---
title: "Chinese open-source AI in the enterprise: the numbers add up, so do the risks"
description: "DeepSeek, Qwen, GLM and Kimi have passed 45% of global AI traffic at a fraction of the cost of US models. What to weigh before using them safely."
url: https://csidia.com/en/notes/modelli-cinesi-open-source-in-azienda/
lang: en
date: 2026-05-14
label: "Scenarios"
publisher: CSIDIA S.r.l. (https://csidia.com/)
italiano: https://csidia.com/note-operative/modelli-cinesi-open-source-in-azienda/
---

# Chinese open-source AI in the enterprise: the numbers add up, so do the risks

A year ago, Chinese AI models accounted for less than 2% of global traffic. By April 2026 their combined share had passed **45%**: DeepSeek with the new V4 family, Alibaba’s Qwen, Z.ai’s GLM, Moonshot’s Kimi. Many are released with open weights, cost a fraction of the American alternatives, and match them on several tasks. For a European SME the temptation is strong — and partly justified. But the decision has to be made knowing exactly what you are choosing. Let’s lay out the facts.

## Why everyone is talking about it

Three concrete reasons: **cost** (Chinese APIs cost up to ten times less; open weights, run on your own hardware, bring the cost per token to zero), **openness** (downloadable weights mean no lock-in, the ability to specialise the model on your own data, and operation even without connectivity) and **pace of improvement** (releases follow one another at a rate of weeks). For well-defined enterprise tasks — document classification, data extraction, internal assistants — a well-chosen open model is often more than sufficient.

## The risks, without alarmism but without discounts

1. **Where the data goes.** If you use a Chinese provider’s *APIs*, prompts and responses pass through servers subject to Chinese legislation. For the personal data of European citizens this is a concrete GDPR problem, even before it is a strategic one. This risk concerns the APIs, **not** open weights run in-house.
2. **What the model answers.** Estonia’s foreign intelligence service has documented that, on topics sensitive to Beijing, DeepSeek omits information and inserts elements of propaganda. For an industrial use case (reading a production log) this is irrelevant; for an assistant answering open questions, much less so.
3. **The geopolitical tap.** Beijing is considering limits on foreign access to its most advanced models; Washington is pushing in the opposite direction with its own providers. Anyone building business processes on a model has to ask: *what do I do if it is no longer available tomorrow?*

## The sensible path: open weights, your own premises, a replaceable architecture

For a European company, the configuration that captures the benefits while cutting the main risks is well known: an **open-weight model run on-premise or on a European cloud**, inside your own infrastructure. Data does not leave, the applicable legislation is European, and the model remains available even if the provider changes policy — downloaded weights cannot be revoked.

The condition almost everyone forgets: **the architecture must treat the model as a replaceable component.** The value does not lie in the model — which will be superseded within six months, whoever produces it — but in the *context* you give it: your connected data, the [operating model](https://csidia.com/en/platform) that makes it legible, the controls over what the AI is allowed to do. Those who build this way can use a Chinese model today, a European one tomorrow, an American one the day after, changing one component rather than the system. Those who instead hard-wire their processes to a single provider have turned a tactical choice into a strategic dependency.

## Checklist before deciding

- Does the use case touch **personal or confidential data**? Then foreign APIs are excluded: open weights in-house, or a provider with European guarantees.
- Is the task **well-defined and verifiable** (classifying, extracting, summarising)? Open models are excellent candidates.
- Have you defined **how to measure quality** before choosing the model? The benchmark that counts is on your own documents, not the published one.
- Does the AI’s action have **operational consequences**? Then a human operator needs to be in the loop, whatever the model — [it is the rule we never bend](https://csidia.com/en/operational-ai).

*Weighing up an open model for a concrete use case? [Let’s talk](https://csidia.com/en/contact): half an hour to see whether the numbers really add up.*

## Sources

- [DeepSeek — open weights on Hugging Face](https://huggingface.co/deepseek-ai)
- [Qwen (Alibaba) — open weights on Hugging Face](https://huggingface.co/Qwen)
- [Estonian Foreign Intelligence Service — annual security reports](https://www.valisluureamet.ee/en.html)

Note by CSIDIA S.r.l. (Vignola, MO, Italy): https://csidia.com/en/notes/modelli-cinesi-open-source-in-azienda/ · Who we are and what we do: https://csidia.com/en/at-a-glance/ · engagement@csidia.com