Laguna M.1 — Hardware Requirements & GPU Compatibility
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Laguna M.1 is a 225.8B-parameter open language model from poolside. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 136.07 GB of VRAM — see which GPUs and Macs can run it below.
1.9K downloads
120 likesSpecifications
- Publisher
- poolside
- Parameters
- 225.8B
- Architecture
- LagunaForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 100,352
- Release Date
- 2026-06-15
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Laguna M.1 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 96.6 GB | 133.8 GB | 95.96 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 99.4 GB | 136.7 GB | 98.79 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 110.7 GB | 148.0 GB | 110.08 GB | 3-bit medium quantization |
| Q4_K_M | 4.80 | 136.1 GB | 173.4 GB | 135.48 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 161.5 GB | 198.8 GB | 160.88 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 186.9 GB | 224.2 GB | 186.28 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 226.4 GB | 263.7 GB | 225.80 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Laguna M.1?
Q4_K_M · 136.1 GBLaguna M.1 (Q4_K_M) requires 136.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 177+ GB is recommended. Using the full 262K context window can add up to 37.3 GB, bringing total usage to 173.4 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Laguna M.1?
Q4_K_M · 136.1 GB6 devices with unified memory can run Laguna M.1, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio (M3 Ultra, 256GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download Laguna M.1
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Frequently Asked Questions
- How much VRAM does Laguna M.1 need?
Laguna M.1 requires 136.1 GB of VRAM at Q4_K_M, or 452.2 GB at BF16. Full 262K context adds up to 37.3 GB (173.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 225.8B × 4.8 bits ÷ 8 = 135.5 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 37.9 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M136.1 GBQ4_K_M + full context173.4 GB- Can NVIDIA GeForce RTX 5090 run Laguna M.1?
No — Laguna M.1 requires at least 68.3 GB at IQ2_XS, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Laguna M.1?
For Laguna M.1, Q4_K_M (136.1 GB) offers the best balance of quality and VRAM usage. Q5_K_S (155.8 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XS at 68.3 GB.
VRAM requirement by quantization
IQ2_XS68.3 GBQ2_K96.6 GBIQ4_XS122.0 GBQ4_K_M ★136.1 GBQ5_K_S155.8 GBBF16452.2 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Laguna M.1 on a Mac?
Laguna M.1 requires at least 68.3 GB at IQ2_XS, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Laguna M.1 locally?
Yes — Laguna M.1 can run locally on consumer hardware. At Q4_K_M quantization it needs 136.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Laguna M.1?
At Q4_K_M, Laguna M.1 can reach ~32 tok/s on AMD Instinct MI350X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 136.1 × 0.65 = ~38 tok/s
Estimated speed at Q4_K_M (136.1 GB)
~38 tok/s~38 tok/s~32 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Laguna M.1?
At Q4_K_M, the download is about 135.48 GB. The full-precision BF16 version is 451.59 GB. The smallest option (IQ2_XS) is 67.74 GB.
- Which GPUs can run Laguna M.1?
No single consumer GPU has enough VRAM to run Laguna M.1 at Q4_K_M (136.1 GB). Multi-GPU or professional hardware is required.
- Which devices can run Laguna M.1?
6 devices with unified memory can run Laguna M.1 at Q4_K_M (136.1 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), Mac Studio M2 Ultra (192 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.