segment leader by revenue and firm count. Pick it when you want a vendor accountable for legal output, lawyer-facing onboarding, and LexisNexis citation checking. Harvey is also an Astra for Law API customer, so you may get OpenAI’s model through it anyway.
Thomson Reuters CoCounsel is the incumbent for primary law. Pick it when citator-backed research on Westlaw is the core job. Astra’s index is case law without KeyCite or Shepard’s signals.
Legora is the fastest-growing entrant. Pick it for a collaborative review and drafting surface associates open on their own, and outside the US, where Astra’s index has nothing.
Claude for Legal is the closest analogue. Pick it when you are not on the Trusted Access list, want to fork the prompts yourself (Apache 2.0 on GitHub), or need to start without a sales cycle. Gemini Enterprise for Legal is the pick for firms whose estate is Google Workspace.
Watch-outs
- You probably cannot buy it yet. Access is invitation-only, Am Law 200, US. Guard: ask your OpenAI account team in writing whether your firm is eligible and on what timeline, and do not budget on Astra until the answer names a date.
- The benchmark is self-reported against itself. Guard: run your own 30 to 50 research questions from closed matters through Astra and your current research platform, and score the citations by hand before any rollout memo.
- A fluent answer is not a checked citation. Nearly half of benchmark answers failed. Guard: keep Westlaw or Lexis citator checks as a required step for every cite in a filing, and record that step in the matter workflow.
- ZDR terms are long. Launch coverage noted the full retention agreement runs about 30 pages. Guard: have the general counsel’s office review the agreement and the plugin data flows before the first client matter goes through it.