| 0 |
| 1 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $10/mo |
| Capabilities | 12 decomposed | 13 decomposed |
| Times Matched | 0 | 0 |
Launches an Aider CLI session directly from VSCode's command palette via the 'Aider: Open' command, establishing a bidirectional bridge between the editor and Aider's AI-driven code modification engine. The extension spawns Aider as a subprocess, passing the current workspace context and maintaining file synchronization between VSCode's editor state and Aider's internal file tracking. This integration eliminates context-switching by embedding Aider's full capabilities within the editor's native command interface.
Unique: Directly embeds Aider CLI as a subprocess within VSCode's extension host rather than wrapping Aider's API or reimplementing its logic, preserving all of Aider's native capabilities (multi-file editing, git integration, model selection) while adding VSCode-native UI affordances like command palette, context menus, and status bar integration.
vs alternatives: Provides tighter VSCode integration than using Aider standalone in a terminal, and avoids the latency/context-loss of cloud-based AI coding assistants by delegating to Aider's local-first architecture.
Enables in-place code refactoring by right-clicking on a code selection in the editor, which passes the selected text and surrounding file context to Aider's AI engine with a refactoring intent. The extension captures the selection range, file path, and project context, then invokes Aider with refactoring-specific prompts. Modified code is returned and applied back to the editor with change tracking, allowing developers to review and accept/reject modifications before committing.
Unique: Integrates refactoring as a context menu action on code selections rather than requiring manual prompt engineering, automatically inferring refactoring intent from the selection and applying changes directly to the editor with VSCode's change tracking.
vs alternatives: Faster than copying code to Aider CLI or using generic AI chat interfaces, because it preserves selection context and applies changes in-place; more discoverable than terminal-based Aider because it uses VSCode's native right-click affordance.
Allows developers to assign custom keyboard shortcuts to Aider commands (e.g., 'Aider: Open', 'Aider: Voice Command') via VSCode's keybindings configuration interface. Developers can override default keybinds or create new ones for frequently-used commands, enabling rapid access without command palette invocation. Keybindings are configured through VSCode's standard keyboard shortcuts UI (File > Preferences > Keyboard Shortcuts) and stored in the user's keybindings.json file.
Unique: Integrates with VSCode's native keybindings system, allowing developers to assign custom shortcuts to Aider commands using the same interface they use for other VSCode extensions, rather than requiring extension-specific configuration.
vs alternatives: More flexible than fixed keybindings because developers can customize shortcuts to match their workflow; integrates seamlessly with VSCode's keybinding ecosystem.
Provides extension settings for configuring OpenAI and Anthropic API keys, which are stored in VSCode's settings storage and used to authenticate requests to AI model APIs. Developers configure API keys through VSCode's settings UI (File > Preferences > Settings > Extensions > Aider), and the extension passes them to Aider CLI via environment variables or command-line arguments. The extension does not implement its own API calls; instead, it delegates to Aider CLI, which handles authentication.
Unique: Integrates API key configuration into VSCode's settings UI rather than requiring manual environment variable setup or CLI configuration, making credential management more discoverable for VSCode users.
vs alternatives: More user-friendly than manually setting environment variables for Aider CLI; integrates with VSCode's settings system for consistency with other extensions.
Integrates with VSCode's diagnostics system to enable right-click error fixing on code errors, linting warnings, or type errors. When a developer right-clicks on a diagnostic (red squiggle), the extension captures the error message, error location, surrounding code context, and file path, then sends this to Aider with a fix-intent prompt. Aider's AI engine analyzes the error and suggests or applies fixes, which are returned to the editor for review and application.
Unique: Hooks into VSCode's native diagnostics system (language servers, linters) to capture error context automatically, rather than requiring manual error description; passes structured error metadata (location, message, code context) to Aider for more accurate fixes.
vs alternatives: More contextual than generic 'fix this error' prompts to ChatGPT because it includes precise error location and surrounding code; faster than manually copying error messages to Aider CLI because it's triggered via right-click on the error itself.
Provides right-click context menu integration on files and folders in VSCode's file explorer, enabling developers to add or ignore files from Aider's context without manually managing Aider's file list. The extension translates file explorer selections into Aider CLI commands (e.g., 'aider add <file>' or 'aider ignore <file>'), updating Aider's internal file tracking and ensuring subsequent AI operations only consider the selected files. This allows developers to scope AI operations to specific parts of the codebase.
