Legal AI Pricing in 2026: Published Prices, Reported Quotes and What a Five-Lawyer Firm Needs

Search for “Harvey pricing” and you will find pricing guides written by Harvey’s competitors, a demo form, and one anonymous Reddit post. The post is the only place a buyer has written down what they were actually quoted: “Harvey initially quoted us $1,200 per user per month, and $2,400 per user per month if we wanted Lexis integration. Later, they came back with a lower tier around $399/user/month” (r/legaltech). That is the state of legal AI pricing in September 2026: the products most firms are being sold are the ones with no price tag.

The honest format is therefore a transparency scorecard, not a price list. Every number below is labelled published (on the vendor’s own page, checked in September 2026), reported (a named third party’s figure) or quoted (a single anonymous buyer). Then comes the arithmetic for a five-lawyer firm, and finally what you can bill to a client.

The transparency scorecard: who publishes a price

Sources: claude.com/pricing, Microsoft’s enterprise Copilot page, LawNext on Clio Work and GC AI’s Harvey vs CoCounsel table. The pattern is not accidental: the vendors with published prices sell to individuals and small teams; the vendors without them sell to committees.

General models: ChatGPT, Claude, Gemini and Copilot tiers

The general models are the only layer where you can read the price before the call. For a lawyer the number that matters is not the fee but whether the tier trains on your inputs.

ChatGPT’s consumer Plus and Pro prices are omitted because openai.com’s pricing page could not be verified as of September 2026. The cheapest defensible set-up for client work is therefore $20-$25 per lawyer per month on a business tier, the subject of ChatGPT Business vs Enterprise for law firms.

Legal platforms: published and reported ranges

None of the four big platforms publishes a price. The reported ranges, with sources:

• Harvey. $1,000-$2,000 per user per month for mid-market firms of 50-200 lawyers; $100-$200 at Am Law 100 scale; seat minimums around 25-50; 12-month terms; renewal uplifts of 10-25% without a cap. The Legal Prompts, which compiled these, calls them “a planning range, not a quote” (The Legal Prompts). JuriScout, a German comparison site, reports $1,200-$2,000 per seat with a 20-seat minimum.
• Legora. About $3,000 per user per year with a 10-seat floor, per JuriScout; the Reddit poster’s friend was quoted about $400 per user per month.
• CoCounsel Legal. $104-$639 per user per month for firms up to 10 attorneys via the configurator (GC AI); $637-$784 per attorney per month self-serve (The Legal Prompts), which estimates a 25-person deployment at about $265,000 in year one.
• Lexis+ with Protégé. All-in quotes of $250-$500 per seat per month on annual auto-renewing contracts, per Vaquill, a competitor; unconfirmed by LexisNexis.
• Clio Work $199 per user per month and GC AI $500 per seat per month, both published.

What each platform does for that money is in Harvey vs Legora vs CoCounsel vs Protégé. Germany has its own spread: Lulius at EUR 99 a month, Beck-Noxtua at EUR 1,050 a month for three licences, Harvey at roughly $14,400 per user per year, a hundredfold range for “legal AI” (figures from Lulius, a competitor, so treat with care). The DACH options are in legal AI tools for Germany, Austria and Switzerland.

Word-native and niche tools

The tools that live inside Word are priced for individuals and mostly reported rather than published. Spellbook is reported at $99-$199 per user per month, and Justin Monahan of KMSC Law says “Spellbook probably helps me bill an extra hour a day. Maybe more.” Claude for Word is a Team and Enterprise beta, so its price is the Team seat; Microsoft’s Legal Agent in Word arrives through the Frontier early-access programme for Microsoft 365 Copilot, and no separate price has been published.

Two categories went free in 2026: Relativity folded aiR for Review and aiR for Privilege into standard RelativityOne at no extra charge, and Everlaw made its single-use AI Assistant features free as well. Citation checkers cost little: CaseRead is free up to 50,000 characters and GroundTruth is a free Word add-in.

What the Reddit innovation committee was quoted

The most useful detail there is not a price: a 120-user midsize firm chose Microsoft Copilot licences “while the market kind of sort itself outs”, which is the cheapest rational response to price opacity: buy the layer you can price, wait on the layer you cannot.

Seat minimums, renewals and the volume-discount paradox

The headline seat price is the least important number in a platform quote. Three other terms decide what you pay.

Seat minimums. Harvey is reported at 25-50 seats (JuriScout says 20), Legora at 10. For a firm of eight lawyers the real price is the minimum times the rate: ten Legora seats at the reported $3,000 a year is $30,000 before anyone logs in.

Renewal uplifts. The Legal Prompts reports Harvey uplifts of 10-25% at renewal with no cap; Vaquill describes Lexis contracts as annual and auto-renewing. An uncapped uplift on a 12-month term makes the year-one price a teaser. Negotiate the cap before the discount.

The volume-discount paradox. Harvey’s reported discounts start above roughly 100 seats, which The Legal Prompts calls “structurally optimized for exactly the firms that need discounts least”. The mid-market firm pays the most per lawyer, which is a reason to cost the alternative stack below before signing.

