---
license: apache-2.0
base_model: Jackrong/Qwopus3.6-35B-A3B-v1
tags:
  - gguf
  - quantized
  - apex
  - moe
  - mixture-of-experts
  - qwen3.5
  - reasoning
  - chain-of-thought
---

# Qwopus 3.6 35B-A3B v1 APEX GGUF

**APEX (Adaptive Precision for EXpert Models)** quantizations of [Jackrong/Qwopus3.6-35B-A3B-v1](https://huggingface.co/Jackrong/Qwopus3.6-35B-A3B-v1).

**Brought to you by the [LocalAI](https://github.com/mudler/LocalAI) team** | [APEX Project](https://github.com/mudler/apex-quant)

## Available Files

| File | Profile | Size | Best For |
|------|---------|------|----------|
| Qwopus3.6-35B-A3B-v1-APEX-I-Quality.gguf | I-Quality | 23 GB | Highest quality with imatrix |
| Qwopus3.6-35B-A3B-v1-APEX-Quality.gguf | Quality | 23 GB | Highest quality standard |
| Qwopus3.6-35B-A3B-v1-APEX-I-Balanced.gguf | I-Balanced | 25 GB | Best overall quality/size ratio |
| Qwopus3.6-35B-A3B-v1-APEX-Balanced.gguf | Balanced | 25 GB | General purpose |
| Qwopus3.6-35B-A3B-v1-APEX-I-Compact.gguf | I-Compact | 17 GB | Consumer GPUs, best quality/size |
| Qwopus3.6-35B-A3B-v1-APEX-Compact.gguf | Compact | 17 GB | Consumer GPUs |
| Qwopus3.6-35B-A3B-v1-APEX-I-Mini.gguf | I-Mini | 14 GB | Smallest viable, fastest inference |

## What is APEX?

APEX is a quantization strategy for Mixture-of-Experts (MoE) models. It classifies tensors by role (routed expert, shared expert, attention) and applies a layer-wise precision gradient — edge layers get higher precision, middle layers get more aggressive compression. I-variants use diverse imatrix calibration (chat, code, reasoning, tool-calling, agentic traces, Wikipedia).

See the [APEX project](https://github.com/mudler/apex-quant) for full details.

## Architecture

- **Base Model**: [Jackrong/Qwopus3.6-35B-A3B-v1](https://huggingface.co/Jackrong/Qwopus3.6-35B-A3B-v1)
- **Architecture**: Qwen3.5-MoE 35B-A3B
- **Layers**: 40
- **Experts**: 256 routed (8 active per token)
- **Total Parameters**: ~35B
- **Active Parameters**: ~3B per token
- **APEX Config**: 6+6 symmetric edge gradient across 40 layers
- **Calibration**: v1.3 diverse dataset (chat, code, reasoning, tool-calling, multilingual)

## Run with LocalAI

```bash
local-ai run mudler/Qwopus3.6-35B-A3B-v1-APEX-GGUF@Qwopus3.6-35B-A3B-v1-APEX-I-Balanced.gguf
```

## Credits

APEX is brought to you by the [LocalAI](https://github.com/mudler/LocalAI) team. Developed through human-driven, AI-assisted research. Built on [llama.cpp](https://github.com/ggerganov/llama.cpp).