Unique: Translates VSCode's file explorer UI directly into Aider CLI commands, allowing developers to manage Aider's file context through familiar file explorer interactions rather than learning Aider's CLI syntax or manually editing configuration files.
vs alternatives: More discoverable and faster than using Aider's CLI directly for file management; integrates file scoping into the editor's native UI rather than requiring context-switching to terminal.
Provides a 'Aider: Select Model' command in the command palette that displays available AI models (GPT-4, Claude, and custom models) and allows developers to switch between them without restarting Aider or the extension. The extension maintains model selection state and passes the selected model to Aider CLI invocations via command-line arguments. Developers can also set a default model in extension settings, which is used for all subsequent Aider sessions unless explicitly overridden.
Unique: Exposes model selection as a first-class command in VSCode's command palette rather than burying it in settings, enabling rapid model switching during development; maintains model state across Aider invocations within a session.
vs alternatives: Faster than reconfiguring Aider CLI arguments manually or editing config files; more discoverable than Aider's native model selection because it's integrated into VSCode's command palette.
Enables voice-based prompting for Aider operations via a 'Aider: Voice Command' command, triggered by a customizable keybind (e.g., Ctrl+Shift+V). When activated, the extension captures audio input from the system microphone, converts it to text using OpenAI's speech-to-text API, and sends the transcribed text as a prompt to Aider. This allows developers to issue AI-assisted code modifications using natural speech rather than typing, useful for hands-free or rapid-fire prompting.
Unique: Integrates OpenAI's speech-to-text API directly into the extension to enable voice-based prompting, rather than requiring developers to use external voice recording tools or VSCode's native voice input; keybind-triggered activation allows rapid voice command invocation.
vs alternatives: Enables hands-free coding workflows that generic AI chat interfaces don't support; faster than typing long prompts, especially for developers with accessibility needs.
+4 more capabilities
Generates single-line and multi-line code suggestions in real-time as developers type, using semantic indexing of the entire codebase to retrieve relevant type definitions, function signatures, and contextual patterns. The system maintains a 1M token context window (Pro/Team tiers) that enables suggestions informed by distant code definitions and cross-file dependencies, constructed via local codebase semantic search rather than simple token-based recency. Suggestions adapt to detected coding style on Pro/Team tiers through implicit pattern learning from recent edits.
Unique: 1M token context window with codebase-wide semantic indexing enables suggestions informed by distant code definitions and cross-file patterns, versus competitors (Copilot, Tabnine) that typically use fixed context windows (4K-32K tokens) or file-local context. Claimed 250ms latency suggests optimized retrieval pipeline, though indexing mechanism and performance at scale remain undisclosed.
vs alternatives: Larger context window than GitHub Copilot (8K-32K tokens) and faster latency than unnamed competitors (250ms vs 783ms claimed), enabling suggestions on large codebases with minimal typing delay; trade-off is cloud dependency and undisclosed free tier limitations.
Provides a separate chat interface supporting multiple LLM backends (GPT-4o, Claude 3.5 Sonnet, GPT-4, others) for conversational code assistance. Users attach files, reference recent edits, and trigger compiler diagnostic uploads; the system generates diffs and applies code changes directly to the editor. Model selection is per-conversation, and $5/month in credits (included in Pro/Team) covers external model API costs; overage pricing is undisclosed. Hotkey-driven workflow enables rapid context switching between inline completion and chat.
Unique: Multi-model chat interface with per-conversation model selection and integrated diff application, combined with compiler diagnostic auto-upload. Unlike Copilot Chat (single model per tier) or standalone ChatGPT, Supermaven Chat unifies multiple LLM backends in a single hotkey-driven workflow with direct editor integration for change application.
Supermaven scores higher at 71/100 vs VSCode Aider (Sengoku) at 28/100. VSCode Aider (Sengoku) leads on ecosystem, while Supermaven is stronger on adoption and quality.
Need something different?
Search the match graph →© 2026 Unfragile. Stronger through disorder.
vs alternatives: Supports multiple LLM backends (GPT-4o, Claude 3.5 Sonnet) in one interface with included credits, whereas GitHub Copilot Chat is single-model per tier and requires separate ChatGPT subscription for model switching; trade-off is credit limits and unknown overage pricing.
Supermaven Chat can automatically upload compiler diagnostic messages (errors, warnings) alongside code context to provide error-aware suggestions and fixes. The mechanism is described as 'automatically uploading your code together with compiler diagnostic messages,' but specific language/compiler support and the upload trigger mechanism are undisclosed. This feature is Chat-only and not available in inline completion.
