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OP·Fredoline Eruo
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RUNLOCALAI · v38
RefinedNeuro RN TR R2 / on / NVIDIA GeForce RTX 5080
Fits comfortably

Running RefinedNeuro RN TR R2 on NVIDIA GeForce RTX 5080

NVIDIA GeForce RTX 5080 runs RefinedNeuro RN TR R2 comfortably at Q4_K_M with 9 GB of headroom for context.

By Fredoline Eruo·Latest benchmark evidence May 28, 2026

Model size

8B params
RefinedNeuro RN TR R2 →

Memory available

16 GB
NVIDIA GeForce RTX 5080 →

Recommended quant

Q4_K_M
Highest quality that fits

Quick start with Ollama

1. Install
ollama pull RefinedNeuro/RN_TR_R2:latest
2. Run
ollama run RefinedNeuro/RN_TR_R2:latest

Default quant in Ollama is Q4_K_M. To use a different quant, append it: RefinedNeuro/RN_TR_R2:latest-q5_K_M.

Variants and what fits

QuantizationFile sizeVRAM requiredFits on NVIDIA GeForce RTX 5080?
Q4_K_M4.9 GB7 GB
Yes

Real benchmarks

ToolQuantContexttok/sVRAM usedDateEvidenceExport
—Q4_K_M2,048133.4 tok/s—May 28, 2026Measured here
operator: fred-oline
DetailSourceJSON

Frequently asked

Can NVIDIA GeForce RTX 5080 run RefinedNeuro RN TR R2?

NVIDIA GeForce RTX 5080 runs RefinedNeuro RN TR R2 comfortably at Q4_K_M with 9 GB of headroom for context.

What quantization should I use?

Q4_K_M is the highest-quality variant of RefinedNeuro RN TR R2 that fits in 16 GB VRAM. Lower-bit quants will be smaller but lose some quality.

How fast will it be?

Measured at 133.4 tok/s on this combination in our testing.

See also: RefinedNeuro RN TR R2, NVIDIA GeForce RTX 5080, all benchmarks.

Reviewed by RunLocalAI Editorial. See our editorial policy.