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Lucie 7BvsTeuken 7B Instruct

Complete comparison between Lucie 7B (7B parameters, OpenLLM-France) and Teuken 7B Instruct (7B, OpenGPT-X). VRAM required by quantization, tokens/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 Lucie 7B Teuken 7B Instruct
Settings 7B 7B
Family Lucie Teuken
Author OpenLLM-France OpenGPT-X
Origin FR DE
License Apache 2.0 Apache 2.0 (commercial)
Context 4,096 tokens 4,096 tokens
Output January 2025 November 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 Teuken 7B Instruct
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 14 GB
CPU-only RAM 8 GB 10 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 Teuken 7B Instruct
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.

General chat
Close match — it depends on the exact use case. The two are equivalent on this criterion; decide based on your VRAM or licensing constraints.
Formal French
Lucie 7B wins. Trained on a dense French-language corpus, better at idiomatic phrasing.
Agents & tool use
Close match — it depends on the exact use case. The two are equivalent on this criterion; decide based on your VRAM or licensing constraints.
Lightweight deployment
Close match — it depends on the exact use case. The two are equivalent on this criterion; decide based on your VRAM or licensing constraints.
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Strengths and weaknesses

OpenLLM-France · 7B

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

ollama run lucie:7b
OpenGPT-X · 7B

Teuken 7B Instruct

German sovereignty (BMWK). 24 EU languages. Research-v0.4 variant under a restricted license.

  • EU sovereignty
  • 24 European languages
  • Commercial Apache 2.0 variant
  • 4K context
  • No official Ollama
  • Research variant under a restricted license

Installation

# HuggingFace: openGPT-X/Teuken-7B-instruct-commercial-v0.4

Frequently asked questions

Which model runs best on RTX 4090 (24 GB): Lucie 7B or Teuken 7B Instruct?

On an RTX 4090, Lucie 7B runs at FP16 (~90 tok/s), Teuken 7B Instruct in FP16 (~90 tok/s). In pure throughput, Teuken 7B Instruct wins. See the configurator to test your exact GPU.

Lucie 7B or Teuken 7B 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?

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?

Lucie 7B is under Apache 2.0 — free for commercial use. Teuken 7B Instruct is under Apache 2.0 (commercial) — also free. 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: Lucie 7B (7B). 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.

Go further