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mudler/holo3-35b-a3b-apex-gguf overview

APEX (Adaptive Precision for EXpert Models) quantizations of Holo3-35B-A3B. Brought to you by the LocalAI team | APEX Project | Technical Report

ggufquantizedapexmoemixture-of-expertsholo3vlmvisionbase_model:Hcompany/Holo3-35B-A3Bbase_model:quantized:Hcompany/Holo3-35B-A3Blicense:apache-2.0endpoints_compatibleregion:usconversational
mudler/holo3-35b-a3b-apex-gguf visual
Downloads
3,156
Likes
4
Pipeline
Library
Visibility
Public
Access
Open

Repository Files & Downloads

8 files detected
Direct downloads for all repository files
FileTypeQuantizationSizeLink
Holo3-35B-A3B-APEX-Balanced.gguf GGUF 23.87 GB Download
Holo3-35B-A3B-APEX-Compact.gguf GGUF 16.11 GB Download
Holo3-35B-A3B-APEX-I-Balanced.gguf GGUF 23.87 GB Download
Holo3-35B-A3B-APEX-I-Compact.gguf GGUF 16.11 GB Download
Holo3-35B-A3B-APEX-I-Mini.gguf GGUF 13.33 GB Download
Holo3-35B-A3B-APEX-I-Quality.gguf GGUF 21.25 GB Download
Holo3-35B-A3B-APEX-Quality.gguf GGUF 21.25 GB Download
mmproj.gguf GGUF 857.62 MB Download

Model Details Live

Model Slug
mudler/holo3-35b-a3b-apex-gguf
Author
mudler
Pipeline Task
Library
Created
2026-04-02
Last Modified
2026-04-04
Gated
No
Private
No
HF SHA
57998c466360e3c2e029c30f0c0a4ef78413cabb
License
apache-2.0
Language
Unknown
Base Model
Hcompany/Holo3-35B-A3B

Metadata Inspector

Normalized metadata (stored in metadata_json)
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  "metadata": {},
  "card_data": {
    "license": "apache-2.0",
    "base_model": "Hcompany/Holo3-35B-A3B",
    "tags": [
      "gguf",
      "quantized",
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      "mixture-of-experts",
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      "vlm",
      "vision"
    ],
    "frontmatter": {
      "license": "apache-2.0",
      "base_model": "Hcompany/Holo3-35B-A3B",
      "tags": [
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    "summary": "**APEX (Adaptive Precision for EXpert Models)** quantizations of Holo3-35B-A3B. **Brought to you by the LocalAI team** | APEX Project | Technical Report",
    "quick_links": [],
    "benchmark_table_html": "",
    "readme_markdown": "---\nlicense: apache-2.0\nbase_model: Hcompany/Holo3-35B-A3B\ntags:\n  - gguf\n  - quantized\n  - apex\n  - moe\n  - mixture-of-experts\n  - holo3\n  - vlm\n  - vision\n---\n\n# Holo3-35B-A3B APEX GGUF\n\n**APEX (Adaptive Precision for EXpert Models)** quantizations of [Holo3-35B-A3B](https://huggingface.co/Hcompany/Holo3-35B-A3B).\n\n**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)\n\n## Benchmark Results\n\nBenchmarks coming soon. For reference APEX benchmarks on the same Qwen3.5-MoE architecture, see [mudler/Qwen3.5-35B-A3B-APEX-GGUF](https://huggingface.co/mudler/Qwen3.5-35B-A3B-APEX-GGUF).\n\n## Available Files\n\n| File | Profile | Size | Best For |\n|------|---------|------|----------|\n| Holo3-35B-A3B-APEX-I-Balanced.gguf | I-Balanced | ~24 GB | Best overall quality/size ratio |\n| Holo3-35B-A3B-APEX-I-Quality.gguf | I-Quality | ~22 GB | Highest quality with imatrix |\n| Holo3-35B-A3B-APEX-Quality.gguf | Quality | 22 GB | Highest quality standard |\n| Holo3-35B-A3B-APEX-Balanced.gguf | Balanced | 24 GB | General purpose |\n| Holo3-35B-A3B-APEX-I-Compact.gguf | I-Compact | ~17 GB | Consumer GPUs, best quality/size |\n| Holo3-35B-A3B-APEX-Compact.gguf | Compact | 17 GB | Consumer GPUs |\n| Holo3-35B-A3B-APEX-I-Mini.gguf | I-Mini | ~13 GB | Smallest viable, fastest inference |\n| mmproj.gguf | Vision projector | ~858 MB | Required for image understanding |\n\n## What is APEX?\n\nAPEX 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).\n\nSee the [APEX project](https://github.com/mudler/apex-quant) for full details, technical report, and scripts.\n\n## Architecture\n\n- **Model**: Holo3-35B-A3B (Qwen3.5-MoE variant, VLM)\n- **Layers**: 40 (30 linear attention + 10 full attention)\n- **Experts**: 256 routed + 1 shared (8 active per token)\n- **Total Parameters**: ~35B\n- **Active Parameters**: ~3B per token\n- **Vision**: Built-in vision encoder (mmproj included)\n- **APEX Config**: 5+5 symmetric edge gradient across 40 layers\n\n## Run with LocalAI\n\n```bash\nlocal-ai run mudler/Holo3-35B-A3B-APEX-GGUF@Holo3-35B-A3B-APEX-I-Balanced.gguf\n```\n\n## Credits\n\nAPEX 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).\n",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "quantized",
    "apex",
    "moe",
    "mixture-of-experts",
    "holo3",
    "vlm",
    "vision",
    "base_model:Hcompany/Holo3-35B-A3B",
    "base_model:quantized:Hcompany/Holo3-35B-A3B",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
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  "likes": 4,
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  "gated": false,
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  "last_modified": "2026-04-04T22:50:40.000Z",
  "created_at": "2026-04-02T21:08:10.000Z",
  "pipeline_tag": "",
  "library_name": ""
}
Source payload excerpt (from Hugging Face API)
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