Helium 1 2B

Overview

Kyutai's 2B multilingual base covering all 24 EU languages, distilled from Gemma 2 — which means Gemma Terms apply on top of CC-BY-SA. Beats Qwen 2.5 1.5B, Gemma 2B, and Llama 3.2 3B at its scale.

When to pick this model

• You need a small multilingual base for fine-tuning across EU languages
• You're building edge or embedded deployments with French as a priority
• You want a European base model with strong sub-3B performance
• You're doing pre-training research and need a clean small foundation

VRAM requirements by quantization

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

• Compact multilingual base from a European lab
• Covers all 24 EU languages
• Beats Qwen 2.5 1.5B, Gemma 2B, and Llama 3.2 3B at its scale
• Built by Kyutai

Limitations

• CC-BY-SA 4.0 plus Gemma Terms via distillation
• Base model — not instruction-tuned
• No official Ollama support

Architecture & training

Architecture: Dense · GQA · RoPE · distilled from Gemma 2

Training: 2.5T tokens, 24 EU languages.

Quick start

# HuggingFace : kyutai/helium-1-2b

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