Claire 7B 0.1
By LINAGORA · France
Updated 2026-07-13
Overview
LINAGORA's LoRA fine-tune of Falcon-7B specialized for spontaneous French dialogue. Released under CC-BY-NC-SA 4.0, with a separate Apache-licensed variant available for commercial work.
When to pick this model
- Research projects focused on conversational French
- Non-commercial prototypes needing native-feeling French dialogue
- Academic studies of spoken-style language modeling
- Baseline comparisons against modern French-capable LLMs
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) | 14 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.
In practice, Claire 7B 0.1 fits an 8 GB consumer card at Q4_K_M (5 GB). Stepping up to Q8_0 nearly doubles the footprint to 9 GB, and unquantized FP16 weights take 14 GB — plan your GPU around the Q4 or Q5 figure unless you specifically need the higher fidelity.
Without a GPU, Claire 7B 0.1 needs roughly 8 GB of system RAM to run on CPU via llama.cpp or Ollama — workable for background jobs, but far slower than GPU inference. Throughput estimates from our compatibility engine: around 12 tokens/sec on entry-level GPUs, on the order of 35 tokens/sec on a mid-range card, and up to 90 tokens/sec on high-end hardware — assuming the chosen quantization fully fits in VRAM.
What hardware do you need
The table below matches Claire 7B 0.1 to common GPU memory tiers, using the highest-fidelity quantization that fully fits each card class. Spilling layers to system RAM works but costs most of the speed, so size your card to the quantization you actually want to run.
| GPU memory | Example cards | Best fit for Claire 7B 0.1 |
|---|---|---|
| 8 GB | RTX 5070 Laptop, RTX 5060, RTX 5060 Ti 8GB | Q5_K_M (6 GB used) |
| 12 GB | RTX 5070, RTX 5070 Ti Laptop, RTX 4080 Laptop | Q8_0 (9 GB used) |
| 16 GB | RTX 5080, RTX 4080 Super, Radeon RX 9070 XT | FP16 (14 GB used) |
| 24 GB | RTX 4090, Radeon RX 7900 XTX, RTX 5090 Laptop | FP16 (14 GB used) |
| 32 GB | RTX 5090 | FP16 (14 GB used) |
Which GPU should you buy to run Claire 7B 0.1?
To run Claire 7B 0.1 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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Strengths
- Natural, spoken-style French output
- Lightweight 7B footprint for local experimentation
- Backed by OpenLLM-France community work
- Targeted training on authentic French dialogue data
Limitations
- CC-BY-NC-SA license blocks most commercial use
- Tiny 2k context window by modern standards
- Built on aging Falcon-7B base
- Outclassed by Mistral and Qwen on general French tasks
Typical workloads
In our catalog grid, Claire 7B 0.1 is filed under Spontaneous FR Dialogue — the use cases where its size/quality trade-off makes the most sense. Its tags translate to concrete workloads: French-language output where quality matters.
Note the 2k-token context window — fine for short interactions, limiting for long documents or big retrieval contexts. It ships under the CC-BY-NC-SA 4.0 license — commercial use is generally possible but read the specific terms before embedding it in a product.
Architecture & training
Architecture: LoRA fine-tune of Falcon-7B on spontaneous FR dialogue
Training: LINAGORA + OpenLLM-France.
A historically interesting French-dialogue specialist, but the restrictive license and 2k context make it a research-only pick today.
Quick start
# HuggingFace : OpenLLM-France/Claire-7B-0.1 (Apache : Claire-7B-Apache-0.1)Or use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.
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Frequently asked questions
How much VRAM does Claire 7B 0.1 need?
At the recommended Q4_K_M quantization, Claire 7B 0.1 needs about 5 GB of VRAM. Q8_0 takes 9 GB, and unquantized FP16 weights take 14 GB.
Can Claire 7B 0.1 run without a GPU?
Yes — with roughly 8 GB of system RAM it runs CPU-only through llama.cpp or Ollama. Expect a fraction of GPU speed, which is fine for background or batch jobs but slow for interactive chat.
What context window does Claire 7B 0.1 support?
Claire 7B 0.1 supports a 2k-token context window (2,048 tokens).
Can I use Claire 7B 0.1 commercially?
Claire 7B 0.1 ships under the CC-BY-NC-SA 4.0 license. Commercial use is generally permitted subject to its terms — review the license text before shipping a product.
How fast is Claire 7B 0.1 on consumer hardware?
Our compatibility engine estimates on the order of 35 tokens/sec on a mid-range GPU and up to 90 tokens/sec on high-end cards, assuming the quantization fully fits in VRAM.
Which quantization of Claire 7B 0.1 should I download first?
Start with Q4_K_M (5 GB) — the standard size/quality sweet spot. Step up to Q5_K_M or Q8_0 only if you have VRAM headroom. It already fits an 8 GB card at Q5_K_M.