Production-ready GGUF quantization of deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B for distributed text generation and conversation — powered by the Aether edge inference runtime on Edgework.ai.

Model Details

Property	Value
Base model	deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
Parameters	1.5B
Architecture	Qwen2
Quantization	Q4_K_M
Format	GGUF
Size	~0.9 GB
License	apache-2.0

Usage

With llama.cpp

./llama-cli -m DeepSeek-R1-Distill-Qwen-1.5B-Q4_K_M.gguf -p "Your prompt here" -n 256

With Aether (Distributed Inference)

This model is deployed across the Aether distributed inference network. Weights are layer-sharded and distributed across multiple edge nodes for parallel inference.

Also available: `.knot` (sovereign format)

This repo ships deepseek-r1-1.5b.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/deepseek-r1-distill-qwen-1.5b-gguf deepseek-r1-1.5b.knot --local-dir ./knots

Full format spec: KNOT_FORMAT.md. Inspect the header with bun run open-source/bitwise/scripts/dump-knot.ts deepseek-r1-1.5b.knot.

Deployment Architecture

This model runs on the Aether distributed inference runtime — a custom engine that shards model layers across multiple nodes for parallel execution:

Coordinator receives requests and manages token generation
Layer nodes each hold a subset of model layers (2 nodes for this model)
Hidden states flow between nodes via gRPC
Zero cold start via warm pool scheduling

Deployed via Edgework.ai — bringing fast, cheap, and private inference as close to the user as possible.

About

Published by AFFECTIVELY · Managed by @buley

We quantize and publish production-ready models for distributed edge inference via the Aether runtime. Every release is tested for correctness and stability before publication.

All models · GitHub · Edgework.ai

forkjoin-ai/deepseek-r1-distill-qwen-1.5b-gguf

Deepseek R1 Distill Qwen 1.5b (GGUF, Q4_K_M)