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Bielik or PLLuM in a Company: Hardware and GDPR

Short answer

Bielik 11B or PLLuM 12B in 4-bit quantisation takes about 7 GB of GPU memory, so it fits on Hetzner's cheapest GPU server with 24 GB. That server costs €214 a month net, and with 8 hours of upkeep about €493. At documents with 3,000 input tokens and 1,000 output tokens, the Claude Sonnet 5.5 API is cheaper up to about 34,500 documents a month.

How we workDetails ↓

  1. 01Call30 minutes with an engineer, free
  2. 02PrototypeA working system on your process and data, free
  3. 03ImplementationTarget and fixed price in the contract; 50% at signing
  4. 04Acceptance50% once the agreed target is met
analysis with an engineer and a free prototype
€0
team in ChatGPT or Claude, up to 10 people
from €1,150
automation, agent or application for one process
from €3,000

We belong to the OpenAI and Anthropic partner programmes and learn through their official courses. What this means ↓

Author: Syntalith · 4 min read

Example: the morning request inbox
Agent · ready

Statistics

Polish AI models in companies: statistics 2026

34,500

documents a month, from which a 24 GB GPU server with upkeep at €493 comes out cheaper than the Claude Sonnet 5.5 API. Scenario.

Figures checked: 22 October 2026

How much GPU memory a model takes

As much as the weights weigh at the chosen precision, plus headroom for context. In bf16 each parameter takes 2 bytes, in 8-bit one, in 4-bit about half a byte. Add 15 to 25% to the result for context memory and driver overhead.

Modelbf168-bit4-bitOn 24 GB?
Bielik 4.5B~9 GB~4.5 GB~2.7 GByes, even in bf16
PLLuM 8B, Llama-PLLuM 8B~16 GB~8 GB~4.7 GB4-bit with room to spare
Bielik 11B, PLLuM 12B~22–24 GB~11–12 GB~6.5–7 GB4-bit with room to spare
PLLuM 8x7B~94 GB~47 GB~26–28 GBno, it needs 48 GB or more
Llama-PLLuM 70B~140 GB~70 GB~40–43 GBno, it needs 96 GB

A 24 GB card handles the whole middle of both families in 4-bit. Only the 70B model needs a server with 96 GB.

Where the 48 GB in the PLLuM table comes from

The PLLuM infrastructure page gives the requirements for production serving: about 34 GB for the 8B model, 48 GB for 12B, 70 GB for 24B, 134 GB for 8×7B and 168 GB for 70B, plus 24 to 48 GB for search and the reranker. These are numbers without quantisation, with headroom for many users at once. Both sets of numbers are true and describe two different deployments.

Quantisation costs quality. No measurement of that cost has been published for Bielik and PLLuM, so the only sound procedure is a few dozen tasks from your process run in bf16 and in 4-bit. That is a day or two of work.

What a GPU server in the EU costs

Hetzner GPU servers, a month net in euros

Prices on 22 October 2026, with an IPv4 address, without the one-off setup fee.

GEX45, 24 GB€214
GEX63, 96 GB€999
GEX131, 96 GB€1,499

Źródło: Hetzner, GPU servers (2026) ↗

The GEX45 has an RTX PRO 4000 Blackwell card with 24 GB and is available in Helsinki. The GEX63 and GEX131 have an RTX PRO 6000 Blackwell with 96 GB. The one-off setup fee is €209, €999 and €1,499 respectively. The €889 price from the December 2025 press release about the GEX131 is out of date. Add disk space for models and the index, backups, monitoring and a second machine for a test environment to the count.

When your own server is cheaper than the API

Scenario: a document with 3,000 input tokens and 1,000 output tokens
GEX45 server
€214 + 8 h of upkeep (€279) = €493
GEX63 server for the 70B model
€999 + upkeep = €1,278
One document on the Claude Sonnet 5.5 API
$0.016 (€0.0143)

Break-even: about 34,500 documents on the GEX45, 89,500 on the GEX63

Price of the GEX45 server with 24 GB of GPU memory from Hetzner's page on 22 October 2026, without the one-off €209 fee. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. The API at Anthropic's rates, at the ECB rate of 1.1205 USD per euro on 22 October 2026. The upkeep time and the document size are the scenario's assumptions. The local model's quality must be comparable, which you check with a test.

Below the threshold the API is simpler and cheaper. On Claude Haiku 5.5 a document costs twenty times less than on Sonnet 5.5, so the threshold rises to hundreds of thousands of documents. A Polish model on your own server usually wins on the requirement that data does not leave the company. We cover this in more depth in a Polish model or an API.

