EuroLLM 9B — VRAM, speed & local setup
Written by Jakub Rusinowski · Last updated
The mid-size EuroLLM, covering all 24 EU languages on a card most people already own. Apache-2.0.
EuroLLM 9B needs about 6 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.
VRAM and speed by quantization
Quoted against NVIDIA RTX 4090 (24 GB). Weights plus overhead only: this model's architecture is unpublished, so no KV cache is added.
| Quant | Memory | VRAM | Speed (est.) | Fit |
|---|---|---|---|---|
| Q2_K 2.63 bpw | 3.8 GB | ~144 tok/s | Fits | |
| Q3_K_M 3.41 bpw | 4.6 GB | ~123 tok/s | Fits | |
| Q4_K_M 4.83 bpw | 6.2 GB | ~98 tok/s | Fits | |
| Q5_K_M 5.67 bpw | 7.2 GB | ~87 tok/s | Fits | |
| Q6_K 6.56 bpw | 8.2 GB | ~78 tok/s | Fits | |
| Q8_0 8.50 bpw | 10.4 GB | ~64 tok/s | Fits | |
| F16 16.00 bpw | 18.8 GB | ~37 tok/s | Fits |
Black marker = usable memory on the NVIDIA RTX 4090 (24 GB). Estimates from the memory-bandwidth roofline on the methodology page. EuroLLM 9B VRAM calculator →
Get EuroLLM 9B running
The cheapest catalogued GPU that runs EuroLLM 9B is the Intel Arc B570 (10 GB).
or compare on Vast.ai from $0.35/hr (typical low · varies)
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How to run EuroLLM 9B
Install Ollama, then run:
ollama run eurollmSpecifications
Corroborated — Two or more independent sources agree on these figures, but the model card itself was not retrieved. Treat the numbers as good rather than confirmed. Still unconfirmed: context, releaseDate.
- Parameters
- 9 Billion
- Context window
- 4,096
- Architecture
- Dense
- Provider
- Unbabel / Instituto Superior Técnico / INESC-ID
- Licence
- Apache 2.0
- Practical deployment
- Laptop
- Specified at
- Q4_K_M
- System RAM
- 16 GB
- Record updated
- 2026-09-19
Commercial use permitted. No usage restrictions beyond attribution.
Quality and use cases
Scores as published by the model’s authors or an independent evaluator — quality, not throughput, and not measured by us.
Other EuroLLM sizes
EuroLLM 9B — frequently asked questions
How much VRAM does EuroLLM 9B need?
About 6 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does EuroLLM 9B run on an RTX 4090 (24 GB)?
Yes. EuroLLM 9B needs about 6 GB at Q4_K_M, inside a 24 GB card, at an estimated 98 tokens/sec.
How do I run EuroLLM 9B locally?
Install Ollama and run `ollama run eurollm`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does EuroLLM come in?
EuroLLM 9B (6 GB), EuroLLM 22B (14 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.