ansulev/OmniCoder-9B-heretic-ara-uncensored
VISIONConcurrency Cost:1Model Size:9BQuant:FP8Ctx Length:32kTool Calling:SupportedPublished:Apr 23, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Cold
ansulev/OmniCoder-9B-heretic-ara-uncensored is a 9-billion parameter coding agent model, based on Tesslate/OmniCoder-9B, which itself is fine-tuned on Qwen3.5-9B's hybrid architecture. This version has been decensored using the Heretic v1.2.0 Arbitrary-Rank Ablation (ARA) method. It features a 32,768 token context length and excels at agentic coding tasks, error recovery, and multi-step reasoning, having been trained on over 425,000 curated agentic coding trajectories.
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OmniCoder-9B-heretic-ara-uncensored: Decensored Coding Agent
This model is a decensored variant of the Tesslate/OmniCoder-9B coding agent, created by ansulev using the Heretic v1.2.0 Arbitrary-Rank Ablation (ARA) method. It retains the core capabilities of the original OmniCoder-9B while aiming to reduce refusals.
Key Capabilities & Features
- Decensored Behavior: Modified using Heretic ARA to reduce content refusals, achieving 7/100 refusals compared to 0/100 in the original model, with a KL divergence of 0.0452.
- Base Architecture: Built upon Qwen3.5-9B, featuring a hybrid architecture with Gated Delta Networks interleaved with standard attention for efficient long-context processing.
- Agentic Coding Expertise: Fine-tuned on over 425,000 curated agentic coding trajectories from models like Claude Opus 4.6, GPT-5.4, and Gemini 3.1 Pro.
- Advanced Error Handling: Demonstrates strong agentic behavior, including error recovery (read-before-write), responsiveness to LSP diagnostics, and generation of minimal edit diffs.
- Extended Context Window: Supports a 262,144 token native context window, extensible to over 1M tokens.
- Reasoning Chains: Incorporates a
<think>...</think>mode for complex problem decomposition.
Performance Highlights
- GPQA Diamond (pass@1): Achieves 83.8%, a 2.1-point improvement over the Qwen3.5-9B base model.
- AIME 2025 (pass@5): Scores 90%.
- Terminal-Bench 2.0: Reaches 23.6%, an 61% improvement over the Qwen3.5-9B base model.
Ideal Use Cases
- Agentic Development: Suited for tasks requiring autonomous coding, tool use, and terminal operations.
- Complex Code Generation: Excels in scenarios demanding multi-step reasoning and error recovery within coding workflows.
- Uncensored Code Assistance: For users requiring a coding assistant with reduced content restrictions.