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llmradar/eu-open-weight-models

EU-readiness of open-weight LLMs Curated by LLM Radar — updated 2026-05-03 — 55 models. A manually-reviewed dataset assessing open-weight Large Language Models (LLMs) on their suitability for EU deployment and commercial use. Each model is evaluated on licence, commercial use, training data, and origin, with quality / speed / price metrics from Artificial Analysis where available. Primary use cases: Selecting open-weight models for self-hosted EU deployment Licensing and… See the full description on the dataset page: https://huggingface.co/datasets/llmradar/eu-open-weight-models.

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Dataset Card

EU-readiness of open-weight LLMs

Curated by [LLM Radar](https://llmradar.eu) — updated 2026-05-03 — 55 models.

A manually-reviewed dataset assessing open-weight Large Language Models (LLMs) on their suitability for EU deployment and commercial use. Each model is evaluated on licence, commercial use, training data, and origin, with quality / speed / price metrics from Artificial Analysis where available.

Primary use cases:

—Selecting open-weight models for self-hosted EU deployment
—Licensing and commercial-use due diligence
—Training classifiers on open-source LLM licensing and provenance
—Tracking the emergence of EU-origin and permissively-licensed models

Fields

column	description
`name`	Human-readable model name
`vendor_name`	Publisher / research lab
`vendor_country`	HQ country of the vendor
`verdict`	Overall verdict: `ok`, `warn`, or `ko`
`verdict_text`	One-line editorial verdict
`licence`	Licence summary (Apache-2.0, MIT, custom, etc.)
`commercial_use`	Commercial-use posture
`training_data`	Training-data disclosure / provenance
`origin`	Origin / publisher jurisdiction
`tags`	Comma-separated topic tags (`permissive`, `commercial`, `euorigin`)
`quality_index`	Artificial Analysis Quality Index (0–100, higher is better)
`output_tokens_per_second`	Median output speed (tokens/s)
`blended_price_per_m`	Blended input+output price per million tokens (USD)
`context_tokens`	Advertised context window
`last_reviewed_at`	ISO date of last manual review
`llmradar_url`	Canonical URL of the full model page
`slug`	Stable identifier on LLM Radar

Performance metrics (quality / speed / price) are sourced from Artificial Analysis under their public API and are attributed there; see their terms for reuse.

Methodology

Each entry is reviewed manually against public sources (provider docs, terms of service, data-protection agreements, sub-processor lists, regulator guidance, model cards, and vendor statements). Badges use a three-tier traffic-light scheme:

—green — meets the EU/GDPR/AI-Act criterion without material caveats
—amber — partial fit, conditional, or requires customer action to qualify
—red — does not meet the criterion, or requires data transfer outside the EEA

See the full methodology at https://llmradar.eu/methodology.

License & attribution

Released under CC BY 4.0. You may share and adapt the dataset for any purpose, including commercial use, provided you give appropriate credit and link back to the source:

Data from LLM Radar — https://llmradar.eu — licensed under CC BY 4.0.

Updates

This dataset is regenerated on a weekly cadence from the LLM Radar editorial database. Each row carries a last_reviewed_at date so you can filter for recency.

Citation

bibtex

@misc{llmradar_eu-open-weight-models,
  title        = { EU-readiness of open-weight LLMs },
  author       = { {LLM Radar} },
  year         = { 2026 },
  howpublished = { \url{https://huggingface.co/datasets/llmradar/eu-open-weight-models} },
  note         = { CC BY 4.0 }
}

Report corrections

Found an inaccuracy? Submit a correction or exercise your right of reply at https://llmradar.eu/corrections or https://llmradar.eu/right-of-reply.