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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Pixels2Flutter
✓ verifiedFree

Turns UI screenshots into working Flutter code.

12K
Sherpa Coder
✓ verifiedFree

VS Code extension letting developers chat with their own custom OpenAI assistants without leaving the editor.

GitLoop
✓ verifiedFree trial

AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.

👁 11K/mo2.7K
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✓ verifiedFreemium

Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.

👁 775K/mo
OLMo 2
✓ verifiedFree

Ai2's family of fully open language models with weights, code, and training data released, built for transparent LLM research and building.

Pricing

No public pricing

No public pricing

No public pricing

Free trial available

No public pricing

No public pricing

Core features
  • in-editor chat with OpenAI assistants
  • workspace source-code context sharing
  • support for custom, user-defined assistants
  • secure management of the user's OpenAI account
  • Chat with your repositories
  • Natural-language codebase search
  • Fast code indexing
  • AI pull-request and commit review
  • Automated documentation generation
  • AI unit-test generation
  • Open-source AI code assistant
  • Customizable autocomplete
  • In-editor AI chat
  • Community-built coding agent
  • Fully open weights, code, and training data
  • Base, Think (reasoning), and Instruct variants
  • 7B and 32B model sizes
  • Open model flow across all training stages
  • Open-source training/eval tools (OlmoCore, OLMES)
  • OlmoTrace to trace outputs to training data
Use cases
  • getting coding help without switching out of VS Code
  • using a personalized OpenAI assistant tuned to a project
  • quick in-editor Q&A while writing code
  • Onboard new developers to a codebase
  • Resolve bugs faster
  • Generate docs and tests automatically
  • Review pull requests with AI
  • Get AI code completions while coding
  • Ask questions about code in the editor
  • Build on an open-source coding-agent foundation
  • Researching language-model training and behavior
  • Building and fine-tuning open models
  • Machine-unlearning and clinical-NLP research
  • Deploying transparent open LLMs
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