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.
- How it works
- Bank statement lines are compared against your open-invoice list, targeting exactly the cases that break exact matching: mistyped references, a customer paying from a different company name, two invoices in one transfer, small over- or underpayments. Amount arithmetic — which invoice combinations sum to the payment — is computed by plain code, not the model. The language model judges only the fuzzy evidence, such as whether the payer name plausibly belongs to a customer, and each proposal shows its reasoning ('amount equals invoices 2041+2042; payer name resembles the delivery contact'). Bank data stays on your own EU-hosted hardware throughout.
- Data you need
- A bank statement export and an open-invoices export (number, customer, amount, due date). Both exist in any accounting package.
- What to expect
- The value is only in the messy tail — exact-reference matches don't need a language model, and your accounting software already does those. The model can propose a confidently wrong match when two customers owe similar amounts, which is exactly why confirmation stays manual; with a very long open-invoice list, some proposals are little better than guesses and belong in the manual pile.
- Where people stay involved
- A person confirms every proposed match before reconciliation is booked. Anything the model marks uncertain stays in the unmatched pile for manual handling.
Which model, and what it costs to run
Qwen3-32B
This job runs in bulk rather than to a waiting person, so size is not the constraint — we take the strongest independent score on structured output and tool calls that we may serve freely and that fits on a single card.
- Licence
- Apache-2.0
- Weights at 4-bit
- 18 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
- $0.12 / $0.12per M in / out · Nebius AI Studio · EU
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.
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.
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
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.
Draft payment reminder letters that sound like you
Drafts overdue-invoice reminders in your tone and your customer's language, escalating from friendly nudge to final notice.
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.