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CodeGPT
✓ verifiedFreemium
IDE coding assistant for VS Code and JetBrains that uses your own API keys across 15+ model providers, with agentic mode and autocomplete.
👁 262K/mo
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GitFluence
✓ verifiedFree
Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.
Pricing
Free: $0/mo (BYOK, 30 free interactions)
AutoComplete Add-on / BYOK Pro: $8/mo per seat ($6.67 annual)
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
Core features
- ✦BYOK access to 15+ model providers
- ✦Agentic planning-then-build mode
- ✦AI autocomplete
- ✦MCP connections to external systems
- ✦Custom rules and live context tracking
- ✦Local models via Ollama/LM Studio
- ✦VS Code and JetBrains plugins
- ✦Enhanced Context Engineering for deep codebase analysis and adaptive memory
- ✦Intelligent Agents for autonomous planning, coding, and testing
- ✦Spec-Driven Development for clarifying requirements and automating execution
- ✦Intelligent Codebase Search and Advanced Repository Insight
- ✦Context-aware code completions and next-edit suggestions
- ✦Support for leading AI models (Claude, GPT, Gemini)
- ✦Natural-language to Git command suggestions
- ✦AI-driven command matching
- ✦Copy-ready command output
- ✦Git guides and reference
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
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Use cases
- →Code generation, refactoring and debugging
- →Control AI spend with your own keys
- →Switch between frontier models per task
- →Keep code private and data-sovereign
- →Delegating complex software development tasks to AI agents for autonomous completion.
- →Performing multi-file code edits and refactoring through natural language chat.
- →Gaining deep architectural understanding of a codebase to resolve issues with precision.
- →Generating unit tests, code explanations, and uncovering codebase architecture.
- →Systematically tackling software development tasks from planning to testing.
- →Find the correct Git command quickly
- →Learn Git syntax by describing a goal
- →Avoid memorizing Git flags
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
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