truthcoder/TC-Mini

TC Mini — a private AI that runs entirely on your phone or PC

Open-source, on-device chat AI. No account, no server, no telemetry — your chats never leave your device. Runs in the browser with WebGPU (phones, laptops, desktops) or on your PC with Ollama / LM Studio / llama.cpp. Three sizes: 4B (desktop), 1.7B (balanced / phones), 0.6B (any phone, 336 MB).

▶ Open it on your phone or computer: https://truthprotectors.github.io/TC-Mini/app/ 💻 Code (GitHub): https://github.com/truthprotectors/TC-Mini

What's inside

Build	Size (browser)	For	Model
Desktop · 4B	2.3 GB	laptops / desktops with a GPU or Apple Silicon	Qwen3-4B abliterated
Balanced · 1.7B	939 MB	newer phones, small laptops	Qwen3-1.7B abliterated
Mobile · 0.6B	336 MB	any WebGPU phone	Qwen3-0.6B abliterated

Honest lineage: these are the open Qwen3 models with refusal directions removed ("abliterated", by mlabonne), quantized by us to 4-bit for WebGPU (MLC q4f16_1 / q4f32_1; the 4B uses AWQ-style channel scales folded into the norms, which cut 4-bit quality loss from KL 0.120 to 0.090 vs f16). They are not yet our own distilled model — each signed manifest says so. Measured: 0/8 refusals on our 8-prompt probe for every size; ~34 tok/s for the 4B in Chrome on an RTX 5070; the 0.6B is good for simple code and explanations, weak at arithmetic.

Built to be trusted

• Signed releases. Every release has an Ed25519-signed MANIFEST.json listing the SHA-256 of every file. The app pins the public key (02c6bedb…77ae), verifies the signature in the browser, then hashes every downloaded shard before using it. A tampered mirror is refused before a single byte loads. Rollbacks to older releases are refused too.
• Your device decides the size. A capability check (GPU, shader-f16, memory, iOS/Android) picks a build that won't freeze your device. Phones never get the 4B, and integrated GPUs get a small context and prefill chunks, because a 4B model can hard-freeze a laptop's display driver.
• Checked on your device. Before the first chat, the exact build runs an 8-prompt response check on your hardware.
• No telemetry. The only network requests are the signed release files. Everything else runs locally, and it works offline after the first download.

Use it on a PC (Ollama / LM Studio / llama.cpp)

Size	GGUF repo	Q4_K_M	Best for
4B	truthcoder/TC-Mini-4B-GGUF	2.5 GB	desktops / laptops with a GPU or Apple Silicon
1.7B	truthcoder/TC-Mini-1.7B-GGUF	1.1 GB	small laptops, mini-PCs
0.6B	truthcoder/TC-Mini-0.6B-GGUF	0.4 GB	any computer

# Ollama
ollama run hf.co/truthcoder/TC-Mini-4B-GGUF:Q4_K_M
# llama.cpp
llama-cli -hf truthcoder/TC-Mini-4B-GGUF:Q4_K_M

LM Studio: search TC-Mini. Q8_0 (near-lossless) and F16 files are in each repo too. Add /no_think to a message to skip the thinking step.

Verify a release yourself (any machine with OpenSSH ≥ 8.2)

git clone https://huggingface.co/truthcoder/TC-Mini && cd TC-Mini/release/r1-2026-09-20-full
A=qwen3-4b-abl-q4f16_1
ssh-keygen -Y verify -f allowed_signers -I truthcoder-mini-release -n truthcoder-mini -s $A/MANIFEST.json.sig < $A/MANIFEST.json
python3 -c "import json;m=json.load(open('$A/MANIFEST.json'));[print(v['sha256'],' $A/'+k) for k,v in m['files'].items()]" | sha256sum -c

Self-host

The app is static files — no build step. Serve app/, vendor/, probe.js, fixtures.json and probe_constants.json from any web server. To serve the weights yourself, put the release/ folder from Hugging Face next to app/ and set window.TC_WEIGHTS="" in app/boot.js. Any mirror is safe because of the signatures.

License

App code: Apache-2.0. Model weights: Apache-2.0, inherited from Qwen3 via mlabonne/Qwen3-4B-abliterated (and the 1.7B / 0.6B siblings). Runtime: WebLLM / MLC-LLM (Apache-2.0).

Abliterated models answer requests that stock models refuse. You are responsible for how you use it.