AnkitAI / text-generation Open weights updated 1 month ago

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.

Params
4.0 B
Context
40,960
Downloads 30d
213 K
Likes
29
Commercial use: allowed apache-2.0 Not gated GGUF View on Hugging Face ↗

Download history

daily snapshots · 89 days
▲ 45 K in the last 30 days (17.3%)
515 K186 K
Aug 14Sep 12Oct 12Nov 10

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q4_K_M.gguf Q4_K_M 2.5 GB 3.8 GB ✅ Runs comfortably
Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q5_K_M.gguf Q5_K_M 2.9 GB 4.3 GB ✅ Runs comfortably
Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q6_K.gguf Q6_K 3.3 GB 4.7 GB ✅ Runs comfortably
Parable-Qwen3-4B-Claude-Fable-5-GGUF-Q8_0.gguf Q8_0 4.3 GB 5.8 GB ✅ Runs comfortably
Parable-Qwen3-4B-Claude-Fable-5-GGUF-F16.gguf GGUF 8.1 GB 10.0 GB ✅ Runs comfortably
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub
~ · ollama · Q4_K_M
$ ollama run parable-qwen3-4b-claude-fable-5-gguf

# pin the quantization explicitly
$ ollama run parable-qwen3-4b-claude-fable-5-gguf-q4_k_m
est. VRAM 3.8 GBon RTX 4090 · 24 GBJSON API →

Specifications

Parameters
4.0 B
Context length
40,960
Licence
apache-2.0
First seen on the Hub
2026-07-09
Base model
Qwen3-4B
Training datasets
Glint-Research/Fable-5-traces, Roman1111111/gpt5.5-terminal
Added to our catalog
2026-08-14

Family

Base model and the most-downloaded derivatives in the catalog.

Compare with any text-generation model