Java vs. Nim vs. PureScript vs. StarCoder Comparison Chart

Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Nim generates native dependency-free executables, not dependent on a virtual machine, which are small and allow easy redistribution. Nim's memory management is deterministic and customizable with destructors and move semantics, inspired by C++ and Rust. It is well-suited for embedded, hard-realtime systems. Modern concepts like zero-overhead iterators and compile-time evaluation of user-defined functions, in combination with the preference of value-based datatypes allocated on the stack, lead to extremely performant code. Support for various backends: it compiles to C, C++ or JavaScript so that Nim can be used for all backend and frontend needs.

StarCoder and StarCoderBase are Large Language Models for Code (Code LLMs) trained on permissively licensed data from GitHub, including from 80+ programming languages, Git commits, GitHub issues, and Jupyter notebooks. Similar to LLaMA, we trained a ~15B parameter model for 1 trillion tokens. We fine-tuned StarCoderBase model for 35B Python tokens, resulting in a new model that we call StarCoder. We found that StarCoderBase outperforms existing open Code LLMs on popular programming benchmarks and matches or surpasses closed models such as code-cushman-001 from OpenAI (the original Codex model that powered early versions of GitHub Copilot). With a context length of over 8,000 tokens, the StarCoder models can process more input than any other open LLM, enabling a wide range of interesting applications. For example, by prompting the StarCoder models with a series of dialogues, we enabled them to act as a technical assistant.