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Open weightsSwiss AI Initiative (ETH Zurich, EPFL, CSCS)/10 trustVerified
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Apertus-8B

Switzerland's fully open 8B multilingual LLM, trained on 15T tokens across 1,000+ languages.

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About

Apertus-8B is the smaller of the two models in Apertus 1.0, released September 2, 2025 by the Swiss AI Initiative (EPFL, ETH Zurich, and CSCS on the Alps supercomputer). It was trained on more than 15 trillion tokens spanning over a thousand languages with roughly 40% non-English content, and the release includes weights, training code, intermediate checkpoints, and dataset documentation.

Everything is Apache 2.0, including commercial use, and the project was built to respect GDPR, the EU AI Act, and Swiss data-protection law. The honest caveat from launch coverage: the first iteration trails frontier models on raw capability, and chat is a secondary use case — this is a research and sovereignty play more than a ChatGPT replacement.

Specs

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Pricing

Free (open weights); hosted APIs via Swisscom, Public AI, AWS, Azure

Free quota

API access

Swisscom, Infomaniak, Public AI, AWS SageMaker, Azure; self-host via vLLM/SGLang

Weights

Open weights

Released

September 2, 2025

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

researchothers

Trust score — 8/10

/10 trustVerified

Scored 8/10 (verified tier, metrics-v1). Evidence: Public-institution release (EPFL, ETH Zurich, CSCS); hosted by Swisscom, Public AI, AWS, Azure; Fully open: weights, code, checkpoints, training data documentation; Launch coverage notes first iteration trails frontier models; chat is a secondary use case. License: Apache 2.0.

How the trust score is built

Full methodology →
Adoption · stars/downloads, log-scaled vs peers
6.0/10
Maintenance · recency, releases, issue load
8.0/10
Openness · license + docs
10.0/10
Manual review · sanity read + red-flag check
8.0/10
  • · Public-institution release (EPFL, ETH Zurich, CSCS); hosted by Swisscom, Public AI, AWS, Azure
  • · Fully open: weights, code, checkpoints, training data documentation
  • · Launch coverage notes first iteration trails frontier models; chat is a secondary use case

More in the apertus family

Sources