DeepSeek-V4.1-Flash-4bit-paged

Expert-paged build of pipenetwork/DeepSeek-V4.1-Flash-MLX-mixed-4_8bit. The weights that are read a fraction at a time live in their own containers, so a machine loads what it needs rather than all of it.

file	size	holds
model.safetensors	10.48 GiB	resident weights
experts.bin	284.77 GiB	routed experts
engram-layer-1/	51.50 GiB	engram table, layer 1
engram-layer-14/	51.50 GiB	engram table, layer 14
mtp/	7.85 GiB	draft head, off by default

Total 406.10 GiB. The bytes moved into containers of their own; they were not copied.

from gbx_lm.utils import load
model, tokenizer = load("GreenBitAI/DeepSeek-V4.1-Flash-4bit-paged")

Where the weights fit they are filled from experts.bin and the model runs the stock path at stock speed; where they do not, they stream from disk. Reading the machine decides that, not a flag.

To override that: GBX_PAGING=off holds the experts resident, GBX_ENGRAM=off holds the engram tables resident.

The directory also carries DeepSeek's own DSpark draft head, off unless asked for: GBX_DEEPSEEK_MTP=on decodes speculatively against it. It is converted from deepseek-ai/DeepSeek-V4.1-Flash and keeps that licence; no published MLX build carries it, which is why it is here.

Checked at build time, while the source checkpoint was still there to compare against:

• PASS bit-identical logits — exact on 5 prompt(s) to 160 tokens; 1 longer differ by at most 15, same greedy token throughout
• PASS layer-wise vs resident — 40 layers x 2 draws exact, 377.86 GiB peak for this gate

Quantization, tokenizer, chat template and licence are unchanged from pipenetwork/DeepSeek-V4.1-Flash-MLX-mixed-4_8bit.