What about GDPR

Where the obligations sit
  • Your own server room

    no transfer

    PLLuM assumes a fully on-premise deployment, with the data in the institution's infrastructure.

  • Hosting in the EU

    a data processing agreement

    Hetzner runs data centres in Falkenstein and Helsinki. An Article 28 GDPR agreement is a condition for the start.

  • Always with the company

    the record and access

    Legal basis, impact assessment, access control, log retention and training.

With Bielik, the terms of use add to the obligations: version 1.1 of 31 July 2025 forbids using the model to process any personal data, so HR documents and customer data need another model or a clarification with the SpeakLeash foundation. A model in the company's server room does not change who has the right to see HR documents. Isolation levels from the cloud to air-gap are described in on-prem and air-gap.

When not to host the model yourself

Choose the API if
  • You have a few hundred documents a month
  • The task needs hard reasoning or code
  • Nobody in the company will maintain the server, the drivers and the model
  • You want to check first whether the idea works
  • Data may be processed by a vendor with a data processing agreement in the EU

Every new model version means fresh quantisation, a test set and a check of the instructions. We deliver this work as part of private LLMs: deployment, tests on your tasks, monitoring and upkeep. We price the build from €3,000 net and upkeep individually. The variants' licences are covered in the article on PLLuM in a company.

This is how we implement it in companies

All case studies →

Client results.

All projects →
foap.comcustomer service

foap.com customer service: 95% of replies are sent automatically.

Users from several countries write to foap.com, in several languages. The system reads the entire conversation and the terms of that person, and then sends a response in that person's language. Questions about money and exceptions go to the team with a ready draft, so they have to check and send them.

the system sends the answers itself, without human typing
95%
time from the arrival of the e-mail to the ready response (median)
30 s
e-mails that require a response receive a ready-made draft
100%
less work for every 1000 answers (estimate)
47 h

Data from foap.com production, October 20-21, 2026. Estimate: 3 minutes for handwritten response.

How foap.com customer service works →
Sample messages. Money matters always come to the person.

Other implementations

jaktako.design

studio projektowe

−87%

Time to look for new customers, every day

4 hours → 30 min

approx. 73 hours less per month (21 days of work)

according to the studio

How the agent loop works →
Signature Estates

real estate

approx. −90%

Operator time spent browsing portals, per day

2–3 hours → 20 min

approx. 45 hours less per month (21 days of work)

respect · contact the seller 5 minutes after the announcement

How the agent finds property listings →
Kuba Koziej, CEO and co-founder of MoreGrowth and board member at Natu.Care

Kuba Koziej

CEO and co-founder, MoreGrowth

„We started with my own AI agent. During the training that followed, I learned to build new applications myself. Today I am bringing this way of working with AI into my business. Working with Syntalith gave me exactly the skills and tools I needed.”

View the original training review on LinkedIn ↗

Start with the process that takes the most time each week.Book a free process review (30 min) →

How we build automation and agents

From a conversation to a working system in four steps.

  1. 01 · 30 min

    Free process review

    €0

    You're talking to an engineer. You receive the written plan within 2 business days.

  2. 02 · 5 days

    Free prototype

    €0

    The system works on 20-100 cases that your team has already handled. You see every result.

  3. 03 · 2–16 weeks

    Build

    50%

    Fixed price and goal written in the contract. First installment upon signing.

  4. 04 · after reaching the goal

    Reception

    50%

    You pay the second installment when the system reaches its target on your cases.

How a free prototype is created

Mon.

We set a goal

What result do you consider good?

Tue–Wed

The system is working

It goes through your affairs, one by one.

Thu

We compare

We check every difference with the team's work.

Fri

Result and price

List of errors and fixed implementation price.

You choose the matters. We anonymize them upon request, they stay in the EU and we delete them after the test.

On the market, such a test usually costs from PLN 3,000 to PLN 8,000.

Book a free process review (30 min)

We establish a prototype during a free analysis.

Data checked on October 25, 2026.

„Is my data safe?”

Yes. You choose where they go: from your company account to the model on your server.

  1. 00Employee's private account

    Customer and company data ends up in an account that the company cannot see or control. There is no data processing agreement, so it is a violation of the GDPR. When an employee leaves, the chat history goes with them.

  2. 01ChatGPT or Claude corporate account

    The provider does not use your data to train models. A copy of the queries remains in his logs for up to 30 days.

  3. 02API with zero retention (ZDR)

    The provider processes the request and does not save anything. It requires his consent, we prepare the application together.

