KatyTheCutie·LlamaForCausalLM

EstopianMaid 13B — Hardware Requirements & GPU Compatibility

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EstopianMaid 13B is a 13.0B-parameter open language model from KatyTheCutie. It supports a context window of up to 4,096 tokens. At FP16 it needs about 28.01 GB of VRAM — see which GPUs and Macs can run it below.

87 downloads 55 likes4K context

Specifications

Publisher
KatyTheCutie
Parameters
13.0B
Architecture
LlamaForCausalLM
Context Length
4,096 tokens
Vocabulary Size
32,000
Release Date
2024-05-27
License
Llama 2 Community

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How Much VRAM Does EstopianMaid 13B Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
FP1616.0028.0 GB

Which GPUs Can Run EstopianMaid 13B?

FP16 · 28.0 GB

EstopianMaid 13B (FP16) requires 28.0 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 37+ GB is recommended. Using the full 4K context window can add up to 1.7 GB, bringing total usage to 29.7 GB. 1 GPU can run it, including NVIDIA GeForce RTX 5090.

All compatible consumer-level GPUs are running near their VRAM limit. You may also want to consider professional GPUs (e.g., NVIDIA A100, H100) which offer significantly more VRAM. For more headroom and better throughput, consider a multi-GPU configuration with tensor parallelism (supported by tools like vLLM, llama.cpp, or text-generation-inference).

Decent

Enough VRAM, may be tight

Which Devices Can Run EstopianMaid 13B?

FP16 · 28.0 GB

15 devices with unified memory can run EstopianMaid 13B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Studio M4 Max (36 GB).

Related Models

Frequently Asked Questions

How much VRAM does EstopianMaid 13B need?

EstopianMaid 13B requires 28.0 GB of VRAM at FP16. Full 4K context adds up to 1.7 GB (29.7 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 13.0B × 16 bits ÷ 8 = 26 GB

KV Cache + Overhead 2 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 3.7 GB (at full 4K context)

VRAM usage by quantization

28.0 GB
29.7 GB

Learn more about VRAM estimation →

Can I run EstopianMaid 13B on a Mac?

EstopianMaid 13B requires at least 28.0 GB at FP16, 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 EstopianMaid 13B locally?

Yes — EstopianMaid 13B can run locally on consumer hardware. At FP16 quantization it needs 28.0 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is EstopianMaid 13B?

At FP16, EstopianMaid 13B can reach ~104 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

tok/s = (bandwidth GB/s ÷ model GB) × efficiency

Example: AMD Instinct MI300X5300 ÷ 28.0 × 0.55 = ~104 tok/s

Estimated speed at FP16 (28.0 GB)

~104 tok/s
~78 tok/s
~64 tok/s

Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.

Learn more about tok/s estimation →

What's the download size of EstopianMaid 13B?

At FP16, the download is about 26.03 GB.

Which GPUs can run EstopianMaid 13B?

1 consumer GPU can run EstopianMaid 13B at FP16 (28.0 GB). Top options include NVIDIA GeForce RTX 5090.

Which devices can run EstopianMaid 13B?

15 devices with unified memory can run EstopianMaid 13B at FP16 (28.0 GB), including Mac Mini M4 (32 GB), Mac Mini M4 Pro (48 GB), Mac Pro M2 Ultra (192 GB), 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.