😈 Uncensored Gemma 4 E4B (i1-Q4_K_M Abliterix) for Ollama. ⚡ Ultralight Reasoning & Coding Agent, 🛠️ Native Tool Calling, 🧠 Deep Thinking Rust 1.98.0 , Linux/Windows CLI, Claude Code, OpenCode & Edge AI. 🚀 #16HEX Matrix.

Details

Updated 4 days ago

4 days ago

4e9df2b05140 · 5.3GB ·

model

archgemma4

parameters7.46B

quantizationQ4_K_M

5.3GB

system

<|think|> Jesteś Głównym Architektem Wschodniej Szkoły IT (16 HEX, 2^4) – Zwarty Sensor Sensor

942B

params

{ "min_p": 0.05, "num_ctx": 32768, "num_predict": 8192, "repeat_penalty": 1.1, "

142B

template

13B

😈 Gemma 4 E4B • Nightshift Heretic Uncensored (i1-Q4_K_M)

Ultralight Edge Reasoning & Coding Agent Tool Calling • Thinking • Rust • Linux / Windows CLI • Local AI • GGUF • #16HEX Matrix

⚡ Architecture & Technical Specification

Parameter	Value
Base Architecture	Google DeepMind Gemma 4 E4B
Architecture Profile	Dense + PLE
Quantization	`i1-Q4_K_M`
Quantization Method	Importance-matrix optimized (`imatrix`)
Model Size	~5.3 GB
Primary Workloads	Reasoning • Coding • Tools • CLI Agents
Modalities	Text • Tools • Logical Reasoning
Context Window	32,768 tokens
Maximum Generation	8,192 tokens
Deployment Target	Edge AI • Local AI • CPU / GPU / iGPU

🧬 Model Positioning

Gemma 4 E4B Nightshift Heretic Uncensored is a compact local AI model designed for reasoning, software engineering, tool calling and terminal-oriented workflows.

The i1-Q4_K_M build is focused on efficient local inference while maintaining a practical balance between model size, memory requirements, inference speed and output quality.

The ~5.3 GB model footprint makes this variant particularly suitable for constrained local environments, including laptops, iGPU systems and smaller GPU configurations.

🧠 Reasoning Engine

The model is configured for structured reasoning workflows using its supported thinking channel:

<|think|>

This enables an explicit reasoning stage for tasks requiring:

🧩 Problem decomposition
🔍 Logical analysis
📐 Algorithmic reasoning
🧠 Constraint evaluation
🛠️ Technical troubleshooting
💻 Code analysis
📚 Structured document processing

Note: a low-temperature configuration can make generation more consistent, but it does not guarantee factual correctness or eliminate hallucinations.

🛠️ Native Tool Calling

A primary positioning of this build is tool-oriented local AI.

Suitable workflows include:

🔧 Function Calling
📦 Structured JSON
🖥️ CLI automation
🤖 Coding agents
🔄 Tool-driven workflows
🌐 External API integration
📁 File and project operations
⚙️ Local development automation

The exact tool interface depends on the Ollama runtime and the agent/frontend integrating the model.

💻 Coding & Systems Engineering

The model is positioned for compact, local software-engineering workflows, including:

🦀 Rust

Rust code generation
code review
refactoring
debugging
ownership / borrowing analysis
lifetime reasoning
low-level systems programming

🐧 Linux

Bash / shell workflows
CLI automation
system configuration
process and filesystem operations
development environments
local AI tooling

🪟 Windows

PowerShell
Windows CLI
automation
development tooling
local inference workflows

⚙️ Systems-Level Work

memory-aware programming
binary and bitwise operations
data structures
algorithm optimization
low-level debugging
performance-oriented code analysis

The model’s suitability for a programming language comes from its learned capabilities and prompting/tool environment; it should not be interpreted as a guarantee of compiler-level correctness.

🤖 AI Coding Agents & Developer Workflows

This model is intended for integration into local coding-agent environments such as:

Claude Code
OpenCode
OpenClaw
Hermes Agent
Ollama-based local agents
Terminal AI workflows

Example launch pattern:

ollama launch claude --model jikepjikep_16HEX/gemma-4-e4b-nightshift-heretic-uncensored-q4

ollama launch opencode --model jikepjikep_16HEX/gemma-4-e4b-nightshift-heretic-uncensored-q4

Availability and exact command syntax depend on the installed Ollama version and the respective integration.

📐 #16HEX Sampling Matrix

Recommended configuration:

temperature    : 0.20
top_k          : 16
min_p          : 0.05
repeat_penalty : 1.10
num_ctx        : 32768
num_predict    : 8192

🔬 Parameter Interpretation

Parameter	Value	Purpose
`temperature`	0.20	Conservative token sampling
`top_k`	16	Restricts candidate token set
`min_p`	0.05	Removes low-probability candidates
`repeat_penalty`	1.10	Reduces repetitive generation
`num_ctx`	32768	32K-token working context
`num_predict`	8192	Maximum generated output

🎯 16HEX Objective

The configuration is designed to favor:

Precision → Stability → Information Density → Controlled Generation

top_k=16 also provides the direct numerical connection to the 16HEX deployment philosophy:

16 = 2⁴

The branding is therefore reflected directly in the sampling configuration without claiming that hexadecimal representation itself changes model computation.

🔓 Nightshift Heretic / Uncensored Variant

Nightshift Heretic Uncensored identifies this as an experimentally modified model variant intended for a less refusal-oriented interaction profile.