Here is a legal AI vendor's proposal and order form: <proposal>...</proposal>. Extract into a table: Seat price and currency | Minimum seats | Contract term | Renewal mechanism (auto-renew? notice period?) | Uplift at renewal (capped? at what?) | Usage or token limits and overage rates | Training-on-our-data clause (quote it) | Retention and deletion at termination | Data export format and any export fee | Subprocessors and regions | Termination for convenience.
Where the proposal is silent, write NOT ADDRESSED. Then list the five terms to negotiate first, ranked by financial impact over three years, with the arithmetic.

Metered tokens: Fable 5 pricing and cost control

A new line is appearing on invoices: consumption. Ahead of Anthropic’s expected July 2026 shift of Claude Fable 5 to metered usage at about $10 per million input tokens and $50 per million output tokens, roughly twice Opus 4.8 at $5 and $25 (both confirmed on Anthropic’s pricing page in September 2026), Carolyn Elefant wrote an ethics opinion on it; Legora announced consumption-based pricing in the same period, and Artificial Lawyer predicted large-firm token bills “could reach millions of dollars” (MyShingle). Residency has a price too: Anthropic’s US-only inference option costs 1.1x, and OpenAI’s in-region European inference carries a 10% uplift on newer models.

The sums stop being small when an agent re-runs a 400-page data room twenty times. Elefant’s cost-control list is the answer: match the model to the task, chunk long documents and ask targeted questions (“Run a 50-page contract in sections”), set spend caps and per-matter budgets, limit agent re-runs, and audit dollars spent against hours saved.

Three budgets for a five-lawyer firm

Illustrative monthly figures at list or reported prices, in US dollars, before VAT and negotiation, for a firm already on Microsoft 365 or Google Workspace.

Level 1 is not a compromise: it is close to what Zack Shapiro’s two-person, Claude-native firm runs, and the Vals research benchmark of October 2025, as written up by LawNext, found plain ChatGPT matching the legal research tools on accuracy. Level 3 is a research decision, not a status purchase. The first thirty days at any level are in the AI plan for solo and small firms.

Data extraction fees and lock-in

The price you are not quoted is the price of leaving. Clio’s own data, relayed by the North Carolina Bar Association, puts reported data extraction fees at GBP 12,888 in the UK and A$24,861 in Australia (NC Bar), a preview of what platform exit fees could look like.

Consolidation adds a second exit risk. Harvey made four acquisitions in 2026, Legora five, and Robin AI went from a failed $50m raise to seeing its engineers hired by Microsoft within three months. So the contract questions are: export in open formats at no charge; deletion at matter end and at termination, in writing; a change-of-control clause that lets you leave; and no uplift without a cap.

Can you pass any of this to clients?

The ethics opinions have converged, and the answer is mostly no.

Elefant’s July 2026 opinion draws the usable line: subscriptions may never be billed; metered charges only when attributable to a specific matter, at actual cost, without markup, disclosed in advance in writing. Clients are writing the same rule into outside counsel guidelines; Poppy Legal’s sample clause bars markup on AI costs and suggests the invoice notation “AI-assisted; attorney reviewed”.

Draft a plain-English clause for our engagement letter under [jurisdiction] rules covering AI costs. Encode: our AI subscriptions are overhead and never billed; hourly matters are billed for actual time only, including time instructing and reviewing AI, never reconstructed "equivalent time"; metered AI charges directly attributable to this matter are billed as an expense at actual cost, without markup, itemised, only with prior written consent; if actual cost cannot be attributed, no charge is made. Add one sentence on our verification commitment. Under 180 words. Then list the [jurisdiction] ethics rules to check it against, tagged [VERIFY].

The bigger money is on the other side of the ledger. Bryce Tarling’s arithmetic for Clio: “If a matter used to take five hours and AI brings it down to one, hourly billing means you’ve just handed your client an 80% discount they never asked for” (ABA Law Technology Today). Clio’s 2026 data says 86% of solos and 78% of small firms have not changed pricing since adopting AI; against that, the subscription is a rounding error. The repricing question is the subject of AI and the billable hour; this prompt is the first step.

Help me price [a standard NDA review / a simple will / a residential closing] as a flat fee. Here is our time data for the last [20] such matters: <data>...</data>. Compute the mean, median and 80th percentile of hours and cost at our rates, before and after we started using AI on this matter type; identify the three drivers of outliers; propose a scope definition with explicit exclusions; propose a flat fee at a [target margin] with an add-on schedule for the exclusions; and draft a two-paragraph client-facing scope description. Show the arithmetic in a table; I will check it.

The expensive decision is not which tool to buy but whether you can use the $20-$200 tools well enough to know what you are missing. That is what the four live sessions of AI Lab for Lawyers are built around, on your own documents and without code, so a platform demo becomes a comparison rather than a revelation.

Where to go next: the legal AI tools map places every tool here in its layer; general AI versus legal-specific tools is the argument behind Level 1; the prompt library has the three prompts above ready to paste; and the tools cluster has the rest.