Find the clause in your contracts — and read it in context
Ask a plain question about your signed contracts and get the actual clause back, quoted, with a pointer to the document and section.
- How it works
- You ask 'what's the notice period on the warehouse lease?' or 'which supplier contracts let us terminate for late delivery?' and the system retrieves the relevant passages from your own contract files using multilingual embeddings and a reranker. The large model then quotes the clause and briefly explains it, with a pointer to the exact document and section. It is a lookup tool over documents you already signed — not legal advice, and it should say so in its own answers.
- Data you need
- Your contracts as digital text — Word files or PDFs with a text layer. Contracts that exist only as scans need OCR first; contracts sitting in a drawer don't exist for this system at all.
- What to expect
- Fast at finding the passage, which is its whole job. Retrieval can miss a clause that's phrased unusually or split across an amendment and the main contract — cross-references and side letters are a known weak point. The model may summarise a clause too generously; the quoted original text, not the paraphrase, is what you rely on.
- Where people stay involved
- Always read the quoted clause yourself before acting on it; for anything with money or liability attached, that reading is your lawyer's job.
Which model, and what it costs to run
Qwen3-8B
This job answers while someone waits, so latency comes first: we hold it to a single small card and, within that, take the best independent score on sticking to the document.
- Licence
- Apache-2.0
- Weights at 4-bit
- 5 GB
- Context
- 32K tokens
- Publisher
- Alibaba (Qwen Team)
What the hardware costs
One 48 GB card holds it
- Rent in the EU
- $1.60/hrScaleway, Paris (PAR2)
- Buy the card
- $7,569new, one-off
- Or rent it by the token
- $0.04 / $0.04per M in / out · DeepInfra
Hardware only, third-party prices from 2026-07. The figure excludes the KV cache, which grows with context length and how many people use it at once — sized properly in a conversation, not guessed here. Renting by the token is cheaper up front; why our customers still self-host is below.
Sticking to the document
Measured on public documents, by a model acting as judge. Read it beside the answer rate: the lowest hallucination rates on this board belong to models that simply decline more often.
Independent measurement · Vectara · board updated May 11, 2026
Structured output and tool calls
Measured in a sandbox, on somebody else's functions. It tells you which models are capable of the shape of the job, not which one will survive contact with your API.
Independent measurement · UC Berkeley (Gorilla project) · board updated 2026-04-12
Reading a long document whole
No benchmark measures this
No current benchmark ranks today's open models here. HELMET showed that the popular test — finding a planted sentence — predicts nothing, and its own table has not been rerun on 2026 models.
So we do not show a chart here. We measure it on your own content, in the first week, and you see the result before anything ships.
The API is cheaper per token. Here is why our customers don't use it.
We will not pretend otherwise: renting a model by the token from a serverless API costs less per million tokens than a card we run for you. We show that price on every use-case page. What it does not include is the part a shop with a customer database actually pays for.
- 01
Your data never leaves hardware you can point at
A serverless "we don't retain your data" is a clause in a contract. Running the model on a card in Amsterdam is a fact of architecture: your catalogue, tickets and customer records are never sent to a third party at all. For a GDPR audit, that is the difference between a promise and a floor plan.
- 02
The price cannot move without your say-so
A serverless rate card is somebody else's lever. The provider can raise the price, retire the model, or change the terms, and your cost moves with it. The same model on the same card costs the same next year — you own the number.
- 03
The model cannot be taken away
Hosted APIs deprecate models on their own schedule; the one you built on can be gone in a quarter. An open-weight model on your own hardware runs for as long as you keep the lights on. No vendor can end-of-life it out from under you.
And the price gap closes with volume: past a card you keep busy — very roughly four billion tokens a month — owning is cheaper outright, even before the three reasons above.
Getting a case like this one from a conversation to production takes about two months, and you can stop at the end of any phase.
Also in finance & admin
All 15 →Pull the details off supplier invoices into your bookkeeping
Pulls supplier name, invoice number, dates, line items and VAT out of PDF invoices into records your accounting software can import.
Turn expense receipts into draft expense entries
Turns OCR'd receipt text into draft expense entries — merchant, date, amount, VAT and likely category — for the submitter and finance to confirm.
Sort expenses into your bookkeeping categories
Reads cryptic bank and card descriptions and proposes a category from your own chart of accounts, backed by your past bookings as evidence.
Match incoming bank payments to open invoices
Proposes matches between bank statement lines and open invoices when references are mistyped, names differ or one transfer covers two invoices.
Next
Tell us what your team does by hand
Describe the process that takes the most time. We will say plainly whether a model is the right tool for it.