---
license: cc-by-sa-4.0
base_model:
  - kyutai/helium-1-2b
tags:
  - kyutai
  - helium
  - llama
  - base-model
  - multilingual
  - edge
  - mobile
  - europe
  - gguf
  - llama.cpp
  - 12gb-gpu
  - 8gb-gpu
  - 6gb-gpu
language:
  - bg
  - cs
  - da
  - de
  - el
  - en
  - es
  - et
  - fi
  - fr
  - ga
  - hr
  - hu
  - it
  - lt
  - lv
  - mt
  - nl
  - pl
  - pt
  - ro
  - sk
  - sl
  - sv
pipeline_tag: text-generation
library_name: gguf
---

# Helium-1-2B — GGUF

> 🟢 **Fits on**: every GPU class — even integrated graphics. Runs on phones at Q2_K.

GGUF conversion of [`kyutai/helium-1-2b`](https://huggingface.co/kyutai/helium-1-2b) — Kyutai's lightweight 2B base language model targeting edge and mobile devices, with native support for all 24 official EU languages.

This is a community quantization. The base model is by Kyutai (creators of Mimi, Moshi, and the Kyutai TTS/STT family). Until now, only MLX (Apple Silicon) variants existed — this fills the GGUF gap for `llama.cpp` and `ollama` users.

## Model details

| Field | Value |
|---|---|
| Architecture | `LlamaForCausalLM` (standard Llama; works with stock llama.cpp) |
| Parameters | 2B |
| Layers | 28 |
| Hidden size | 2048 |
| Vocab | 64,000 (multilingual) |
| Context | 4K |
| Type | **Base model** — not instruction-tuned |
| License | CC-BY-SA 4.0 + [Gemma Terms of Use](https://ai.google.dev/gemma/terms) (Helium is distilled from Gemma 2) |

## Use case

- **Edge / mobile inference** — fits comfortably on consumer hardware, including phones and small GPUs
- **EU multilingual base** — train your own instruction-following model on top of this with the language coverage you need
- **Research** — distillation lineage from Gemma 2 with smaller footprint
- **Not for chat out-of-the-box** — this is a base model, no instruction tuning. For chat, fine-tune it first.

## Quants

| Quant | Size | Use case |
|---|---|---|
| **Q2_K** | ~0.8 GB | tiniest footprint — phones, microcontrollers, 4 GB cards |
| **Q3_K_M** | ~1.0 GB | balance for 6 GB cards |
| Q4_K_M | ~1.2 GB | recommended default — fits anywhere |
| Q5_K_M | ~1.5 GB | quality bump if you have headroom |
| Q6_K | ~1.8 GB | near-lossless |
| Q8_0 | ~2.3 GB | reference quality |
| F16 | ~4.0 GB | full precision |

## Usage — Ollama

```bash
hf download RhinoWithAcape/helium-1-2b-GGUF \
  helium-1-2b.Q4_K_M.gguf Modelfile --local-dir ./helium
cd ./helium
ollama create helium-1-2b:Q4_K_M -f Modelfile
ollama run helium-1-2b:Q4_K_M "Once upon a time"
```

## Usage — llama.cpp

```bash
./build/bin/llama-completion \
    -m helium-1-2b.Q4_K_M.gguf \
    -p "The capital of France is" \
    -n 30 --temp 0.6
```

(Sample: `"The capital of France is Paris..."`)

## License notes

- This conversion is **CC-BY-SA 4.0** (matching the source release).
- Helium-1 is **distilled from Gemma 2**, so use is also subject to the [Gemma Terms of Use](https://ai.google.dev/gemma/terms).
- This GGUF inherits both terms.

## Conversion details

- Source: `kyutai/helium-1-2b` (downloaded 2026-04-29; Q2_K + Q3_K_M backfilled 2026-05-02)
- Tools: stock `llama.cpp` (no patches required — standard Llama arch)
- Steps: `convert_hf_to_gguf.py` → `llama-quantize`

## More from RhinoWithAcape

We're a small AI lab making powerful models actually run on consumer GPUs. Curated GGUFs with the full Q2/Q3/Q4 ladder for 12-16 GB cards and first-mover conversions for new architectures.

- [Cosmos-Reason2-32B](https://huggingface.co/RhinoWithAcape/Cosmos-Reason2-32B-GGUF) — NVIDIA's reasoning VLM
- [Nemotron-3-Nano-Omni-30B](https://huggingface.co/RhinoWithAcape/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-GGUF) — Mamba2-Transformer hybrid MoE
- [BAR-5x7B](https://huggingface.co/RhinoWithAcape/BAR-5x7B-GGUF) / [BAR-2x7B-Tool-Use](https://huggingface.co/RhinoWithAcape/BAR-2x7B-Tool-Use-GGUF) — AllenAI FlexOlmo
- [gpt-oss-20b-Q2_K](https://huggingface.co/RhinoWithAcape/gpt-oss-20b-Q2_K-GGUF) — 12 GB-VRAM specific cut

→ Full catalogue at [huggingface.co/RhinoWithAcape](https://huggingface.co/RhinoWithAcape)

## Acknowledgments

- Kyutai for the open release of Helium-1, targeting under-served EU language coverage at edge scale
- Google DeepMind for the Gemma 2 base from which Helium was distilled
- llama.cpp maintainers