June 1, 2026 (in 3 days): New York: 22 NYCRR Part 161 takes effect, system-wide AI policy for all UCS courts

Claude vs ChatGPT for Legal Research

A vendor-disclosed comparison of the two leading consumer AI assistants for the lawyer evaluating either for legal-research use. Every cell is sourced to the vendor's own page. Neither vendor markets a legal-specific use case; both are general-purpose assistants. The legal-research question is which one fits a firm's governance posture, not which one is "better at law."

Dimension Claude ChatGPT
Free tier $0/month $0/month; limited messages, uploads, image generation, deep research, memory, Codex
Individual paid tier Pro: $17/month billed annually ($200 up front), or $20/month billed monthly Plus: $20/month
Power-user individual tier Max: from $100/month Pro: from $100/month; 5x or 20x more usage than Plus, unlimited GPT-5.3, GPT-5.5 Pro reasoning
Team tier (small business) Team (5-150 users): Standard seat $20/seat/month annual ($25 monthly); Premium seat $100/seat/month annual ($125 monthly), 5x more usage than standard Business (2+ users): $20/seat/month annual ($25 monthly)
Enterprise tier Enterprise: $20/seat + usage at API rates Enterprise: custom pricing; contact sales
Training on user content (consumer tiers) Anthropic's commercial terms state Anthropic may not train models on Customer Content from Services Not publicly disclosed
Training on user content (team / enterprise) No model training on your content by default (stated on the Team and Enterprise plan cards) No training on your data (stated on the Business plan card); no training on your business data by default (stated on the Enterprise plan card)
SSO / identity controls (team / enterprise) Single sign-on (SSO) on Team; SCIM, audit logs, role-based access on Enterprise SAML SSO + MFA on Business; SCIM, EKM, role-based access on Enterprise
Compliance posture (team / enterprise) HIPAA-ready offering available on Enterprise; Compliance API for observability and monitoring Business: support for compliance with GDPR, CCPA, and other privacy laws; aligned with CSA STAR and SOC 2 Type 2
Data residency / retention (enterprise) Custom data retention controls; network-level access control; IP allowlisting Expanded context window; custom data retention; encryption at rest and in transit; data residency in ten regions
Public legal-use language Not publicly disclosed Not publicly disclosed

Last verified against vendor sources: May 5, 2026.

Legal AI Governance does not sell, resell, take referral fees, or accept advertising from any vendor on this site. Every cell above is sourced to the vendor's own page; cells marked "not publicly disclosed" reflect the absence of a first-party statement and are intentionally not back-filled from third-party aggregators.

Where the two products overlap

Both Claude and ChatGPT are general-purpose conversational AI assistants with broadly similar pricing structures: a free tier, a mid-tier consumer subscription at $17 to $20 per month, a power-user tier from $100 per month, and team and enterprise tiers with identity, billing, and compliance controls. Both vendors state on their team and enterprise plan cards that user content is not used to train models by default. Both offer SSO, role-based access control, and audit-trail features at the enterprise tier. Both have an expanding integration surface with Microsoft, Slack, Google Workspace, and other workplace tools.

Neither vendor publicly markets a legal-specific use case on the pricing page or product surface reviewed. A lawyer evaluating either tool is evaluating a general-purpose assistant, not a legaltech product. The Stanford RegLab study summarized on the AI hallucination explainer found that even purpose-built legal AI products (Lexis+ AI, Westlaw AI, Casetext) hallucinated on 17% to 33% of legal-research queries. A general-purpose tool like Claude or ChatGPT carries at least the same risk, often more.

Where their public posture differs

Pricing structure. Both offer a $20/month consumer tier and a $100/month power-user tier. Claude's annual discount on Pro ($200 up front, working out to $17/month) is the cheapest committed-annual price among the major consumer assistants. The Team and Business tiers land at the same $20-$25/seat range; the operationally meaningful difference is at the high end, where Claude's Premium seat ($100/seat/month annual) is twice the cost of standard but with 5x usage, while ChatGPT keeps a single Business tier and gates expanded usage to Enterprise.

Compliance and confidentiality posture. ChatGPT Business carries explicit GDPR, CCPA, CSA STAR, and SOC 2 Type 2 alignment language on the pricing page. Claude does not match those compliance frameworks line-for-line on the pricing page itself, but Claude Enterprise is described as "HIPAA-ready," which ChatGPT does not state on its pricing page. For firms whose AI use will touch protected health information or sit on top of healthcare data, the HIPAA framing matters. Both vendors support SSO at the team tier and SCIM at enterprise; the operational differences are at the controls layer (custom data retention, IP allowlisting, network access control) where Claude Enterprise is more explicit.

Training on user content. Both vendors state at the team and enterprise tiers that customer content is not used to train models by default. Anthropic's commercial terms make a stronger blanket statement that Anthropic "may not train models on Customer Content from Services," language that applies across the Services as a class rather than only at the tier card. ChatGPT's training-on-input behavior at the consumer Plus and Pro tiers is controlled through user settings rather than a contractual guarantee, and is not surfaced on the pricing page. For client confidential work under Rule 1.6, the contractual posture matters more than the default setting.

Data residency. ChatGPT Enterprise documents "data residency in ten regions"; Claude Enterprise documents "network-level access control" and "IP allowlisting" but does not enumerate residency regions on the pricing page. For US firms with no cross-border practice, this is a non-issue. For firms with EU clients, Australian clients, or healthcare clients with data sovereignty requirements, this is a real procurement question.

Confidentiality posture for client-confidential work

ABA Formal Opinion 512's Rule 1.6 analysis (covered in the Opinion 512 compliance guide) puts the burden on the firm to verify the training-on-input behavior of each AI tool before client information is input. The ranked posture for both vendors:

The vendor due-diligence checklist is the 11-item file the policy template assumes a firm has on hand. Whichever vendor the firm picks, the same checklist applies.

Which fits which use case in legal work

Neither vendor wins outright. The defensible buyer-side read, given the public record:

How to evaluate either on your own corpus

The methodology that matters more than any vendor comparison is the firm's own representative-query test. Twenty to fifty of the firm's actual recent legal-research queries, run through both tools, with results compared against verified human-reviewed answers, will surface signal that no public pricing page or third-party review can give. This is the methodology Stanford RegLab used to test purpose-built legal AI products (summarized at the AI hallucination explainer), and the same approach applies to general-purpose assistants used for legal work.

The procurement-side checks before either tool reaches client work:

  1. Vendor due-diligence file. Terms of use, privacy policy, data retention, training-on-input behavior at the chosen tier. The 11-item vendor checklist is the artifact a malpractice carrier asks to see at renewal.
  2. Verification protocol for any AI-assisted filing. Every cite in a filing opened in the underlying reporter or docket, by a named human, before the brief is signed. The verification log template is the per-matter record.
  3. Supervisory protocol for AI-assisted work product. Any work product generated with AI assistance reviewed by a supervising lawyer before it leaves the firm. The policy template covers the section structure.

Whichever tool the firm picks, the documentation a malpractice carrier or a sanctioning court asks for is the same set. See AI Liability Insurance for Law Firms for the current carrier landscape and the seven questions to put to the underwriter.

How this page is built

Every cell in the comparison table above is sourced to a URL on the vendor's own site, dated 2026-05-05, and was extracted from a live browser session against the vendor's pricing page. Cells marked "not publicly disclosed" reflect the absence of a first-party statement on the pages reviewed; they are intentionally not back-filled from PitchBook, Crunchbase, or trade-press aggregators. The page will be re-verified quarterly. Last verified: May 5, 2026.