The GGUF files in this repository were converted using the latest build of llama.cpp with the --no-nextn conversion flag to ensure compatibility across local inference runtimes.

Model Overview

Base Model: Umranz/Hydra-Turbo
Architecture: Qwen 3.5 (Hybrid Linear Attention + Full Attention)
Parameters: 8.95B (9.0B label)
Context Length: 262,144 tokens
Vocabulary Size: 248,320
License: Apache 2.0

Available Files and Quantization Formats

File Name	Quantization Type	File Size	Description
`hydra-turbo-q4_0.gguf`	Q4_0	4.95 GB	Legacy 4-bit quantization. Fast execution, low VRAM footprint.
`hydra-turbo-q4_k_m.gguf`	Q4_K_M	5.24 GB	Recommended medium 4-bit quant. Balanced accuracy and memory usage.
`hydra-turbo-q5_k_m.gguf`	Q5_K_M	6.02 GB	High-precision 5-bit quant. Reduced perplexity loss with minimal speed overhead.
`hydra-turbo-q8_0.gguf`	Q8_0	8.87 GB	Near-lossless 8-bit quantization. Maximum output quality.

Technical Specifications

Layers: 32 Main Transformer Blocks (SSM / Gated Delta Net + Full Attention)
Embedding Length: 4096
Feed Forward Dimension: 12288
Attention Heads: 16 (Key-Value Heads: 4)
Rotary Position Embedding (RoPE): Frequency Base 10,000,000
Layer Norm Epsilon: 1e-6

Prompt Template

Hydra-Turbo uses the standard Qwen Chat Template:

text

<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
Your query here<|im_end|>
<|im_start|>assistant

Umranz/Hydra-Turbo-GGUF

Hydra-Turbo-GGUF

Model Overview

Available Files and Quantization Formats

Technical Specifications

Prompt Template

Umranz/
Hydra-Turbo-GGUF