Move your team from ChatGPT to Claude Science.
Each person gets a short interview, then a personalized step-by-step guide showing exactly where their saved work, prompts, and projects land in Claude Science — and the few things that need a manual step, walked through. You send one invite; nobody becomes the help desk, and nothing in ChatGPT is changed or cancelled. Want to see where you’re paying for both first? Run the free audit.
ChatGPT Canvas is (or, per its May 2026 partial removal, was) a side-panel for iterating on a single document or code file with version history. Claude Science's versioned artifacts go further for research outputs specifically: every figure, notebook, structure, or manuscript is saved with a full provenance record (exact code, environment, and conversation that produced it), and a background Reviewer agent cross-checks claims against that record — catching citation errors, unverifiable numbers, and figures that don't match their underlying code. A user relying on Canvas's version history to track how a document evolved should treat Claude Science artifacts as the closer fit for scientific work: the provenance record answers 'what produced this exact number/figure' in a way Canvas's edit history does not, and the Reviewer adds an automated correctness check with no Canvas equivalent at all.
- Warning: Canvas revision history is manual/user-driven; the Reviewer is an automated agent that runs on its own schedule (automatic on Max/Team/Enterprise, manual 'Request review' on Pro) and produces findings cards with evidence and transcript links, a fundamentally different mechanism than diffing document versions.
- Warning: The Reviewer explicitly checks claims against the execution record rather than re-running analyses, and cannot judge whether the chosen scientific method was appropriate — it is not a substitute for a human scientific reviewer, just a citation/consistency check.
- Warning: Canvas's separate side-panel surface was removed from GPT-5.5 Instant/Thinking as of May 28, 2026 (folded into inline writing/code blocks), so the ChatGPT side of this comparison is itself unstable — verify current Canvas availability before treating it as a stable baseline.
- Warning: Claude Science artifact viewers are domain-specific (protein/molecular structures, sequence alignments, genomic tracks, chemical structures, PDFs) — there is no equivalent specialized rendering in Canvas, which is oriented toward general text/code documents.
ChatGPT's Code Interpreter runs Python in a stateful, session-scoped Jupyter sandbox with no external network access. Claude Science's sandboxed compute environment is the closer analogue than plain Claude code execution: it runs Python, R, and shell locally on the user's machine with persistent kernels tied to a session's workspace folder, so dataframes and loaded models survive across turns the same way a Code Interpreter session persists mid-conversation. Scientific users moving heavier analyses over should expect to grant explicit approval for folder access and network hosts (Claude Science can reach the network and remote hosts, unlike Code Interpreter's fully offline sandbox) and to install the ~5GB local runtime plus platform prerequisites (bubblewrap/socat on Linux, macOS 13+) before first use.
- Warning: Code Interpreter cannot make outbound network calls at all; Claude Science's sandbox can request network hosts (with approval), so a workflow that relied on Code Interpreter's total isolation needs re-scoping, not just porting, if network access must stay blocked.
- Warning: Code Interpreter has no local install — it's fully hosted; Claude Science requires ~5GB of local disk and OS-level prerequisites (bubblewrap 0.8.0+ and unprivileged user namespaces on Linux, macOS 13+ on Mac) and has no Windows-native build (WSL only, not fully available yet).
- Warning: R is not supported by ChatGPT's Code Interpreter (Python only); Claude Science adds R kernels, which is a net capability gain but not a like-for-like migration concern.
- Warning: Code Interpreter's environment resets per new chat; Claude Science kernels persist per session workspace folder and can run across a long research project, so mapping 1:1 by 'session' undercounts how much state actually carries over.
ChatGPT's Custom Connectors (Apps/MCP) give generic access to third-party services the user configures per-app, with read-only defaults and per-app approval. Claude Science ships 60+ domain-specific connectors pre-configured out of the box (Ensembl, UniProt, PDB, AlphaFold, PubChem, ClinVar, GTEx, and dozens more across genomics, structural biology, and cheminformatics) plus a skills directory for model-specific workflows (AlphaFold2, ProteinMPNN, ESM-2, scGPT). A researcher moving from a custom MCP connector they built against a scientific database should first check whether Claude Science already has a featured connector for it — most major public scientific databases are covered natively and need only be enabled in Settings > Connectors, no auth or per-tool approval required. Only bespoke or internal data sources need a custom connector (still MCP-based, approved per Once/conversation/project/global scope, same as ChatGPT).
