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FreedomAISVR/Qwable-v1-MXFP4-MOE-GGUF overview

license: agpl 3.0 tags: qwable qwen3 qwen3.5 moe mixture of experts agentic claude fable distillation mxfp4 mxfp4 moe gguf image text to text pipeline tag: tex…

ggufqwableqwen3qwen3.5moemixture-of-expertsagenticclaudefabledistillationmxfp4mxfp4_moeimage-text-to-texttext-generationlicense:agpl-3.0endpoints_compatibleregion:usconversational

Runs locally from ~857.6 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

Repository Files & Downloads

2 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
mmproj-qwable-v1-f16.ggufGGUFF16857.6 MBDownload
qwable-v1-mxfp4_moe.ggufGGUFGGUF18.87 GBDownload

Model Details

Model IDFreedomAISVR/Qwable-v1-MXFP4-MOE-GGUF
AuthorFreedomAISVR
Pipelinetext-generation
Licenseagpl-3.0
Base modelQwen/Qwable-v1
Last modified2026-09-16T17:10:04.000Z

Model README

---

license: agpl-3.0

tags:

  • qwable
  • qwen3
  • qwen3.5
  • moe
  • mixture-of-experts
  • agentic
  • claude
  • fable
  • distillation
  • mxfp4
  • mxfp4_moe
  • gguf
  • image-text-to-text

pipeline_tag: text-generation

base_model: Qwen/Qwable-v1

---

Qwable-v1 MXFP4 MoE GGUF

GGUF quantization of lordx64/Qwable-v1 — an agentic coding model built by layering Claude Fable-5 tool-use behavior on top of a Claude Opus 4.7 reasoning distill of Qwen3.6-35B-A3B.

Model Details

  • Architecture: Qwen3.5 MoE, 41 blocks (40 layers + 1 MTP head), 256 experts (8 active/token)
  • Active Parameters: ~3B
  • Context: 262,144 tokens
  • Vision: Yes (27-layer SigLIP ViT)
  • License: AGPL-3.0
  • Base: Qwen3.6-35B-A3B → Opus 4.7 reasoning distill → Fable-5 agentic SFT

What's Included

| File | Type | Size | BPW |

|------|------|------|-----|

| qwable-v1-mxfp4_moe.gguf | MXFP4 (experts) + Q8_0 (non-experts) | ~18.87 GB | 4.56 |

| mmproj-qwable-v1-f16.gguf | Vision projector (F16) | ~0.88 GB | F16 |

Quantization Details

MXFP4_MOE

  • MoE expert weights (ffn_down_exps, ffn_gate_exps, ffn_up_exps) quantized to MXFP4
  • Non-expert weights (attention, shared experts, norms) quantized to Q8_0
  • Router weights kept at F32
  • Vision encoder and projector kept at F16 (not quantized)

Usage

# With llama.cpp (vision + text)
./llama-server -m qwable-v1-mxfp4_moe.gguf --mmproj mmproj-qwable-v1-f16.gguf --host 0.0.0.0 --port 8080

# Text-only (no vision)
./llama-cli -m qwable-v1-mxfp4_moe.gguf -p "Hello, how are you?"

Agentic Tool-Use

Qwable-v1 emits <tool_use> XML when prompted with an agent-style system prompt:

system: You are a coding agent. When you need to read, write, edit, or run code,
emit XML tool calls in this exact format:
<tool_use name="X" id="toolu_01abc">
{"...": "..."}
</tool_use>

Without the agent prompt, the model falls back to the Opus 4.7 reasoning prior (markdown code blocks).

Credits

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