May 12, 2025

Introducing Spec-Coder

Spec-Coder is SVECTOR’s cutting-edge, open-source 4B parameter AI model built for real-world programming tasks.

Model Specifications

•Architecture: Transformer (LLaMA-based)
•Parameters: 4 Billion
•Context Window: 8,192 tokens
•Training Tokens: ~4.3 Trillion
•Tasks: Code generation, infilling, debugging, FIM
•Hardware: Trained on 4090 GPUs for ~140 days

Architecture Overview

Spec-Coder is built on a transformer-based architecture optimized for coding tasks. It uses a LLaMA-style design with efficient attention mechanisms and advanced infilling capabilities.

It is trained using a standard language modeling objective across diverse codebases such as The Stack v1/v2, CommitPack, and OpenCodeReasoning.

The model supports supervised fine-tuning and reinforcement learning to enhance task-specific performance, enabling features like function completion, bug fixing, and natural language to code conversion.

It performs strongly across RepoBench, HumanEval Infilling, and SAFIM benchmarks, making it ideal for integration into developer tools or research.

Spec-Coder is compatible with llama.cpp and Ollama for flexible deployment across platforms.