Advisor / Models / Laguna XS 2.1

Laguna XS 2.1: VRAM requirements & speed

Laguna XS 2.1 (33.44B MoE, 3B active, openmdw-1.1). Native context 256k. Smallest GGUF: 20.55 GB.

20.55 GBsmallest quant file
19hardware pages that fit it fully
8run with offload
0measured data points

Memory needed by quantization and context

GGUF file size plus f16 KV cache (and fixed overhead of ~1 GB per GPU not shown). Source: bartowski/Laguna-XS-2.1-GGUF.

QuantFile+8k ctx+32k ctx+128k ctx+256k ctx
Q4_K_M20.55 GB20.9 GB22.0 GB26.0 GB31.4 GB
Q5_K_M24.01 GB24.4 GB25.4 GB29.4 GB34.8 GB
Q6_K29.04 GB29.4 GB30.4 GB34.5 GB39.8 GB
Q8_035.6 GB36.0 GB37.0 GB41.0 GB46.4 GB

KV cache size by context length

Computed from the model's attention layout (sliding-window layers capped at their window).

Contextf16q8_0q4_0
8k0.40 GB0.21 GB0.11 GB
32k1.41 GB0.75 GB0.40 GB
128k5.43 GB2.89 GB1.53 GB
256k10.80 GB5.74 GB3.04 GB

Which hardware runs Laguna XS 2.1? · 16k context

HardwareQuantFitMemoryTok/sSpeed source
RTX 5090 32GBQ6_Kfits fully29.8 GB343scaled from measured
AMD RX 7900 XTX 24GBQ4_K_Mfits fully21.3 GB249estimated
RTX PRO 6000 96GBQ8_0fits fully36.3 GB238scaled from measured
RTX 4090 24GBQ4_K_Mfits fully21.3 GB191scaled from measured
Mac Studio M5 Ultra 256GBQ8_0fits fully36.3 GB184estimated
Mac Studio M5 Ultra 512GB (ships late Oct 2026)Q8_0fits fully36.3 GB184estimated
RTX 3090 24GBQ4_K_Mfits fully21.3 GB159scaled from measured
2x RTX 3090 (48GB total)Q8_0fits fully36.3 GB158estimated
RTX 5080 16GBQ4_K_MMoE offload to CPU21.3 GB80estimated
RTX 5070 Ti 16GBQ4_K_MMoE offload to CPU21.3 GB79estimated
Mac Studio (2025) M3 Ultra 96GBQ8_0fits fully36.3 GB75scaled from measured
RTX 5060 Ti 16GBQ4_K_MMoE offload to CPU21.3 GB72estimated
Mac Studio M5 Max 128GBQ8_0fits fully36.3 GB71scaled from measured
MacBook Pro 14/16 M5 Max 128GBQ8_0fits fully36.3 GB71scaled from measured
16GB VRAM class (RTX 4060 Ti 16GB, 32GB RAM)Q4_K_MMoE offload to CPU21.3 GB65estimated
MacBook Pro 14/16 M5 Pro 48GBQ6_Kfits fully29.8 GB65estimated
MacBook Pro 14/16 (2024) M4 Max 128GBQ8_0fits fully36.3 GB64estimated
AMD Ryzen AI Max+ PRO 495 (Ryzen AI Halo) 192GBQ8_0fits fully36.3 GB54estimated
AMD Ryzen AI Max+ 395 (Strix Halo) 128GBQ8_0fits fully36.3 GB52scaled from measured
RTX 5070 12GBQ4_K_MMoE offload to CPU21.3 GB51estimated
RTX 4070 12GBQ4_K_MMoE offload to CPU21.3 GB50estimated
NVIDIA DGX Spark 128GBQ8_0fits fully36.3 GB49scaled from measured
Mac mini M6 32GBQ4_K_Mfits fully21.3 GB45estimated
MacBook Air M5 32GBQ4_K_Mfits fully21.3 GB42estimated
Mac mini (2024) M4 Pro 64GBQ8_0fits fully36.3 GB39estimated
8GB VRAM class (RTX 4060 8GB, 32GB RAM)Q4_K_MMoE offload to CPU21.3 GB38estimated
RTX 3060 12GB (32GB RAM)Q4_K_MMoE offload to CPU21.3 GB29estimated
Mac mini / iMac M4 16GB-does not fit--

Discrete GPUs are modelled with 32 GB of system RAM available for offload. Does not fit even with offload: Mac mini / iMac M4 16GB.

MLX conversions for Apple Silicon

RepoBitsSizeRuns with
mlx-community/Laguna-XS-2.1-4bit4-bit (4bit)18.8 GBmlx-vlm
mlx-community/Laguna-XS-2.1-8bit8-bit (8bit)35.5 GBmlx-vlm

Verified via the Hugging Face API on 2026-10-20. Compare with the GGUF sizes above (Q4_K_M 20.55 GB, Q8_0 35.6 GB). Mac hardware pages show the MLX command; there are no MLX speeds on this site yet. MLX vs GGUF.

Links

Model card · GGUF files · Open in the advisor · last verified 2026-10-20

FAQ

How much VRAM does Laguna XS 2.1 need?

The smallest quant (Q4_K_M) is 20.55 GB, so you need roughly 22 GB for an 8k context including KV cache and overhead. At 256k context the f16 KV cache alone is 10.8 GB.

Can I run Laguna XS 2.1 on a RTX 5090 32GB?

Yes: on RTX 5090 32GB it fits fully as Q6_K at about 343 tok/s (scaled from measured). 19 of 28 hardware configurations fit it fully at 16k context.

What is the maximum context for Laguna XS 2.1?

256k tokens natively. Memory, not the model, is usually the limit: see the KV cache table above.

All models: model index · by memory: 8 GB · 12 GB · 16 GB · 24 GB · 32 GB · 48 GB · 64 GB · 96 GB · 128 GB · 192 GB · 256 GB · 512 GB. Numbers use the same fit math as the advisor; sources and methods.