  4. 03Processing in the EU

    Queries are counted and stored in Europe: OpenAI in the EU region, Claude via clouds with the EU region.

  5. 04Model at your place

    The open model runs on your server or in your cloud in the EU. The data does not go outside the company.

What we do with every implementation

  • Confidentiality agreement and data processing agreement before we receive any data.
  • You choose the cases for the prototype and we anonymize them upon request.
  • The data stays in the EU and we delete it after the test.
  • Corporate accounts with an administrator on your side.

When data cannot leave the company

The open model runs on your server or in your cloud in the EU. To choose from:

White-tailed eagle
Polish model, SpeakLeash and ACK Cyfronet AGH
PLLUM
Polish model, HIVE consortium commissioned by the Ministry of Digitization
Qwen
Alibaba
GLM
Zhipu AI
DeepSeek
DeepSeek

We select a model for the task and check it on your cases. We run it, tune it and maintain it.

Source: Bielik and PLLuM, ACK Cyfronet AGH ↗ · PLLuM, Ministry of Digitization ↗

Do you have a lot of your own data? We will fine-tune the small model.

  1. 1 Your examples
  2. 2 tuning
  3. 3 test on new cases
  4. 4 model at your place

When you have thousands of similar emails, documents or reports, we teach a small open model based on your examples. It works for you, responds quickly and costs less to maintain than a large model. We measure quality on issues that the model has not seen while learning.

Przemysław and Piotr did it in large programming and consulting companies. Artem did it before and does it today at Syntalith. It's about models on your own infrastructure, tuning and quality measurement.

You choose the protection level during the interview. We sign the data processing agreement before we see any data.Schedule a free analysis →

AI implementation

Start with the process that takes the most time each week.

The engineer chooses one process with you and calculates how much it costs today. Then we build a free prototype on 20-100 cases that your team has already handled. We write down the goal and the fixed price in the contract.

See AI implementation →
analysis with an engineer and a free prototype
€0
team in ChatGPT or Claude, up to 10 people
from €1,150
automation, agent or application for one process
from €3,000

Questions

  • How much VRAM do Bielik 11B or PLLuM 12B need?

    About 22 to 24 GB in bf16, 11 to 12 GB in 8-bit and 6.5 to 7 GB in 4-bit. The rule: 2 GB per billion parameters in bf16, 1 GB in 8-bit, about 0.5 GB in 4-bit, plus 15 to 25% for context.

  • How much does a GPU server in the EU cost?

    At Hetzner a GEX45 with 24 GB costs €214 a month net plus a one-off €209, a GEX63 with 96 GB €999, and a GEX131 with 96 GB from €1,499.

  • When is your own server cheaper than the API?

    At a large, steady volume. In the scenario with documents of 3,000 input tokens and 1,000 output tokens, a 24 GB server with upkeep beats Claude Sonnet 5.5 from about 34,500 documents a month. With Claude Haiku 5.5 the threshold is twenty times higher.

  • Why does PLLuM give 48 GB for the 12B model?

    The table on the PLLuM site describes production serving without quantisation, with headroom for many users. 4-bit quantisation reduces memory, but costs quality, which you measure with your own set of tasks.

  • Does your own server take care of GDPR?

    It settles the question of transferring data to an outside model vendor. The record of processing, the legal basis, access control, log retention and team training stay with the company. Hosting in the EU needs a data processing agreement.

Let's talk

Just write, call or choose a date.

We work fast because we hate corporate cotton wool. We don't have salespeople or managers to keep an eye on managers. You talk immediately to engineers who then build your system. We respect each other's time and yours too.

We will accept 3 more companies by the end of the year.

Mon–Fri 9:00–17:00 CET

What our OpenAI and Anthropic partnerships mean for you.

OpenAI makes ChatGPT and Anthropic makes Claude. We belong to the partnership programs of both companies, so we work with their tools every day and learn from the creators themselves.

OpenAI Select PartnerClaude Partner Network
01We will select a tool for the task
We implement both ChatGPT and Claude. We check both on your documents, and you choose the one that makes fewer corrections and saves more time.
02Knowledge straight from the creators
We learn from official OpenAI and Anthropic courses and materials. Your team learns about the features and settings that work today.
03Licenses without our margin
When we roll out ChatGPT, Claude or Copilot, you buy the licences directly from OpenAI, Anthropic or Microsoft and they invoice you. We add nothing to the licence.
04Certified engineers
On the team, we have an AWS certification in machine learning and an Anthropic certification in systems architecture on Claude.

Participation in programs does not mean that OpenAI or Anthropic endorses our services.