empero-ai·Qwen3_5ForConditionalGeneration

Qwable 9B Claude Fable 5 — Hardware Requirements & GPU Compatibility

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Qwable 9B Claude Fable 5 is a 9.4B-parameter open language model from empero-ai. It supports a context window of up to 262,144 tokens. At BF16 it needs about 19.39 GB of VRAM — see which GPUs and Macs can run it below.

17.9K downloads 105 likes262K context
Based on Qwen3.5 9B

Specifications

Publisher
empero-ai
Parameters
9.4B
Architecture
Qwen3_5ForConditionalGeneration
Context Length
262,144 tokens
Vocabulary Size
248,320
Release Date
2026-06-15
License
Apache 2.0

Get Started

How Much VRAM Does Qwable 9B Claude Fable 5 Need?

Select a quantization to see compatible GPUs below.

QuantizationBitsVRAM
BF16est.16.0019.4 GB

est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.

Which GPUs Can Run Qwable 9B Claude Fable 5?

BF16 · 19.4 GB

Qwable 9B Claude Fable 5 (BF16) requires 19.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 26+ GB is recommended. Using the full 262K context window can add up to 34.1 GB, bringing total usage to 53.5 GB. 8 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.

Which Devices Can Run Qwable 9B Claude Fable 5?

BF16 · 19.4 GB

41 devices with unified memory can run Qwable 9B Claude Fable 5, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).

Runs great

Plenty of headroom

Related Models

Frequently Asked Questions

How much VRAM does Qwable 9B Claude Fable 5 need?

Qwable 9B Claude Fable 5 requires 19.4 GB of VRAM at BF16. Full 262K context adds up to 34.1 GB (53.5 GB total).

VRAM = Weights + KV Cache + Overhead

Weights = 9.4B × 16 bits ÷ 8 = 18.8 GB

KV Cache + Overhead 0.6 GB (at 2K context + ~0.3 GB framework)

KV Cache + Overhead 34.7 GB (at full 262K context)

VRAM usage by quantization

19.4 GB
53.5 GB

Learn more about VRAM estimation →

Can I run Qwable 9B Claude Fable 5 on a Mac?

Qwable 9B Claude Fable 5 requires at least 19.4 GB at BF16, 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 Qwable 9B Claude Fable 5 locally?

Yes — Qwable 9B Claude Fable 5 can run locally on consumer hardware. At BF16 quantization it needs 19.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.

How fast is Qwable 9B Claude Fable 5?

At BF16, Qwable 9B Claude Fable 5 can reach ~227 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~34 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.

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

Example: NVIDIA B2008000 ÷ 19.4 × 0.65 = ~268 tok/s

Estimated speed at BF16 (19.4 GB)

~268 tok/s
~34 tok/s
~268 tok/s
~227 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 Qwable 9B Claude Fable 5?

At BF16, the download is about 18.82 GB.

Which GPUs can run Qwable 9B Claude Fable 5?

8 consumer GPUs can run Qwable 9B Claude Fable 5 at BF16 (19.4 GB). Top options include NVIDIA GeForce RTX 5090, AMD Radeon RX 7900 XT, AMD Radeon RX 7900 XTX. 1 GPU have plenty of headroom for comfortable inference.

Which devices can run Qwable 9B Claude Fable 5?

41 devices with unified memory can run Qwable 9B Claude Fable 5 at BF16 (19.4 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.