text model · Laguna · Windows
Can I run Laguna XS 2.1 on Nvidia GeForce RTX 3090 (24GB)?
Yes. Laguna XS 2.1 runs on Nvidia GeForce RTX 3090 (24GB) at Q4_K_M (~22.2 GB of ~23 GB usable).
Fits at Q4_K_M (~22.2 GB of ~23 GB usable) but with little headroom. Close other apps; a smaller context frees a few hundred MB.
That figure is at a 4k context and moves about ±15% as context length changes. Nvidia GeForce RTX 3090 (24GB) leaves ~0.8 GB of headroom.
- Q4_K_M needed
- ~22.2 GB
- Usable on device
- ~23 GB
- Device memory
- 24 GB
- Best quant
- Q4_K_M
Which quant fits
Run it
Loads the Q4_K_M weights.
ollama run laguna-xs-2.1 - Parameters
- 33.4B (MoE, 3B active)
- Q4_K_M size
- 20 GB
- Q8_0 size
- 36 GB
- Context
- 256k
- Ollama tag
- laguna-xs-2.1
- Memory
- 24 GB vram
- Usable for weights
- ~23 GB
- Power draw
- ~350 W
- Best runtime
- vLLM (Linux) / Ollama (CUDA)
You could also run
Run Laguna XS 2.1 on other hardware
FAQ
Can Nvidia GeForce RTX 3090 (24GB) run Laguna XS 2.1?
Yes. Laguna XS 2.1 runs on Nvidia GeForce RTX 3090 (24GB) at Q4_K_M (~22.2 GB of ~23 GB usable).
How much memory does Laguna XS 2.1 need?
It is a tight fit on Nvidia GeForce RTX 3090 (24GB). At Q4_K_M the weights are ~20 GB; with KV cache and runtime overhead, budget ~22.2 GB at a 4k context. It is a Mixture-of-Experts model (33.4B total / 3B active), so all experts must stay in memory; memory tracks total params, not active params.
What is the best tool to run Laguna XS 2.1 on Windows?
LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
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A live badge for your model card or README, updated as the data is. [](https://localmodel.run/can-i-run/laguna-xs-2.1/nvidia-rtx-3090-24gb) Sources
Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.