Mistral 7B InstructvsLucie 7B
Complete comparison between Mistral 7B Instruct (7B parameters, Mistral AI) and Lucie 7B (7B, OpenLLM-France). 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—no copy-pasting between pages.
In brief
| Feature | Mistral 7B Instruct | Lucie 7B |
|---|---|---|
| Settings | 7B | 7B |
| Family | Mistral | Lucie |
| Author | Mistral AI | OpenLLM-France |
| Origin | FR | FR |
| License | Apache 2.0 | Apache 2.0 |
| Context | 32 768 tokens | 4,096 tokens |
| Output | September 2023 | January 2025 |
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 | Mistral 7B Instruct | Lucie 7B |
|---|---|---|
| Q4_K_M (lightweight) | 5 GB | 5 GB |
| Q5_K_M (balanced) | 6 GB | 6 GB |
| Q8 (near-lossless) | 9 GB | 9 GB |
| FP16 (max quality) | 16 GB | 16 GB |
| CPU-only RAM | 8 GB | 8 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 | Mistral 7B Instruct | Lucie 7B |
|---|---|---|
| RTX 4090 (24 GB) | 90 tok/s · FP16 | 90 tok/s · FP16 |
| RTX 4080 (16 GB) | 35 tok/s · FP16 | 35 tok/s · FP16 |
| RTX 3060 12GB (12 GB) | 12 tok/s · Q8 | 12 tok/s · Q8 |
| Apple M4 Pro (48 GB) (36 GB) | 35 tok/s · FP16 | 35 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
Mistral 7B Instruct
The classic French model. Fast, versatile, and an excellent base to get started.
- Excellent quality-to-speed ratio
- Good in French
- Fully permissive Apache license
- Mature ecosystem (fine-tunes, quantization)
- Worse than 2024+ models at reasoning
- 32k context only
Installation
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
Frequently asked questions
Which model runs best on RTX 4090 (24 GB): Mistral 7B Instruct or Lucie 7B?
On a RTX 4090, Mistral 7B Instruct runs at FP16 (~90 tok/s), Lucie 7B at FP16 (~90 tok/s). In pure throughput, Lucie 7B wins. See the configurator to test your exact GPU.
Mistral 7B Instruct or Lucie 7B: which is better in French?
In French, the two are equivalent for basic chat. For literary or legal texts, prefer a European-origin model (see our French guides).
Which uses the least VRAM?
Both require the same VRAM in Q4 (5 GB). The choice then comes down to the license or perceived quality.
Can these models be used in commercial production?
Mistral 7B Instruct is under Apache 2.0 — free for commercial use. Lucie 7B 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: Mistral 7B Instruct (7B). More capable: Mistral 7B Instruct (7B). If you’re unsure, launch 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.