---
license: apache-2.0
base_model: Qwen/Qwen3-Coder-Next
tags:
  - knot
  - fat-station
  - distributed-inference
  - qwen3next
  - moe
---

# qwen3-coder-next.knot

Sovereign `.knot` encoding of **Qwen3-Coder-Next** (`arch=qwen3next`) for the
Gnosis fat-station runtime. Converted from GGUF with `gguf-to-knot.py`
(K-quant block passthrough, arch-aware config).

## Why a knot

`.knot` is a range-addressable weight container: a station fetches only the
tensors for the layers it owns, over HTTP, instead of loading a whole file.
That is what lets an A3B MoE this size run **sharded across Cloudflare
Containers** (12 GiB each) rather than needing one large host.

## Architecture

Hybrid Mamba-2 gated-DeltaNet SSM with periodic full attention, and a
sparse MoE FFN on every layer. Roughly 3B parameters are active per token.
Long context is cheap because only the periodic attention layers carry a
KV cache.

## Serving

Pipeline-parallel across N stations, each owning a contiguous layer range:

```
FAT_STATION_KNOT=<this knot url>
FAT_STATION_SHARDED=1
FAT_STATION_ROLE=entry|mid|exit
FAT_STATION_LAYERS=0..6
```

MoE shards cleanly along layers: a layer owns its entire expert set, so
top-k routing never needs a tensor held by another station.

Published by AFFECTIVELY. https://huggingface.co/forkjoin-ai