---
license: apache-2.0
base_model: samuelcardillo/Qwopus-MoE-35B-A3B-GGUF
tags:
  - gguf
  - quantized
  - apex
  - moe
  - mixture-of-experts
  - qwen3.5
  - claude-distill
---





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# Qwopus-MoE-35B-A3B APEX GGUF

**APEX (Adaptive Precision for EXpert Models)** quantizations of [Qwopus-MoE-35B-A3B](https://huggingface.co/samuelcardillo/Qwopus-MoE-35B-A3B-GGUF).

**Brought to you by the [LocalAI](https://github.com/mudler/LocalAI) team** | [APEX Project](https://github.com/mudler/apex-quant) | [Technical Report](https://github.com/mudler/apex-quant/blob/main/paper/APEX_Technical_Report.pdf)

## Available Files

| File | Profile | Size | Best For |
|------|---------|------|----------|
| Qwopus-MoE-35B-A3B-APEX-I-Balanced.gguf | I-Balanced | TBD | Best overall quality/size ratio (with imatrix) |
| Qwopus-MoE-35B-A3B-APEX-I-Quality.gguf | I-Quality | TBD | Best quality/compression ratio (with imatrix) |
| Qwopus-MoE-35B-A3B-APEX-Quality.gguf | Quality | TBD | Best quality/compression ratio |
| Qwopus-MoE-35B-A3B-APEX-Balanced.gguf | Balanced | TBD | Best absolute quality |
| Qwopus-MoE-35B-A3B-APEX-I-Compact.gguf | I-Compact | TBD | Consumer GPUs (with imatrix) |
| Qwopus-MoE-35B-A3B-APEX-Compact.gguf | Compact | TBD | Consumer GPUs |
| Qwopus-MoE-35B-A3B-APEX-I-Mini.gguf | I-Mini | TBD | Smallest viable |

## 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, technical report, and scripts.

## Architecture

- **Model**: Qwopus-MoE-35B-A3B (qwen3_5_moe)
- **Layers**: 40 (hybrid: linear attention + full attention every 4th layer)
- **Experts**: 256 routed (8 active per token)
- **Total Parameters**: ~35B
- **Active Parameters**: ~3B per token
- **Origin**: Claude Opus 4.6 QLoRA distill of Qwen3.5-35B-A3B
- **APEX Config**: 5+5 symmetric edge gradient across 40 layers
- **Calibration**: v1.3 diverse dataset (chat, code, reasoning, multilingual, tool-calling, Wikipedia)
- **Source**: [samuelcardillo/Qwopus-MoE-35B-A3B](https://huggingface.co/samuelcardillo/Qwopus-MoE-35B-A3B)

## Run with LocalAI

```bash
local-ai run mudler/Qwopus-MoE-35B-A3B-APEX-GGUF@Qwopus-MoE-35B-A3B-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).