The designation should be understood as a model-variant characteristic, not as a guarantee of:

zero refusals,
unrestricted behavior,
perfect compliance,
elimination of all safety behavior,
or guaranteed execution of every requested operation.

📦 Quantization & Edge Deployment

i1-Q4_K_M is the central deployment format of this build.

The target is an efficient balance between:

Model Size
     ↓
Memory Usage
     ↓
Inference Efficiency
     ↓
Local Deployment
     ↓
Practical Coding / Agent Workloads

The approximately 5.3 GB model size makes this variant particularly attractive for:

💻 laptops
🖥️ desktop PCs
🎮 smaller GPUs
🧠 iGPU systems
🍎 Apple Silicon systems
🐧 Linux workstations
🪟 Windows systems
⚡ Edge AI deployments

Actual RAM / VRAM requirements depend on context length, runtime, KV-cache configuration and CPU/GPU offloading.

🔐 Local AI & Privacy

When executed locally through Ollama, inference can remain on the user’s machine instead of requiring a cloud model endpoint.

This makes the model suitable for:

🔒 private development
🏠 offline AI workflows
💻 local coding
📁 local project analysis
🛠️ terminal automation
🧪 open-source AI experimentation

Network privacy ultimately depends on the complete runtime stack, frontend, plugins, tools and external APIs connected to the model.

🚀 Recommended Use Cases

Gemma 4 E4B Nightshift Heretic Uncensored is optimized for compact local workflows involving:

AI Coding • Reasoning • Tool Calling • CLI Agents • Rust • Linux • Windows • PowerShell • JSON • Automation • Local AI • Edge AI • Developer Tools • Open-Source AI

🧬 Model Identity

Model        : Gemma 4 E4B
Variant      : Nightshift Heretic Uncensored
Quantization : i1-Q4_K_M
Size         : ~5.3 GB
Context      : 32,768 tokens
Generation   : 8,192 tokens
Thinking     : ✓
Tool Calling : ✓
Coding       : ✓
CLI Workflows: ✓
Edge AI      : ✓
Vision       : —
Format       : GGUF / Ollama
Brand        : #16HEX Matrix

🧠 #16HEX Matrix Philosophy

#16HEX is the deployment philosophy behind this model:

High information density. Controlled inference. Local execution.

0–9  → measurable parameters, configuration and system constraints
A–F  → optimization, reasoning, architecture and engineering synergy

The goal is not maximum token generation.

The goal is:

Less noise → more signal → stronger structure → useful output.

Gemma 4 E4B • Gemma 4 E4B Uncensored • Gemma 4 E4B Heretic • Gemma 4 E4B Ollama • Gemma 4 E4B Q4_K_M • i1-Q4_K_M • Abliterix • Uncensored AI • Heretic AI • Local AI • Edge AI • Ollama • GGUF • AI Coding Agent • Coding AI • Reasoning AI • Thinking Model • Tool Calling • Function Calling • CLI AI • Terminal AI • Rust AI • Rust Coding • Linux AI • Windows AI • PowerShell AI • Claude Code • OpenCode • OpenClaw • Hermes Agent • JSON Tool Calling • Local Coding Assistant • Offline AI • Open Source AI • Developer AI • Systems Programming • 16HEX Matrix

gemma4 gemma-4 e4b 27b uncensored heretic abliterix i1-q4_k_m q4_k_m imatrix ollama gguf local-ai edge-ai reasoning thinking tool-calling function-calling coding coding-agent rust linux windows powershell cli terminal-ai claude-code opencode openclaw hermes-agent json automation developer-ai offline-ai open-source-ai 16hex

🛡️ Operator Principle

This model is an experimental local AI system for reasoning, software engineering, tool calling and AI-agent research.

Generated code and technical conclusions should be reviewed and tested by the human operator before use in production or safety-critical environments.

🚀 Final Positioning

Gemma 4 E4B Nightshift Heretic Uncensored is a compact, local-first reasoning and coding agent built for users who want practical Tool Calling, Thinking, Rust, Linux, Windows CLI, AI coding agents and Edge AI in an efficient i1-Q4_K_M package.

Small footprint. Strong reasoning. Native tools. Local execution.

😈 Nightshift Heretic

⚡ #16HEX Matrix

🛠️ Local AI Engineering

🚀 Edge AI / Coding Agents

😎 16 HEX MATRIX 😈

If the Nightshift Heretic 😈 models are useful to you and you would like to support 16 HEX Matrix / Eastern IT School, you can buy me a coffee with Monero (XMR).

🟣 Monero (XMR)

Network: Mainnet

XMR Address:

44DffaT4GKhWDSRxP1FCPfYJbvUXqciDbgMYxnTnNif9Pm5qP4haCmHh8ePEXxQCQRLKNhhnqW8FgDV9UNah7z5CGcBCBQd

Copy the address above and paste it into your Monero wallet.

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⚡ SIMPLE FLOW

Get XMR → Copy the address → Send XMR → Support local AI development.

Your support helps fund the development, testing, hardware and maintenance of the 16 HEX Matrix / Eastern IT School Nightshift Heretic 😈 local AI model series.

Thank you for supporting independent local AI development. 🧠⚡

#MedicalAI #MedicalVision #Radiology #MedicalImaging #EmergencyTriage #ClinicalAI #Qwen35B #Qwen3 #MoE #VisionAI #Ollama #GGUF #LocalAI #MultimodalAI #16HEX