Cerebras vs. CerebrasCoder vs. StarCoder vs. Wing Python IDE Comparison Chart

We’ve built the fastest AI accelerator, based on the largest processor in the industry, and made it easy to use. With Cerebras, blazing fast training, ultra low latency inference, and record-breaking time-to-solution enable you to achieve your most ambitious AI goals. How ambitious? We make it not just possible, but easy to continuously train language models with billions or even trillions of parameters – with near-perfect scaling from a single CS-2 system to massive Cerebras Wafer-Scale Clusters such as Andromeda, one of the largest AI supercomputers ever built.

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.