Lucie 7BvsEuroLLM 9B Instruct
Complete comparison between Lucie 7B (7B parameters, OpenLLM-France) and EuroLLM 9B Instruct (9B, Utter Project / EU). VRAM required by quantization, tokens per second measured on 4 reference GPUs, verdict by use case, license, installation commands. All figures are calculated from catalog data — nothing is copied between pages.
In brief
| Feature | Lucie 7B | EuroLLM 9B Instruct |
|---|---|---|
| Settings | 7B | 9B |
| Family | Lucie | EuroLLM |
| Author | OpenLLM-France | Utter Project / UE |
| Origin | FR | EU |
| License | Apache 2.0 | Apache 2.0 |
| Context | 4,096 tokens | 4,096 tokens |
| Output | January 2025 | December 2024 |
Memory footprint
Approximate VRAM required for inference with an average context window. The winner (in green) is the model that uses less — smaller models have the edge.
| Quantization | Lucie 7B | EuroLLM 9B Instruct |
|---|---|---|
| Q4_K_M (lightweight) | 5 GB | 6 GB |
| Q5_K_M (balanced) | 6 GB | 7 GB |
| Q8 (near-lossless) | 9 GB | 10 GB |
| FP16 (max quality) | 16 GB | 18 GB |
| CPU-only RAM | 8 GB | 12 GB |
Estimated speed (tokens/second)
Estimates based on the best quantization that can fit on each GPU. Actual figures depend on the prompt, context, and engine (llama.cpp, vLLM, MLX). Methodology.
| Reference GPU | Lucie 7B | EuroLLM 9B Instruct |
|---|---|---|
| RTX 4090 (24 GB) | 90 tok/s · FP16 | 80 tok/s · FP16 |
| RTX 4080 (16 GB) | 35 tok/s · FP16 | 30 tok/s · Q8 |
| RTX 3060 12GB (12 GB) | 12 tok/s · Q8 | 10 tok/s · Q8 |
| Apple M4 Pro (48 GB) (36 GB) | 35 tok/s · FP16 | 30 tok/s · FP16 |
Verdict by use case
For each common use case, we indicate which of the two is better suited based on its tags, size, and specialization.
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Strengths and weaknesses
Lucie 7B
Sovereign French-language LLM, trained on French corpora.
- Full French sovereignty
- Public training data
- Excellent in formal French
- Public support (CNRS, LINAGORA)
- 4k context only
- Less versatile than Mistral in English
Installation
EuroLLM 9B Instruct
EU-funded (Horizon Europe). 35 languages (24 EU + extras), trained on 4T tokens on MareNostrum5.
- EU sovereignty (Horizon Europe)
- Apache 2.0
- Best European open model at its scale
- Ctx only 4k
- No official Ollama tag
Installation
Frequently asked questions
Which model runs best on an RTX 4090 (24 GB): Lucie 7B or EuroLLM 9B Instruct?
On an RTX 4090, Lucie 7B runs at FP16 (~90 tok/s), EuroLLM 9B Instruct in FP16 (~80 tok/s). In pure throughput, Lucie 7B wins. See the configurator to test your exact GPU.
Lucie 7B or EuroLLM 9B Instruct: which is better in French?
For formal French (writing, summarization, translation), Lucie 7B has the edge—trained on a dense French-language corpus. The other remains usable, but for less demanding use cases.
Which uses the least VRAM?
In Q4_K_M, Lucie 7B fits in 5 GB versus 6 GB for its rival — a 1 GB gap, significant if you're targeting an RTX 3060 or a 4060 Ti 8 GB.
Can these models be used in commercial production?
Lucie 7B is under Apache 2.0 — free for commercial use. EuroLLM 9B Instruct is under Apache 2.0 — also free to use. For SaaS, prefer Apache 2.0 or MIT.
Which one should you choose in 2026?
Depends on your primary constraint. Smaller / faster: Lucie 7B (7B). More capable: EuroLLM 9B Instruct (9B). If you're unsure, run the configurator with your GPU and use case — it will decide based on both.
Alternatives to consider
If neither works for you, here are some neighboring models you could explore.