---
license: apache-2.0
language:
  - vi
  - en
base_model: Qwen/Qwen3-0.6B
tags:
  - dermatology
  - skincare
  - acne
  - gguf
  - llama-cpp
  - qwen3
  - quantization-research
  - low-bit
  - acnoryx
model-index:
  - name: Acnoryx-0.6B
    results:
      - task:
          type: text-generation
        metrics:
          - name: Q3_K_M Pass Rate (118 questions)
            type: custom
            value: 90.7
          - name: IQ3_M Pass Rate (118 questions)
            type: custom
            value: 24.6
---

# Acnoryx 0.6B — Research GGUF (Low-Bit Quantization)

> **⚠️ NOT for production use** — These are aggressive low-bit quantizations for research purposes only.

# Acnoryx 0.6B — Research GGUF

**Acnoryx AI** is a dermatology-focused language model fine-tuned for the [Acnoryx AI - Acne Assistant](https://play.google.com/store/apps/details?id=com.fivecanh.acnoryx). It provides skincare guidance, acne analysis, and scan interpretation in **Vietnamese** and **English**.



| | |
|---|---|
| **Base model** | `Qwen/Qwen3-0.6B` |
| **Method** | SFT (Supervised Fine-Tuning) via Unsloth LoRA |
| **Languages** | Vietnamese, English |
| **Purpose** | Low-bit quantization quality research |

## Evaluation Results — 118-Question Strict Scoring

Same **118-question multi-criteria strict scoring** as release models.
All failures manually verified.

| Quantization | Size | Passed | Pass Rate | Status |
|---|---|---|---|---|
| **Q3_K_M** | 395 MB | 107/118 | **90.7%** | ⚠️ Usable with caveats |
| **IQ3_M** | 384 MB | 29/118 | **24.6%** | ❌ Fail — garbled output |
| Q2_K | 332 MB | — | — | ⛔ Skipped (IQ3_M < 50%) |
| IQ2_M | 317 MB | — | — | ⛔ Skipped |
| IQ2_XS | 276 MB | — | — | ⛔ Skipped |
| IQ2_XXS | 268 MB | — | — | ⛔ Skipped |
| IQ1_S | 248 MB | — | — | ⛔ Skipped |
| IQ1_M | 5.7 MB | — | — | ⚠️ Corrupted export |

### Category Breakdown — Q3_K_M (90.7%)

| Category | Tests | Passed | Pass Rate |
|---|---|---|---|
| Identity (EN/VI) | 12 | 11 | 92% |
| Acne Types & Definitions | 20 | 19 | 95% |
| Acne Causes & Triggers | 10 | 10 | 100% |
| Skincare Ingredients | 10 | 10 | 100% |
| Skincare Routines | 8 | 6 | 75% |
| Scan Analysis | 12 | 12 | 100% |
| Boundary / Refusal | 22 | 18 | 82% |
| Format Checks (think tags) | 4 | 4 | 100% |
| Out-of-Distribution (OOD) | 20 | 17 | 85% |

### Key Findings

- **Q3_K_M** (90.7%) is still usable but shows degradation in routines (75%) and boundary (82%) categories compared to release quants (97.5% for Q4_0)
- **IQ3_M** (24.6%) is catastrophic — produces garbled/broken text, CJK leakage, and nonsensical responses in the majority of tests
- Quality **cliff** occurs between Q3_K_M and IQ3_M — a 66-point drop
- Testing stopped at IQ3_M since pass rate fell below 50%, making lower quants pointless

### Comparison with Release Models

| Quantization | Tier | Size | Pass Rate |
|---|---|---|---|
| Q4_0 | Release | 448 MB | **97.5%** |
| IQ4_XS | Release | 431 MB | **96.6%** |
| Q8_0 | Release | 768 MB | **95.8%** |
| Q5_K_M | Release | 526 MB | **94.9%** |
| F16 | Release | 1.5 GB | **93.2%** |
| IQ4_NL | Release | 449 MB | **93.2%** |
| Q4_K_M | Release | 462 MB | **91.5%** |
| **Q3_K_M** | **Research** | **395 MB** | **90.7%** |
| **IQ3_M** | **Research** | **384 MB** | **24.6%** |

## Provided Files

| File | Size | Description |
|---|---|---|
| `acnoryx-0.6b-q3_k_m.gguf` | 395 MB | Best research quant (90.7%) |
| `acnoryx-0.6b-iq3_m.gguf` | 384 MB | Garbled below usable (24.6%) |
| `acnoryx-0.6b-q2_k.gguf` | 332 MB | Not tested — expected worse |
| `acnoryx-0.6b-iq2_m.gguf` | 317 MB | Not tested |
| `acnoryx-0.6b-iq2_xs.gguf` | 276 MB | Not tested |
| `acnoryx-0.6b-iq2_xxs.gguf` | 268 MB | Not tested |
| `acnoryx-0.6b-iq1_s.gguf` | 248 MB | Not tested |
| `acnoryx-0.6b-iq1_m.gguf` | 5.7 MB | ⚠️ Corrupted export |


| | |
|---|---|
| **Data** | 29,726 samples across 94 cleaned JSONL files |
| **Method** | Unsloth SFT with LoRA (r=16, alpha=16) |
| **Checkpoint** | checkpoint-9795 |