- Warning: Claude Science's featured connectors are read-only by design, with the user bearing third-party terms compliance — a ChatGPT custom connector configured for write access to a scientific database has no equivalent path in the featured set and would need a custom connector instead.
- Warning: ChatGPT's full-MCP write/modify actions are still beta and restricted to Business/Enterprise/Edu workspaces; Claude Science's approval-scoped custom connectors are available more broadly, so the admin-gating story differs by org tier on the ChatGPT side.
- Warning: Claude Science's connector list is curated specifically for life-science and chemistry domains; it has no equivalent for the general-purpose business-app connectors (Slack, Notion, Linear, etc.) that ChatGPT's Apps/Connectors cover — those remain a base-Claude or ChatGPT capability, not a Claude Science one.
ChatGPT Deep Research produces a single-shot cited report from a reviewed research plan; Claude Science's coordinating agent runs the equivalent planning-and-search loop inside a persistent desktop research workspace, then keeps going — the same session's kernels, folder, and manuscript draft stay alive for follow-on analysis instead of ending at the report. Users moving a recurring research workflow should recreate each Deep Research topic as a Claude Science project (shared folder permissions + custom instructions), and use delegation (session forking) where they previously ran multiple separate Deep Research tasks to compare approaches. Composer shortcuts ('@' for artifacts, '#' for past sessions, '/' for skills) replace ad hoc re-uploading of prior report context.
- Warning: Claude Science is a beta desktop app (macOS Apple Silicon/Intel, Linux x64) with no Windows-native or web build yet; ChatGPT Deep Research is available anywhere ChatGPT runs, so Windows-only users cannot follow natively (WSL support is tracked but not confirmed shipped).
- Warning: Deep Research is a bounded task with a monthly quota counter; Claude Science sessions are open-ended and instead draw from the same shared 5-hour/weekly usage limit as Claude Code and Claude Cowork, so cost shows up as elapsed compute time rather than a per-report count.
- Warning: ChatGPT's Sites -> Manage sites lets users scope Deep Research to specific domains; Claude Science has no equivalent site-restriction control — its scope narrows via which connectors/skills are enabled, not URL allowlists.
- Warning: Deep Research output is a standalone downloadable report (Markdown/Word/PDF); Claude Science's output is a versioned artifact inside a project workspace with provenance, which is richer but not a portable single file by default.
ChatGPT gates its research-adjacent capabilities (Deep Research quota, Code Interpreter tiers, Canvas availability) by subscription tier across a Free/Go/Plus/Pro/Business/Enterprise ladder with per-feature usage counters. Claude Science is instead bundled at no separate charge into any paid Claude plan (Pro, Max, Team, Enterprise) — there is no standalone Claude Science fee or usage-based add-on, and it draws from the same shared 5-hour/weekly usage budget as Claude Code and Claude Cowork rather than its own quota. A ChatGPT Plus/Pro user evaluating a move should compare against Claude Pro (~$20/mo) as the cheapest tier that unlocks Claude Science, keeping in mind Claude Science is entirely unavailable on Claude's Free plan (unlike some ChatGPT research features which are merely 'Limited' on Free).
- Warning: Team/Enterprise Claude orgs must have an Owner explicitly enable Claude Science under Organization settings > Capabilities before any member gets access — it's off by default at the org level even on a plan that supports it, a stricter default than ChatGPT Business/Enterprise's connectors-style admin gating.
- Warning: There's no Claude Science-specific price tier to compare like-for-like against ChatGPT Pro $100/$200 — cost is fully absorbed into the base Claude plan price, so a cost migration analysis should use the underlying Claude plan price, not a separate feature price.
- Warning: Anthropic separately runs an 'AI for Science' credits program (up to $30,000 Anthropic credits + $2,000 Modal credits) for postdoc/grad researchers — this is a grant program with an application deadline, not a pricing tier, and shouldn't be treated as a standing discount path.
- Warning: ChatGPT's per-feature usage counters (e.g., Deep Research task counts) give users a visible remaining-quota number; Claude Science usage is folded into a broader time-based budget shared with other Claude products, so users can't isolate 'Claude Science quota remaining' the same way.