Mistral 7B Instruct vs Lucie 7B
Side-by-side specs, benchmarks, and a verdict by use case.
Updated 2026-07-13
| Spec | Mistral 7B Instruct | Lucie 7B |
|---|---|---|
| Parameters | 7B | 7B |
| Author | Mistral AI | OpenLLM-France |
| License | Apache 2.0 | Apache 2.0 |
| Context window | 0k | 0k |
| VRAM at Q4 | 5 GB | 5 GB |
| VRAM at Q5 | 6 GB | 6 GB |
| VRAM at Q8 | 9 GB | 9 GB |
| VRAM at FP16 | 16 GB | 16 GB |
| Use cases | chat, general | chat, fr |
Verdict
Both models sit in a similar size class. The pick depends on tags, license, and benchmarks rather than raw parameter count.
The two models at a glance
About Mistral 7B Instruct
Mistral AI's breakout 7B instruct model. Still a go-to baseline for fast, low-cost inference and the most fine-tuned open-weight model in the wild. Strengths: Excellent quality-to-speed ratio for a 7B, Fully permissive Apache 2.0 license, Mature ecosystem of fine-tunes, GGUFs, and quants, Solid multilingual coverage, including strong French.
About Lucie 7B
A French-sovereign 7B model from OpenLLM-France, backed by CNRS and LINAGORA, with a fully transparent and auditable training corpus. Strengths: Full European data sovereignty story, Publicly available training corpus, Strong formal French output, Backed by CNRS and LINAGORA.
How they compare
Mistral 7B Instruct comes from Mistral AI and Lucie 7B from OpenLLM-France, they belong to the Mistral and Lucie families respectively. This comparison is built entirely from structured specs — parameter count, VRAM by quantization, context window, license, and published benchmark scores — so the verdict below reflects measurable differences rather than marketing claims.
Mistral 7B Instruct and Lucie 7B share the same 7B parameter class. Both need about 5 GB of VRAM at a Q4 quantization, so they fit the same GPU tier.
The two models target different sweet spots: Mistral 7B Instruct is tuned for chat, general, while Lucie 7B leans toward chat, fr. Match the model to your dominant workload rather than to raw size.
For long-context work, Mistral 7B Instruct offers the bigger window (32k vs 4k tokens).
Memory, quantization & throughput
Across quantization levels, Mistral 7B Instruct requires Q4 ≈ 5 GB, Q5 ≈ 6 GB, Q8 ≈ 9 GB, FP16 ≈ 16 GB, while Lucie 7B requires Q4 ≈ 5 GB, Q5 ≈ 6 GB, Q8 ≈ 9 GB, FP16 ≈ 16 GB. In practice Mistral 7B Instruct fits an 8 GB card at Q4, so plan your GPU around the Q4 or Q5 figure unless you specifically need the higher fidelity of Q8 or FP16.
Without a GPU, Mistral 7B Instruct needs roughly 8 GB of system RAM to run on CPU and Lucie 7B about 8 GB — workable for offline use but far slower than GPU inference. On a mid-range GPU you can expect on the order of 35 tokens/sec from Mistral 7B Instruct and 35 from Lucie 7B, scaling up to 90 and 90 tokens/sec on high-end hardware.
Which fits your GPU
Here is the highest-quality quantization of each model that fits common GPU memory budgets, so you can match Mistral 7B Instruct or Lucie 7B to the card you actually own:
- On a 8 GB GPU: Mistral 7B Instruct runs at Q5 (6 GB); Lucie 7B runs at Q5 (6 GB).
- On a 12 GB GPU: Mistral 7B Instruct runs at Q8 (9 GB); Lucie 7B runs at Q8 (9 GB).
- On a 16 GB GPU: Mistral 7B Instruct runs at FP16 (16 GB); Lucie 7B runs at FP16 (16 GB).
- On a 24 GB GPU: Mistral 7B Instruct runs at FP16 (16 GB); Lucie 7B runs at FP16 (16 GB).
Benchmark scores
Reported benchmarks for Mistral 7B Instruct: MMLU 60.1, HellaSwag 81.3, HumanEval 30.5.
Reported benchmarks for Lucie 7B: MMLU (fr) 54.2, FrenchBench 68.
Bottom line: which should you pick?
- Pick Mistral 7B Instruct for long-context work (up to 32k tokens).
- Pick Mistral 7B Instruct if your workload is general.
- Pick Lucie 7B if your workload is fr.
Which GPU should you buy to run Mistral 7B Instruct?
To run Mistral 7B Instruct locally at Q4, you need ~5 GB of VRAM. The best value for this is a RTX 5060 (8 GB VRAM).
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Frequently asked questions
What is the difference between Mistral 7B Instruct and Lucie 7B?
The headline differences: both are 7B models; their context windows differ (32k vs 4k tokens). Below we break down VRAM by quantization, benchmark scores, and a use-case verdict so you can pick the right one.
Can Mistral 7B Instruct and Lucie 7B run on a 24 GB GPU?
At a Q4 quantization, Mistral 7B Instruct needs about 5 GB of VRAM and fits comfortably on a 24 GB GPU; Lucie 7B needs about 5 GB and fits comfortably on a 24 GB GPU. Both have the same Q4 footprint.
What licenses do Mistral 7B Instruct and Lucie 7B use?
Mistral 7B Instruct is licensed under Apache 2.0 and Lucie 7B under Apache 2.0.
Which has the longer context window, Mistral 7B Instruct or Lucie 7B?
Mistral 7B Instruct has the larger context window (32k vs 4k tokens), so it handles longer documents and codebases in a single prompt.