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Parable-Qwen3-4B-Claude-Fable-5-GGUF
by AnkitAI · source Hugging Face · updated 2026-09-22
apache-2.02.3 GB~4 GB RAMsource aliveunlabeled
A 4B local coding model with agent instincts. Planning, tool habits and terminal reasoning distilled from real Claude Fable 5 agent sessions, not synthetic Q&A. Runs on ~2.5 GB of RAM.
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Source and license
- Source: https://huggingface.co/AnkitAI/Parable-Qwen3-4B-Claude-Fable-5-GGUF
- License: apache-2.0
- Requirements: about 4 GB of RAM, 2.3 GB on disk (estimate: suggested file size × 1.15 + 0.5 GB; a real measurement comes with lsh models). Runs with llama.cpp, ollama.
- Tags:
llama.cppggufqloraagenticcodingreasoningqwen3local-llmollamalm-studiotext-generationdataset:Glint-Research/Fable-5-tracesdataset:Roman1111111/gpt5.5-terminalendpoints_compatibleconversational
Numbers
- 348,992 downloads on Hugging Face
- 19 likes
- license apache-2.0
- 2.3 GB for Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q4_K_M.gguf
- 327,838 npm downloads a week for node-llama-cpp
- latest node-llama-cpp@3.22.1
Numbers as of 2026-10-02 21:00 UTC, from the source API.
Summary
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Reviews
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Files
| file | quant | size |
|---|---|---|
Parable-Qwen3-4B-Claude-Fable-5-GGUF-F16.gguf | F16 | 7.5 GB |
Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q4_K_M.gguf | Q4_K_M | 2.3 GB |
Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q5_K_M.gguf | Q5_K_M | 2.7 GB |
Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q6_K.gguf | Q6_K | 3.1 GB |
Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q8_0.gguf | Q8_0 | 4.0 GB |
From the source README
Parable-Qwen3-4B-Claude-Fable-5-GGUF
A 4B local coding model with agent instincts. Planning, tool habits and
terminal reasoning distilled from real Claude Fable 5 agent sessions, not
synthetic Q&A. Runs on ~2.5 GB of RAM.
ollama run hf.co/AnkitAI/Parable-Qwen3-4B-Claude-Fable-5-GGUF:Q4_K_M
v3.1 (2026-08-11)
Retrained on corpus v3.1: the v2 agent traces plus 1,807 execution-verified
solutions generated by the previous build and kept only where the code actually
ran against its tests. Two seeds souped, merged at the v2.1 scale.
The result matches or beats base Qwen3-4B on all four execution benchmarks,
where the previous build trailed it on three. If you pulled this model before
11 August 2026, re-pull.
Files
| File | Quant | Size | |
|---|---|---|---|
| Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q4_K_M.gguf | Q4_K_M | 2.5 GB | recommended |
| Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q5_K_M.gguf | Q5_K_M | 2.9 GB | |
| Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q6_K.gguf | Q6_K | 3.3 GB | |
| Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q8_0.gguf | Q8_0 | 4.3 GB | |
| Parable-Qwen3-4B-Claude-Fable-5-GGUF-F16.gguf | F16 | 8.1 GB | for re-quantizing |
What it is good at
- It answers. Base Qwen3-4B spends its whole budget inside `` on
- 34% of ordinary prompts and returns nothing. This model answers 34/34 on
- the same suite, with 140x less reasoning text and no thinking-mode flag to
- manage.
- Agent-shaped reasoning. Trained on genuine multi-step agent sessions,
- so plans, tool selection and terminal workflows come out structured
- instead of improvised.
- Small enough to keep open. Q4_K_M is 2.5 GB. Laptop, old GPU, modest
- desktop — it runs, offline, with your code staying on your machine.
Evaluation
Measured on identical harnesses, greedy decoding, Q4_K_M builds, thinking
disabled on every row. Base and this model run through the same instrument i…
Card id model:hf:AnkitAI/Parable-Qwen3-4B-Claude-Fable-5-GGUF · collected 2026-10-02 21:00 UTC · JSON