enigmacoder/EnigmaCoder-2B

VISIONPricing:Input $0.4 / Cached $0.08 / Output $0.8Concurrent Unit Cost:1Model Size:5.1BQuant:BF16Context Size:32kTool Calling:SupportedPublished:Oct 12, 2026License:gemmaArchitecture:Transformer0.0K Featherless Exclusive Cold

EnigmaCoder 2B is a 2 billion parameter language model developed by EnigmaCoder, fine-tuned from Google's Gemma-4-E2B-IT base model. Specialized for software engineering tasks, it excels at code generation, explanation, debugging assistance, and software reasoning. With a 128K token context window, it is designed to support the full engineering lifecycle within the EnigmaCoder platform, offering capabilities for planning, coding, running, debugging, and verifying software.

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EnigmaCoder 2B: Foundation for AI-Powered Software Engineering

EnigmaCoder 2B is the inaugural model in the EnigmaCoder AI engineering ecosystem, developed by EnigmaCoder to power intelligent software engineering workflows. Built upon Google Gemma-4-E2B-IT, this 2 billion parameter model is specifically fine-tuned for deep understanding and interaction within the software development lifecycle.

Key Capabilities

  • Code Generation: Writes correct and idiomatic Python and general-purpose code from natural language.
  • Code Understanding: Explains code functionality, purpose, and integration within larger systems.
  • Debugging Assistance: Identifies errors, suggests fixes, and reasons about failure modes.
  • Software Reasoning: Aids in architectural decisions, design patterns, and engineering tradeoffs.
  • Technical Q&A: Answers developer questions across various technical domains like databases, APIs, and algorithms.

Good for

  • Developers seeking a locally-runnable coding assistant for tasks like writing and completing functions.
  • Teams needing to explain existing codebases or debug logic errors efficiently.
  • Answering technical questions about algorithms, data structures, and system design.
  • Assisting with SQL queries, API design, and backend development.
  • Integration into IDEs for in-editor code generation, contextual debugging, and agentic workflows, as planned for the EnigmaCoder IDE.

EnigmaCoder 2B features a 128K token context window and was fine-tuned using QLoRA, with merged full Float16 weights for inference. This model represents EnigmaCoder's commitment to building and controlling its own specialized AI stack for software engineering, ensuring deep integration and continuous specialization.

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