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Production-ready GGUF quantization of Qwen/Qwen3-4B for distributed text generation and conversation — powered by the Aether edge inference runtime on Edgework.ai.
| Property | Value |
|---|---|
| Base model | Qwen/Qwen3-4B |
| Parameters | 4B |
| Architecture | Qwen2 |
| Quantization | Q4_K_M |
| Format | GGUF |
| Size | ~2.4 GB |
| License | apache-2.0 |
./llama-cli -m Qwen3-4B-Q8_0.gguf -p "Your prompt here" -n 256.knot (sovereign format)qwen3-4b.knot — the model weights in the KNOT container that the Aether distributed-inference runtime loads natively (the GGUF, when present, sits right beside it). A KNOT is a single self-describing file with a JSON table-of-contents, so any single tensor is one HTTP Range request — ideal for streaming weights to edge nodes.| GGUF | KNOT | |
|---|---|---|
| Container | format-specific header | single file, JSON table-of-contents |
| Per-tensor fetch | whole-file oriented | one tensor = one Range request |
| Ecosystem | broad (llama.cpp, …) | Aether / Gnosis runtime |
huggingface-cli download forkjoin-ai/qwen3-4b-gguf qwen3-4b.knot --local-dir ./knotsbun run open-source/bitwise/scripts/dump-knot.ts qwen3-4b.knot.