Best local LLM for roleplay & writing on a NVIDIA GeForce RTX 5090 (2026)
All figures assume an f16 KV cache, a 0.6 GB display reserve on the GPU, and 64 GB of DDR5 system RAM for the offload tiers. Tune these in the calculator.
The verdict
Rocinante 12B Q8_0
Fits on GPU at 16K · Roleplay & writing score 9/10 · ≈ 89 tok/s
The budget roleplay king. Lowest slop-per-token of anything under 24 GB; the community keeps it alive for a reason.
llama-server -m Rocinante-12B-v1.1-Q8_0.gguf -c 16384 --flash-attn -ngl 99
Worthy alternates
Cydonia 24B Q8_0
Fits on GPU · ≈ 47 tok/s · Roleplay & writing 9/10
Rocinante's bigger sibling on a Mistral Small base. The default serious-RP pick for 24 GB cards.
Mistral Nemo 12B Q8_0
Fits on GPU · ≈ 89 tok/s · Roleplay & writing 7/10
The base under half the roleplay finetunes ever made. Natural prose, light guardrails, happiest at 16K.
Tune this for your exact RAM and settings in the calculator → · All models on the NVIDIA GeForce RTX 5090
Frequently asked questions
What is the best local LLM for roleplay & writing on a NVIDIA GeForce RTX 5090?
Rocinante 12B at Q8_0 — it scores 9/10 for roleplay & writing and runs as "Fits on GPU" at 16K context on the NVIDIA GeForce RTX 5090.
How much context do I need for roleplay & writing?
We recommend 16K tokens for roleplay & writing (minimum 8K). These picks are computed at 16K.
How fast will it run on a NVIDIA GeForce RTX 5090?
Roughly 89 tokens/sec for Rocinante 12B — fast for interactive use.
Do I need more than 32 GB of VRAM for roleplay & writing?
No — the pick above needs 16.5 GB of VRAM at 16K.
What settings should I use?
Start with our command: llama-server -m Rocinante-12B-v1.1-Q8_0.gguf -c 16384 --flash-attn -ngl 99 — then tune context and KV quant in the fit calculator.