Unique: Automatic compiler diagnostic upload in Chat for error-aware suggestions, versus competitors (Copilot, Tabnine) that require manual error context or have limited diagnostic integration. Supermaven's approach reduces friction but with undisclosed language/compiler support.
vs alternatives: Automatic diagnostic upload reduces manual context-gathering compared to manual copy-paste; trade-off is undisclosed language support and unclear upload trigger mechanism.
Supermaven offers a 30-day free trial of the Pro tier ($10/month), providing full access to 1M token context window, largest model, style adaptation, and $5/month chat credits. No credit card is required to start the trial (implied), and trial conversion to paid is automatic after 30 days unless cancelled. Trial terms and auto-renewal policy are not explicitly detailed.
Unique: 30-day free trial of Pro tier with full feature access (1M context, largest model, chat credits), versus competitors (Copilot 2-month free trial, Tabnine free tier only) with different trial lengths and feature access. Supermaven's approach is generous but with undisclosed auto-renewal terms.
vs alternatives: Full Pro feature access during trial compared to limited free tier; trade-off is undisclosed auto-renewal policy and potential unexpected charges if not cancelled.
Supermaven requires internet connectivity and server-side inference; no offline mode or local inference capability is mentioned or available. All code completion requests are sent to Supermaven's backend servers for processing, and responses are returned over the network. This creates a hard dependency on network connectivity and Supermaven's service availability; if the service is down or network is unavailable, code completion is not available.
Unique: Supermaven has no offline mode or local inference capability; all processing is server-side. GitHub Copilot also requires server-side inference, but Tabnine offers local inference options for some use cases. Supermaven's lack of offline capability is a significant limitation for developers with connectivity constraints.
vs alternatives: Supermaven's server-side-only approach is comparable to GitHub Copilot; Tabnine offers local inference options, making Tabnine more suitable for offline work. Supermaven's lack of offline capability is a weakness vs. Tabnine.
Analyzes recent code edits and inferred coding patterns to adapt inline suggestions to match team conventions, naming patterns, and structural preferences. The mechanism is implicit (not explicit fine-tuning) and operates only on Pro/Team tiers, suggesting pattern learning from editor activity rather than explicit configuration. Free tier uses a single base model without personalization.
Unique: Implicit style adaptation via editor activity analysis without explicit configuration, versus competitors (Copilot, Tabnine) that require manual style guides or explicit fine-tuning. Supermaven's approach is transparent to the user but also non-configurable and undisclosed in mechanism.
vs alternatives: Requires no manual style configuration compared to tools requiring explicit style guides; trade-off is lack of transparency and inability to control or export learned styles.
Delivers code suggestions to the editor inline as the developer types, with a claimed baseline latency of 250ms from keystroke to suggestion display. The system uses a cloud inference backend and local editor plugin to minimize round-trip time. Latency claim is positioned against an unnamed competitor (783ms), but methodology is undisclosed and no independent verification is provided.
Unique: Claimed 250ms latency via optimized cloud inference pipeline and editor plugin architecture, versus competitors with higher latency (783ms unnamed baseline). Actual differentiation is undisclosed; mechanism may involve request batching, model quantization, or edge caching, but specifics are not public.
vs alternatives: Faster than unnamed competitor (250ms vs 783ms claimed); trade-off is cloud dependency and unverified latency claim with no SLA or performance guarantee.
Provides native editor extensions for VS Code, JetBrains IDEs (IntelliJ IDEA, PyCharm, WebStorm, etc.), and Neovim, enabling inline suggestion rendering, hotkey-driven chat access, and compiler diagnostic integration directly within the editor. Each plugin variant is maintained separately and integrates with the editor's native autocomplete UI, keybinding system, and file context APIs.
Unique: Native plugins for three major editor ecosystems (VS Code, JetBrains, Neovim) with integrated chat and diff application, versus competitors (Copilot, Tabnine) that support broader editor ecosystems but with less deep integration in some cases. Supermaven's approach prioritizes depth over breadth.
vs alternatives: Deep integration with VS Code and JetBrains (native autocomplete UI, hotkey system) compared to web-based tools or lighter integrations; trade-off is limited editor support (no Sublime, Vim, Emacs) and undisclosed Neovim support details.
+5 more capabilities