ML Env

Use casesMarketing

Adapt product and campaign copy for other EU markets

Translates and adapts your product copy, emails and ads into other EU languages, with a glossary protecting brand terms, on EU-resident hardware.

How it works
It translates and adapts your product descriptions, emails and ads into other EU languages, using a glossary so brand and product terms stay untouched. For German, French, Spanish, Italian and Dutch, the realistic expectation is output a native speaker edits rather than retranslates — verify that on your own copy for each language pair before relying on it. Everything runs on EU-resident hardware in Amsterdam, which matters if the copy quotes customer content.
Data you need
Source copy; a glossary of terms not to translate — brand names, product lines, technical terms — which most small firms don't have yet but can build up during the first review rounds; and per-market notes such as formal versus informal address, local units and currency.
What to expect
Major EU languages are strong but not native; smaller languages such as the Baltic languages or Finnish are noticeably weaker — test before committing. Idiom and humour translate worst. Without a glossary, brand and product terms may get translated inconsistently until one is built. And translation is not localisation: consumer-law wording genuinely differs per country, and the model will not warn you.
Where people stay involved
A native or fluent speaker reviews anything customer-facing before publishing, without exception, checking against the source rather than just for fluency — prices, specs and claims can drift in translation. Legal wording on guarantees, returns and price presentation must be localised by someone who knows that market's rules.

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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