Pleias 3B Preview

Overview

A French 3B from PleIAs trained 100% on Common Corpus open data, designed for EU AI Act compliance by construction. Fully traceable training data, Apache 2.0.

When to pick this model

• You need EU AI Act compliance with auditable training data
• You're shipping into regulated industries that require provenance
• You want a small French-capable model under Apache 2.0
• You're building tooling where data lineage matters more than raw benchmarks

VRAM requirements by quantization

Quantization	VRAM required
Q4_K_M (recommended)	2 GB
Q5_K_M	2.5 GB
Q8_0	3.5 GB
FP16 (no quantization)	6 GB

VRAM figures include model weights plus a typical 8k KV cache and ~600 MB runtime overhead (Ollama / llama.cpp baseline). Add headroom for higher context lengths.

Strengths

• EU AI Act compliant by design
• 100% traceable training data (Common Corpus)
• Apache 2.0
• Compact 3B footprint

Limitations

• Modest benchmark scores vs general-purpose 3B peers
• Context window of only ~2K
• Narrower capabilities than mainstream open models

Architecture & training

Architecture: Dense Llama/GPT-NeoX-style · trained from scratch

Training: ~1.08T tokens on Common Corpus (100% open-licensed data).

Quick start

# HuggingFace : PleIAs/Pleias-3b-Preview

Or use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.