0.1.44.1-poly.2

DeepSeek V4 Flash runs on PolyStrata, and prompts are read faster on a card that holds the model.

What changed since 0.1.44.1-poly.1

• DeepSeek V4 Flash is the seventh model: ./setup.sh --family deepseek installs Unsloth's UD-IQ2_XXS (three files, 91 GB) on strata-poly, the engine GLM 5.3 Flash runs on. On an RTX 5090 with 120 GB of RAM it writes a short chat at 56 tokens/s and reads a 30K-token prompt at 1,040 tokens/s; llama.cpp on the same PC wrote 25 to 28 tokens/s and read a 3K prompt at 96. Its cache keeps 6,880 bytes a token, so long contexts fit beside the experts: a 487,529-token prompt in a 512K context was read and answered in 32 minutes, with the three facts hidden in it found. Its greedy tokens match llama.cpp's up to near ties. Linux and one NVIDIA card for now, about 72 GB of RAM beside a 32 GB card. More in docs/DEEPSEEK.md.
• Faster prompt reading for every model of strata-poly: a prompt batch now routes its tokens on the card instead of the CPU, computes products with few outputs without cuBLAS, and runs the causal convolutions of all its tokens at once. Tiel Coder on an RTX 5090 reads a 32K prompt at 7,520 to 8,110 tokens/s instead of 6,090 to 6,870, and Qwen3.6 UD-Q4_K_XL a 4K prompt at 8,100 to 8,400 instead of 5,582. Where most experts stay in RAM (an 8 GB laptop) the copy of the experts to the card still sets the pace, so the change there is small: Gemma 4 reads a 2K prompt at 1,290 tokens/s instead of 1,084. Writing speed did not change.
• Experts stored as MXFP4, which no kernel here runs on the card, are converted at load to Q5_0, which holds the same values exactly; DeepSeek's file has two such layers.
• The tokenizer gives control tokens as their text, as llama.cpp does, and the server reads DeepSeek's DSML tool calls.

The engine changed, so the zip below is a new ready-made Windows engine; the installer downloads it and checks its SHA-256.

How fast

The README has the tables, now with DeepSeek V4 Flash and Tiel Coder's new workstation numbers; docs/BACKENDS.md has the runs.

Install

Download the source below, or git clone the repository. Then run START-HERE.bat on Windows or ./setup.sh on Linux. An earlier install updates with UPDATE.bat or ./update.sh.

Limits

• The six added models are experimental. DeepSeek V4 Flash has run on one machine, with a 32 GB card and 120 GB of RAM.
• The ready-made engine is for Windows and CUDA 13 only; CUDA 12 and AMD cards compile on your PC.
• GLM 5.3 Flash and DeepSeek V4 Flash need 70 to 100 GB of RAM, and about 8 GB more than their files in a container.
• AMD cards on Windows run Qwen3.8-Flash-Next only.

Most of this project is the work of Strata's author and contributors.