ML Env

Use casesMarketing

Rewrite all our copy in one consistent brand voice

Rewrites copy accumulated from different writers over the years into one consistent voice, batch by batch, anchored to your voice guide and best examples.

How it works
It takes copy written over the years by different staff, freelancers and suppliers and rewrites it batch by batch into one voice. Retrieval anchors every rewrite against your voice guide and gold-standard examples, so the model imitates rather than invents. Typical targets are old product pages, category texts, help pages and email templates.
Data you need
A written voice guide, or failing that 10-30 texts you consider perfectly 'you', plus the corpus to rewrite in exportable text form. If neither exists, this case is weak — 'make it sound like us' with no examples produces generic polish.
What to expect
The aim is a more uniform voice; how close it gets depends on the quality of your examples. Factual drift is the main risk — a 30-day guarantee quietly becoming a 'generous guarantee' is a real failure mode, so numbers, guarantees and legal wording must be locked and diff-checked. The model also smooths away deliberate quirks along with accidental ones, so flag anything intentionally odd. For pages that already rank in search, wholesale rewording can shift keyword usage and affect rankings — rewrite those in small batches and monitor. Getting the rewritten text back into your shop system is a separate import step this does not do for you.
Where people stay involved
Review rewrites as diffs against the original, because rewriting can silently change factual meaning. Sign off per batch.

Which model, and what it costs to run

Qwen3-8B

No public benchmark ranks this particular job, so this is not a leaderboard pick — it is where we would start: small, permissively licensed, and strong wherever it has been measured. We prove it on your own content before anything ships.

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.

Writing in your voice

No benchmark measures this

There is no benchmark for this and there is unlikely ever to be one. Anyone who shows you a chart ranking models on marketing copy has drawn it from a model's opinion of another model.

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.

  1. 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.

  2. 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.

  3. 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.

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