Model fiche
Salamandra 7B Instruct
By BSC · Spain
chat
general
multilingual
fr
Overview
Barcelona Supercomputing Center's 7.8B trained on 7.8T tokens covering 35 European languages and 92 programming languages — built for EU sovereignty under Apache 2.0.
When to pick this model
- EU-sovereign chat deployments
- Multilingual workloads spanning all 35 EU languages
- Code assistance across an unusually broad language set
- Public-sector projects requiring open European provenance
- Catalan, Occitan, and other low-resource Romance language use cases
VRAM requirements by quantization
| Quantization | VRAM required |
|---|---|
| Q4_K_M (recommended) | 5 GB |
| Q5_K_M | 6 GB |
| Q8_0 | 9 GB |
| FP16 (no quantization) | 16 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
- Backed by EU sovereignty and BSC infrastructure
- 35 European languages natively supported
- Apache 2.0 license
- Coverage of 92 programming languages
- 7.8T tokens of training data
Limitations
- 8k context falls short for long-document use
- No official Ollama distribution
- Quality trails frontier 7B models on English benchmarks
Architecture & training
Architecture: Dense 7.7B · RoPE · SwiGLU · GQA · 256k vocab
Training: 7.8T tokens, 35 EU languages + 92 programming languages.
Verdict
The reference EU-sovereign 7B — choose it when European language breadth and provenance matter more than top-tier English benchmarks.
Quick start
# HuggingFace : BSC-LT/salamandra-7b-instructOr use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.