Strata 0.2.4: DeepSeek V4.1-Flash in the Terminal (Terminal 0.2.4.2)

# Strata 0.2.4.2: DeepSeek launch and install fixes

Fixes for strata launch with DeepSeek and for the one-line installer. The Terminal's Control (0.1.49.2), install.sh and the three DeepSeek engine packages (0.1.49.2) changed. The app stays 0.2.3 and every Qwen engine package stays as it was, so there is nothing new to download for them.

What is fixed

• Faster DeepSeek on AMD Ryzen 3000 / Threadripper 3000 / EPYC 7002 CPUs. The 2.00 and IQ1_M sets answered up to 3x slower there; the answers are unchanged. The DeepSeek engine is now 0.1.49.2 (strata-dsv41-0.1.49.2-windows-x86_64-cuda-cuda13, -linux-x86_64-cuda-cuda13 and -linux-x86_64-hip-rx9070).
• DeepSeek setup no longer stops on a Qwen picture file in your models folder (#3927, #3917). If the folder you share between models held a Qwen vision file, DeepSeek setup picked it up by mistake and failed. It now ignores any picture file that is not DeepSeek's.
• Model files you already have are recognised for DeepSeek in the guided screen too, including Unsloth's UD-Q8_K_XL set (#3914). The "use model files I already have" screen called a downloaded UD-Q8_K_XL file unreadable. It now recognises DeepSeek sets by their file names, as strata launch --model-path already did.
• The right DeepSeek engine runs when you have more than one Strata install. Launch now picks the newest DeepSeek engine package of the install that is running, and of the install your model's settings came from, instead of an old path saved in the model's settings.
• A plain message when GitHub cannot be reached. DeepSeek setup checks for 10 seconds before it downloads anything and says in one line that GitHub is not reachable, instead of retrying for minutes.
• Faster returns to a conversation. DeepSeek keeps recent conversations (and a shared system prompt) on disk, so a returning agent or a sub-agent with the same system prompt answers sooner; up to 2 GB, cleaned after a week.
• The DeepSeek engine updates itself. A newer DeepSeek engine package in the signed feed is installed on the next strata launch (see Updating).
• DeepSeek no longer downloads the Qwen engine. A DeepSeek launch does not fetch or test-start the Strata (Qwen) engine, the llama.cpp source or CUDA libraries it never uses. strata launch --plan no longer promises that download.
• The disk check counts only what is still to download. If most of the model files are already in your models folder (also under the first release's file names), the model list no longer says "tight: needs more disk space". The room for the prepared model is still counted.
• Smaller wording fixes. A setup message that ended with a full stop no longer gets a second one ("engine.."), and the second sentence of "The model could not be installed. The model does not answer sensibly after the preparation: ..." starts with a capital.
• The install one-liners keep your terminal open on an error. install.sh is now a function that returns an error instead of closing the shell it runs in, and the commands in the README and docs download it first: curl -fsSL https://github.com/Niko1221/Strata/releases/latest/download/install.sh -o install.sh && sh install.sh.

Updating

• DeepSeek engine: it updates itself on the next launch. When the signed feed has a newer DeepSeek engine package for your PC (0.1.49.2 over 0.1.49), strata launch downloads it, checks it, starts it once, switches to it and removes the old one. If that fails you see one line and the engine you have keeps running; with no internet the launch goes on without waiting. An engine you gave with --dsv41-package or STRATA_DSV41_EXE is never replaced.
• From 0.2.4 or 0.2.4.1: run strata update in the Terminal. It fetches Control 0.1.49.2 and the next strata command runs it (strata --version says 0.2.4.2).
• New installs: use the command in the README (download install.sh, then run it).
• Mac: the Mac Terminal gets Control 0.1.49.2 too. DeepSeek is not on the Mac yet.

