Model Intelligence Sheet
mudler/qwen3.5-35b-a3b-claude-distilled-apex-gguf overview
APEX (Adaptive Precision for EXpert Models) quantizations of Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled. Brought to you by the LocalAI team | APEX Project | Technical Report
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Direct downloads for all repository files
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Qwen3.5-35B-A3B-Claude-Distilled-APEX-Balanced.gguf | GGUF | — | 23.87 GB | Download |
| Qwen3.5-35B-A3B-Claude-Distilled-APEX-Compact.gguf | GGUF | — | 16.11 GB | Download |
| Qwen3.5-35B-A3B-Claude-Distilled-APEX-I-Balanced.gguf | GGUF | — | 23.87 GB | Download |
| Qwen3.5-35B-A3B-Claude-Distilled-APEX-I-Compact.gguf | GGUF | — | 16.11 GB | Download |
| Qwen3.5-35B-A3B-Claude-Distilled-APEX-I-Mini.gguf | GGUF | — | 13.33 GB | Download |
| Qwen3.5-35B-A3B-Claude-Distilled-APEX-I-Quality.gguf | GGUF | — | 21.25 GB | Download |
| Qwen3.5-35B-A3B-Claude-Distilled-APEX-Quality.gguf | GGUF | — | 21.25 GB | Download |
Model Details Live
Metadata Inspector
Normalized metadata (stored in metadata_json)
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"license": "apache-2.0",
"base_model": "Jackrong/Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled",
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"license": "apache-2.0",
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"summary": "**APEX (Adaptive Precision for EXpert Models)** quantizations of Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled. **Brought to you by the LocalAI team** | APEX Project | Technical Report",
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"benchmark_table_html": "",
"readme_markdown": "---\nlicense: apache-2.0\nbase_model: Jackrong/Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled\ntags:\n - gguf\n - quantized\n - apex\n - moe\n - mixture-of-experts\n - qwen3.5\n - claude-distilled\n---\n\n# Qwen3.5-35B-A3B Claude-Distilled APEX GGUF\n\n**APEX (Adaptive Precision for EXpert Models)** quantizations of [Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled](https://huggingface.co/Jackrong/Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled).\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| Qwen3.5-35B-A3B-Claude-Distilled-APEX-I-Balanced.gguf | I-Balanced | ~24 GB | Best overall quality/size ratio |\n| Qwen3.5-35B-A3B-Claude-Distilled-APEX-I-Quality.gguf | I-Quality | ~22 GB | Highest quality with imatrix |\n| Qwen3.5-35B-A3B-Claude-Distilled-APEX-Quality.gguf | Quality | ~22 GB | Highest quality standard |\n| Qwen3.5-35B-A3B-Claude-Distilled-APEX-Balanced.gguf | Balanced | ~24 GB | General purpose |\n| Qwen3.5-35B-A3B-Claude-Distilled-APEX-I-Compact.gguf | I-Compact | ~17 GB | Consumer GPUs, best quality/size |\n| Qwen3.5-35B-A3B-Claude-Distilled-APEX-Compact.gguf | Compact | ~17 GB | Consumer GPUs |\n| Qwen3.5-35B-A3B-Claude-Distilled-APEX-I-Mini.gguf | I-Mini | ~13 GB | Smallest viable, fastest inference |\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**: Qwen3.5-35B-A3B-Claude-Distilled (Qwen3.5-MoE, distilled from Claude 4.6 Opus reasoning)\n- **Layers**: 40\n- **Experts**: 256 routed + 1 shared (8 active per token)\n- **Total Parameters**: ~35B\n- **Active Parameters**: ~3B per token\n- **APEX Config**: 5+5 symmetric edge gradient across 40 layers\n- **Calibration**: v1.3 diverse dataset (chat, code, reasoning, multilingual, tool-calling, Wikipedia)\n\n## Run with LocalAI\n\n```bash\nlocal-ai run mudler/Qwen3.5-35B-A3B-Claude-Distilled-APEX-GGUF@Qwen3.5-35B-A3B-Claude-Distilled-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",
"qwen3.5",
"claude-distilled",
"base_model:Jackrong/Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled",
"base_model:quantized:Jackrong/Qwen3.5-35B-A3B-Claude-4.6-Opus-Reasoning-Distilled",
"license:apache-2.0",
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"created_at": "2026-04-03T23:26:59.000Z",
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Source payload excerpt (from Hugging Face API)
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