Can the RTX 4090 run Laguna-XS-2.1?

Just. Laguna-XS-2.1 at Q4_K_M needs about 20.8 GB of the RTX 4090's 24 GB, running at an estimated 33 tok/s. Keep context short and close other GPU apps.

VRAM
24 GB
Needs at Q4
20.8 GB
Headroom
3.2 GB
Speed (Q4_K_M)
~33 tok/s

Every quantization

Laguna-XS-2.1 (33.4B) on 24 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M19 GB20.8 GBTight~33 tok/s
Q5_K_M24 GB25.8 GBToo big -
Q8_036 GB37.8 GBToo big -
FP1667 GB68.8 GBToo big -

Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the RTX 4090's 1008 GB/s bandwidth (XiongjieDai/GPU-Benchmarks-on-LLM-Inference). Long contexts need more memory and run slower.

Run it

Copy, paste, go

llama-server -hf poolside/Laguna-XS-2.1-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Laguna-XS-2.1 details →

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Same model, other hardware - and other models on this card

Laguna-XS-2.1 on other hardware

Also runs on the RTX 4090

Frequently asked

Quick answers

Can the NVIDIA RTX 4090 run Laguna-XS-2.1?

Just. Laguna-XS-2.1 at Q4_K_M needs about 20.8 GB of the RTX 4090's 24 GB, running at an estimated 33 tok/s. Keep context short and close other GPU apps.

How much VRAM does Laguna-XS-2.1 need?

About 19 GB of weights at Q4_K_M, 36 GB at Q8_0 and 67 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Laguna-XS-2.1 on the RTX 4090?

Roughly 33 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the RTX 4090's 1008 GB/s memory bandwidth.