Downloads

Everything from 0.2.4.1 is attached again, so the release page still holds every file. New in this release: the three Control packages (strata-control-0.1.49.2-windows-x86_64.zip, -linux-x86_64.tar.gz, -macos-arm64.tar.gz), the three DeepSeek engine packages (strata-dsv41-0.1.49.2-windows-x86_64-cuda-cuda13.tar.gz, -linux-x86_64-cuda-cuda13.tar.gz, -linux-x86_64-hip-rx9070.tar.gz), install.sh, the feed and SHA256SUMS.txt. The installers, AppImages, dmg and Qwen engine packages are the 0.2.3 files.

> Update 0.2.4.1: DeepSeek setup now works from the installed Terminal. The 0.2.4 Terminal package was missing the DeepSeek preparation scripts, so setup stopped at "Preparing your model". If you installed 0.2.4, run strata update, then run your DeepSeek setup again. New installs get the fix automatically. The RTX 3060 figure below is corrected to the release defaults (8 to 10 tokens/s; DSpark stays off by default on 12 GB cards).

# Strata 0.2.4: DeepSeek V4.1-Flash in the Terminal

Strata now runs DeepSeek V4.1-Flash on a PC with one 12 GB graphics card and 46 to 64 GB of RAM. The engine keeps the experts it uses most in RAM and streams the rest from your SSD.

DeepSeek is in the Terminal (`strata launch`, `strata setup`) in this release. The desktop app is unchanged (it stays 0.2.3) and gets DeepSeek in a later update.

What you get

• DeepSeek V4.1-Flash in the model list of Setup, in three sizes from ISTA-DASLab:

| set | download | quality against the original model | |---|---|---| | IQ1_M (1.75 bits) | 239 GB | perplexity +21% (KL 0.217); code and agent text +8.9% and +10.2%; weaker on plain English prose. ISTA-DASLab's model card: keeps 98.7% of the base model's task average (AIME25, GPQA-Diamond, LiveCodeBench v6) | | IQ2_XXS (2.00 bits) | 257 GB | perplexity +15.5% (KL 0.170); code and agent text +8.6% and +5.3% | | IQ2_XS (2.25 bits) | 274 GB | perplexity +7.3% (KL 0.107); code and agent text +3.2% and +2.2% | | IQ4_NL (Engram table, not a model to pick) | 111 GB, already in all three downloads above | The 4-bit Engram lookup table the model reads from RAM or SSD; all three sets use this one file |

"Perplexity" is how surprised the model is by a fixed set of 4,995 test texts; lower is closer to the original. Pick IQ2_XS for coding and agent work when you have the disk. Setup shows all three sizes and warns if your PC is short of disk or RAM. It does not stop you.

• Setup downloads the files, builds the model folder and starts the engine. You set no flags.

Speed on real PCs

Output is the speed of the answer. Prompt is how fast Strata reads what you send it.

| PC | output | prompt | |---|---|---| | RTX 5070 12 GB, 64 GB RAM | about 5 tokens/s (code) | 231 tokens/s at 8K | | RTX 3060 12 GB, 46 GB RAM | about 8 to 10 tokens/s (code 9.9, agent work 7.8) | 149 tokens/s at 8K | | 1x Radeon AI PRO R9700 (AMD), IQ2_XS | about 11 tokens/s | not measured | | 4x Radeon AI PRO R9700 (AMD) | about 31 tokens/s (55 to 69 with DSpark) | about 505 tokens/s at 8K, about 818 at 32K |

These are the 2.00-bit set. The 2.25-bit set reads 13% more data per token, so expect it to be a little slower. Your drive matters: the 12 GB cards spend most of each token waiting on the SSD and on the CPU, and a slow NVMe drive lowers every number above.

How it works

• A RAM expert store that sizes itself. The model is a mixture of experts: each token uses a few of thousands of small blocks. Strata keeps the busiest ones in RAM, takes whatever RAM is free, and reads the rest from the SSD with direct reads. On the RTX 5070 PC with 64 GB this gave 4.3 to 4.9 tokens/s where memory-mapping the files gave 1.8 to 2.2.
• Hot-expert profiles ship with the engine, so the first prompts do not start