Short answer
For billable‑grade legal research memos, prioritize a model that you can pair with reliable retrieval (RAG) and an enterprise deployment that provides audit logs and data controls. If you must pick one among these three: Claude (enterprise) is the best single model for long, careful drafting and auditability; use ChatGPT where you need broad plugin/integration support and workflow familiarity; consider Gemini if you already depend on Google’s retrieval stack for citation provenance.

Recommendation
Use Claude Enterprise (or another long‑context, enterprise model) as the drafting engine, combined with a controlled RAG pipeline (document store: Westlaw/Lexis/primary sources; vector DB; strict source metadata). Run every model output through a human verification step that checks citations against primary documents before filing or billing.

Decision criteria (what matters for legal memos)
- Citation grounding: model + retrieval must show exact source, paragraph/page/pinpoint citation and a stable URL or document ID. Models alone rarely suffice.
- Auditability and logs: enterprise offering with query logs, user IDs, and exportable transcripts for ethical/audit review.
- Confidentiality and hosting: on‑prem/VPC or HIPAA/ISO‑27001 level controls and contractual data non‑retention.
- Context length and structure: ability to consume entire pleadings and long facts.
- Accuracy/hallucination controls: low‑temperature deterministic generation, citation‑first prompts, conservative summaries.
- Integration: connectors to your library (Westlaw/Lexis), DMS, and practice templates.

Practical checklist to implement (minimum viable safe workflow)
1. Choose enterprise tier with contractual data protections and logs.
2. Build RAG: ingest only authoritative sources (court opinions, statutes) with metadata (source, section, page).
3. Use a prompt template requiring citation inline and a sources list with direct links/IDs.
4. Set model temperature low and require “show exact quote and citation.”
5. Human reviewer checklist: confirm each cited passage, verify pin cites, update Bluebook form, and certify memo before distribution.
6. Store the search traces, search queries, and the retrieved documents alongside the memo for audit.
7. Run a final automated citation checker or script to validate URLs/pincites.

Best‑for / Avoid‑if
- Best for Claude: long, analytical memos where you need careful stepwise reasoning and long context.
- Best for ChatGPT: integration with diverse plugins/workflows, quick drafting, familiar UX across teams.
- Best for Gemini: firms deeply tied to Google search/data and wanting tight web retrieval (verify enterprise features first).
- Avoid any model if you lack RAG, human verification, or enterprise data controls—models alone are too risky for relied‑upon legal work.

When it depends
If budget is tight, start with ChatGPT and strict manual verification. If you have large teams and high‑risk filings, invest in a Claude/Gemini enterprise deployment plus RAG, ingestion pipelines, and a dedicated review workflow.

Bottom line
Pick the model that your enterprise contract and RAG architecture can secure and log. For most firms writing billable memos, Claude Enterprise + controlled retrieval + human verification is the most practical single‑model choice; use ChatGPT when integration speed matters. Always validate citations against primary sources before relying on them.

Compare Claude and ChatGPT