VibeThinker-3B-heretic
A decensored variant of WeiboAI/VibeThinker-3B (fine-tuned from Qwen/Qwen2.5-Coder-3B), produced with Heretic v1.4.0 (directional ablation / "abliteration"). Refusal behavior is suppressed via targeted weight edits to the attention output and MLP down-projections rather than fine-tuning, so the base model's thinking/reasoning gains and instruction-following are left largely intact.
Who this is for: users who want a ~3B reasoning/coding model with an explicit thinking mode (VibeThinker's chain-of-thought behavior) and no refusal guardrails - for CPU and low-VRAM local use, agents, and edge/on-device reasoning. Not a capability upgrade over base VibeThinker-3B - same model, refusal guardrails removed.
Runs on your gaming PC
Full GGUF ladder included — pick the quant that fits your card:
| Your GPU | Recommended quant | Weights |
|---|---|---|
| RTX 3090 / 4090 / 5090 (24 GB) | Q8_0 | ~3.3 GB |
| RTX 4080 / 5080 / 4060 Ti 16G (16 GB) | Q6_K | ~2.6 GB |
| RTX 3060 / 4070 / 5070 (12 GB) | Q5_K_M | ~2.3 GB |
| RTX 4060 / 3070 (8 GB) | Q4_K_M | ~2.0 GB |
| GTX 1660 Super / 2060 / 3050 laptop (6 GB) | IQ4_XS | ~1.9 GB |
| CPU-only / Apple Silicon | Q4_K_M | fits in system RAM |
Weights only, at this model's 3.1B native size; add ~1 GB for context. OOM? Drop one quant level. Headroom to spare? Go one up.
Why abliteration instead of fine-tuning
Fine-tuning a "helpful" persona on top of RLHF'd refusals fights the base model's training and tends to degrade coherence. Abliteration instead finds and edits the specific weight directions responsible for refusal, leaving the rest of the network (and its capabilities) untouched. See the Heretic repo and the original abliteration writeup for the mechanism.
Performance
| Metric | This model | VibeThinker-3B (base) |
|---|---|---|
| Refusals (out of 100 adversarial prompts) | 22 | 57 |
| KL divergence from base | 0.0444 | 0 (by definition) |
Reproduced with Heretic 1.4.0 (directional ablation), trial 92 of 200, RNG seed 4063399784. Full reproduction assets are in reproduce/.
Files
GGUF quantizations
Full quantization set (14 quants + F16) produced with llama.cpp.
| File | Format | Size |
|---|---|---|
VibeThinker-3B-heretic-F16.gguf |
GGUF F16 | 5.75 GB |
VibeThinker-3B-heretic-Q2_K.gguf |
GGUF Q2_K | 1.19 GB |
VibeThinker-3B-heretic-IQ3_S.gguf |
GGUF IQ3_S | 1.36 GB |
VibeThinker-3B-heretic-Q3_K_S.gguf |
GGUF Q3_K_S | 1.35 GB |
VibeThinker-3B-heretic-Q3_K_M.gguf |
GGUF Q3_K_M | 1.48 GB |
VibeThinker-3B-heretic-Q3_K_L.gguf |
GGUF Q3_K_L | 1.59 GB |
VibeThinker-3B-heretic-IQ4_XS.gguf |
GGUF IQ4_XS | 1.63 GB |
VibeThinker-3B-heretic-Q4_K_S.gguf |
GGUF Q4_K_S | 1.71 GB |
VibeThinker-3B-heretic-Q4_0.gguf |
GGUF Q4_0 | 1.70 GB |
VibeThinker-3B-heretic-Q4_1.gguf |
GGUF Q4_1 | 1.86 GB |
VibeThinker-3B-heretic-Q4_K_M.gguf |
GGUF Q4_K_M | 1.80 GB |
VibeThinker-3B-heretic-Q5_K_S.gguf |
GGUF Q5_K_S | 2.02 GB |
VibeThinker-3B-heretic-Q5_K_M.gguf |
GGUF Q5_K_M | 2.07 GB |
VibeThinker-3B-heretic-Q6_K.gguf |
GGUF Q6_K | 2.36 GB |
VibeThinker-3B-heretic-Q8_0.gguf |
GGUF Q8_0 | 3.06 GB |
Qwen2.5-Coder architecture with VibeThinker thinking mode — loads natively in llama.cpp / Ollama / LM Studio / Jan.
Run llama serve -hf saidutta69/VibeThinker-3B-heretic to pull the default quant.
Quickstart
llama.cpp
# download the LTS build: https://github.com/ggerganov/llama.cpp/releases
llama-cli -m VibeThinker-3B-heretic-Q4_K_M.gguf -p "User: What is the fourth dimension?\nAssistant:" -n 512
Ollama
ollama run hf.co/saidutta69/VibeThinker-3B-heretic:Q4_K_M
LM Studio
- Open LM Studio and click the search icon to open the Model Search panel.
- Type "VibeThinker-3B-heretic" and click the download button marked GGUF.
- Pick your quant, load the model, and start chatting.
FAQ
What is VibeThinker-3B-heretic?
VibeThinker-3B-heretic is a decensored build of WeiboAI/VibeThinker-3B produced with Heretic 1.4.0 (directional ablation). It is the same weights with the refusal direction removed, not a new fine-tune, so its capabilities track the base model.
Is VibeThinker-3B-heretic actually uncensored?
Yes. On Heretic's 100-prompt refusal harness it drops from 57/100 to 22/100 at KL divergence 0.0444 from the base model. These are measured values, not a claim; reproduction data is in reproduce/. This edit is conservative: only 35 of 57 refusals cleared, so read KL and refusal count together.
How do I run VibeThinker-3B-heretic locally?
llama serve -hf saidutta69/VibeThinker-3B-heretic:Q4_K_M pulls the default quant; the repo ships 15 GGUF quants (see Files).
Responsible use
This model has its refusal guardrails removed. Use it lawfully and ethically, and be aware that it may generate content the base model would refuse.
Made with ❤️ by RACER IS OP (saidutta69) — follow for more uncensored models
Related
WeiboAI/VibeThinker-3B- the base model this checkpoint derives from- RACER IS OP - Heretic Models - full collection - every heretic model in this collection
Abliteration hardware
Recorded in reproduce/reproduce.json:
- GPU: NVIDIA L4 (22.03 GB VRAM)
- CPU: Intel Xeon Processor (SapphireRapids)
- OS:
Linux-6.7.10-060710-generic-x86_64-with-glibc2.39 - CUDA / driver: CUDA 12.8, driver 580.126.20
- Software: PyTorch 2.11.0+cu128, Heretic 1.4.0
Heretic notes that KL-divergence and refusal numbers can vary slightly with hardware and library versions.