RefinedNeuro RN TR R2
RefinedNeuro RN TR R2 is an Apache-2.0 Llama-family 8B model distributed on Hugging Face and Ollama. It is measured alongside R1 to compare same-size RefinedNeuro variants on local RTX 5080 inference.
Overview
RefinedNeuro RN TR R2 is an Apache-2.0 Llama-family 8B model distributed on Hugging Face and Ollama. It is measured alongside R1 to compare same-size RefinedNeuro variants on local RTX 5080 inference.
Strengths
- Apache-2.0 license
- Llama-family runtime compatibility
- Stable measured throughput across five runs
Weaknesses
- Low public adoption signal at intake
- Not tagged as a Turkish-specific model in the sweep
- Needs quality evaluation before capability claims
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 | 4.9 GB | 7 GB |
Get the model
Ollama
One-line install
ollama run RefinedNeuro/RN_TR_R2: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 RefinedNeuro RN TR R2.
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 RefinedNeuro RN TR R2?
Can I use RefinedNeuro RN TR R2 commercially?
What's the context length of RefinedNeuro RN TR R2?
How do I install RefinedNeuro RN TR R2 with Ollama?
Source: huggingface.co/RefinedNeuro/RN_TR_R2
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify RefinedNeuro RN TR R2 runs on your specific hardware before committing money.