Supermix_29

Supermix_29 is the working monorepo for the current Supermix / ChampionNet / Omni Collective line.

This repository combines:

• local-first chat and multimodal runtime code
• experimental training and continuation pipelines
• desktop EXE and installer packaging
• benchmark tooling and graph generation
• published-model export helpers
• bundled datasets and generated research artifacts

It is intentionally a mixed workspace, not a minimal source-only model repo.

Current status

As of March 29, 2026:

• the latest finished omni checkpoint in this repo is omni_collective_v4
• the latest packaged desktop release is studio-desktop-20260329-omni-v4-allmodels
• the installer bundle currently includes 23 zipped model artifacts from the local model-pack directory used by the desktop build
• a v5 continuation path exists in source/ and is currently an in-progress local experiment, not a finished released model

What is in this repo

• source/
  • active development workspace
  • training scripts, model definitions, dataset builders, benchmark runners, desktop packaging helpers
• runtime_python/
  • packaged local runtime path
  • simpler run path than the full source/ workspace
• datasets/
  • conversation, coding, reasoning, science, and related local training inputs
• output/
  • generated artifacts, benchmark graphs, summaries, logs, Hugging Face upload folders
• installer/
  • Inno Setup definitions for the desktop app
• dist/
  • built EXEs and installer outputs
• web_static/
  • lightweight browser-only metadata bundle

Main capabilities

• multimodel desktop app with model selector, Auto routing, collective mode, and agent mode
• local chat, image-prompt, math, science-image, and omni-fusion model families
• native-image experimental checkpoints
• training pipelines for frontier, omni, lite, and specialist model lines
• benchmark sweeps across common text benchmarks
• export and publishing workflows for GitHub releases and Hugging Face model/dataset repos

Quick start

Run the packaged runtime

python runtime_python/chat_web_app.py

Windows launchers:

runtime_python\launch_chat_web_supermix.bat
runtime_python\launch_chat_terminal_supermix.bat

Run the active source app

python source/chat_web_app.py

Run the desktop multimodel app from source

python source/supermix_multimodel_desktop_app.py

Run the browser-only static bundle

Open:

web_static/index.html

Current desktop release

Latest release published from this repo:

• Release page:
  • https://github.com/kai9987kai/Supermix_29/releases/tag/studio-desktop-20260329-omni-v4-allmodels
• Installer:
  • https://github.com/kai9987kai/Supermix_29/releases/download/studio-desktop-20260329-omni-v4-allmodels/SupermixStudioDesktopSetup.exe
• EXE:
  • https://github.com/kai9987kai/Supermix_29/releases/download/studio-desktop-20260329-omni-v4-allmodels/SupermixStudioDesktop.exe

Local build outputs:

• dist/SupermixStudioDesktop/SupermixStudioDesktop.exe
• dist/installer/SupermixStudioDesktopSetup.exe
• dist/installer/SupermixStudioDesktopReleaseSHA256.txt

Model families in the workspace

The repo contains code and artifacts for several model lines:

• Qwen adapter line
  • v28
  • v30
• Champion / frontier line
  • v31
  • v32
  • v33
  • v34
  • v35
  • v39
• native-image line
  • v36
  • v37
  • v38
• omni-collective line
  • v1
  • v2
  • v3
  • v4
• specialist lines
  • math_equation_micro_v1
  • science_image_recognition_micro_v1

Latest finished omni model

The latest finished omni checkpoint in this repo is omni_collective_v4.

Key details from output/supermix_omni_collective_v4_frontier_20260329/omni_collective_v4_frontier_summary.json:

• parameter count: 19,032,281
• stage-1 rows: 8,589
• stage-2 rows: 9,447
• final stage-2 weighted validation score: 0.5176
• final stage-2 validation:
  • intent: 0.8195
  • response: 0.1402
  • vision: 0.9020
  • domain: 0.7765

Local packaged artifact:

• output/supermix_omni_collective_v4_frontier_20260329.zip

Hugging Face models

Public model repos already published from this workspace:

• Kai9987kai/supermix-v33-frontier
• Kai9987kai/supermix-omni-collective-v1
• Kai9987kai/supermix-v38-native-image-xlite-fp16
• Kai9987kai/supermix-v39-frontier-reasoning-plus
• Kai9987kai/supermix-omni-collective-v2-frontier
• Kai9987kai/supermix-math-equation-micro-v1
• Kai9987kai/supermix-omni-collective-v4-frontier

Hugging Face datasets

Public dataset repos already published from this workspace:

• Kai9987kai/supermix-conversation-datasets
• Kai9987kai/supermix-science-vision-dataset

Benchmarks

The current local multibench comparison bundle is:

• output/pdf/benchmark_local_all_models_multibench_20260329.pdf
• output/benchmark_local_all_models_multibench_20260329.json
• output/benchmark_local_all_models_multibench_20260329.csv

The current graph covers 20 benchmarked local model entries and keeps specialist-only models labeled separately when the common text suite is not the right evaluation fit.

Representative current common-benchmark leaders from the local graph JSON:

• v33_final: 0.1867
• v39_final: 0.1800
• omni_collective_v1: 0.1633
• v34_final: 0.1600
• v36_native: 0.1533
• v35_final: 0.1533
• omni_collective_v4: 0.0900

Training entry points

Representative training and continuation scripts:

• source/train_omni_collective_v2.py
• source/train_omni_collective_v3.py
• source/train_omni_collective_v4.py
• source/train_omni_collective_v5.py
• source/train_math_equation_model.py
• source/train_image_recognition_model.py
• source/build_reasoning_benchmix_v39.py
• source/benchmark_all_models_common.py

If you want the active experimental path, start in source/.

Desktop build entry points

Primary desktop build helpers:

• source/build_supermix_studio_desktop_exe.ps1
• source/build_supermix_studio_desktop_installer.ps1
• SupermixStudioDesktop.spec
• installer/SupermixStudioDesktop.iss

The current bundled-model manifest is:

• output/supermix_studio_bundled_models_manifest.json

Research and experiment notes

This repo is a living experiment workspace. It contains finished artifacts, release-ready packaging, and in-progress work at the same time.

That means you will see mixed generations such as:

• v28
• v30
• v33
• v34
• v35
• v36
• v37
• v38
• v39
• omni_collective_v1 through omni_collective_v5

That is expected.

Recommended starting points

If you want to:

• run a packaged local system
  • use runtime_python/
• work on the active multimodel app
  • use source/supermix_multimodel_web_app.py
  • use source/supermix_multimodel_desktop_app.py
• work on training
  • start in source/
• inspect the current benchmark outputs
  • use output/benchmark_local_all_models_multibench_20260329.*
• build a Windows installer
  • use the PowerShell build scripts in source/ plus installer/

Platform notes

• Windows is the main desktop packaging target
• the repo includes PyInstaller specs, PowerShell build scripts, and Inno Setup definitions
• some training flows were designed around cloud GPU workflows, but the repo also supports local CPU experimentation

Security note

Do not commit or publish browser-session dumps, cookies, temporary automation state, or live access tokens.

Relevant policy docs:

• SECURITY.md
• CONTRIBUTING.md
• CODE_OF_CONDUCT.md

License

See LICENSE.