Qwen2.5-MOE-6x1.5B-DeepSeek-Reasoning-e32-8.71B-gguf
| Property | Value |
|---|---|
| Total Parameters | 8.71B |
| Base Architecture | Mixture of Experts (MOE) |
| Context Length | 128k tokens |
| Quantizations | Q4_K_S, Q8_0 |
What is Qwen2.5-MOE-6x1.5B-DeepSeek-Reasoning-e32-8.71B-gguf?
This is an experimental Mixture of Experts (MOE) model that combines six Qwen 2.5 1.5B models into a unified 8.71B parameter model. It features specialized reasoning capabilities through the integration of DeepSeek technology and supports an extensive 128k token context window. The model incorporates one captain/controller model with a shared expert and five main expert models, creating a sophisticated neural network architecture.
Implementation Details
The model architecture consists of multiple specialized components working in concert. The captain/controller (with .01 shared expert) utilizes DeepSeek-R1-Distill-Qwen-1.5B-uncensored, while the main experts include various fine-tuned versions of Qwen and DeepSeek models. By default, it activates 4 out of 6 experts, though users can enable all 6 for optimal performance.
- Float32 mastering for improved generation quality
- Supports multiple templating systems including Jinja, Llama 3, and Chatml
- Recommended temperature range of 0.4 to 0.8
- Minimum context setting of 4k tokens, with 8k+ recommended
Core Capabilities
- Advanced reasoning and analytical processing
- Uncensored output generation
- Multi-step thinking and problem decomposition
- Flexible template support
- Extended context handling up to 128k tokens
Frequently Asked Questions
Q: What makes this model unique?
The model's unique strength lies in its MOE architecture that combines six specialized 1.5B parameter models, each contributing different expertise while maintaining a relatively small total parameter count. This allows for sophisticated reasoning capabilities typically associated with much larger models.
Q: What are the recommended use cases?
The model is versatile and can be used for general-purpose tasks, but particularly excels in scenarios requiring complex reasoning, multi-step thinking, and detailed analysis. It's important to note that performance can be variable, ranging from basic to exceptional depending on the specific task and configuration.
