Kumru 2B
Kumru 2B is a compact Turkish text-generation model from VNGRS. The Hugging Face config reports a Mistral-family architecture with an 8K context window, and the public Ollama build makes it a practical edge-speed Turkish model.
Overview
Kumru 2B is a compact Turkish text-generation model from VNGRS. The Hugging Face config reports a Mistral-family architecture with an 8K context window, and the public Ollama build makes it a practical edge-speed Turkish model.
Strengths
- Very high local throughput on consumer GPUs
- Apache-2.0 license with commercial use allowed
- Small enough for low-VRAM Turkish assistants
Weaknesses
- 2B-class quality ceiling on complex reasoning
- Shorter context than current 32K Turkish Mistral derivatives
- Best suited to short Turkish interactions, not deep research
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 1.5 GB | 2 GB |
Get the model
Ollama
One-line install
ollama run alibayram/kumru:latestRead our Ollama review →HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of Kumru 2B.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run Kumru 2B?
Can I use Kumru 2B commercially?
What's the context length of Kumru 2B?
How do I install Kumru 2B with Ollama?
Source: huggingface.co/vngrs-ai/Kumru-2B
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify Kumru 2B runs on your specific hardware before committing money.