| 1 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $10/mo |
| Capabilities | 11 decomposed | 13 decomposed |
| Times Matched | 0 | 0 |
Captures microphone audio during active chat sessions and transcribes it to text using Azure Speech SDK, with configurable language selection and automatic submission on release. Integrates directly into GitHub Copilot Chat UI via a microphone button, supporting both continuous listening and push-to-talk modes via Ctrl+I (Windows/Linux) or Cmd+I (macOS). The extension handles audio buffering, language detection, and real-time transcription without requiring API keys or internet connectivity for local processing.
Unique: Integrates Azure Speech SDK directly into VS Code's chat UI with hold-to-submit keybinding (Ctrl+I) rather than requiring separate voice recording apps or external transcription services; claims local processing without API keys, though Azure SDK dependency suggests potential cloud fallback architecture not fully transparent
vs alternatives: Tighter VS Code integration than generic voice-to-text tools (Whisper, Google Speech-to-Text) because it's built into the editor's chat interface and respects VS Code's keybinding system, but lacks the offline-first guarantees of local Whisper models
Enables voice-to-text input directly into the active editor at the current cursor position via Ctrl+Alt+V (Windows/Linux) or Cmd+Alt+V (macOS). Uses Azure Speech SDK for transcription with configurable language selection. Text is inserted synchronously after transcription completes, supporting code comments, documentation, and prose without requiring chat context or Copilot Chat extension.
Unique: Operates independently of Copilot Chat, allowing voice dictation directly into any editor file without requiring AI chat context; uses VS Code's native keybinding system (Ctrl+Alt+V) and respects cursor position for precise insertion, unlike generic voice-to-text tools that require separate applications
vs alternatives: More integrated than external dictation tools (Dragon NaturallySpeaking, OS-level speech input) because it's built into VS Code's editor context and respects cursor position, but lacks the AI-assisted correction and formatting of dedicated voice writing tools
The extension is explicitly documented as 'still in development,' indicating active feature development, bug fixes, and potential breaking changes. The extension is distributed via the VS Code Marketplace as a free, installable extension, but stability, maturity, and feature completeness are not guaranteed. Users should expect changes to keybindings, settings, UI, and capabilities as the extension evolves.
Unique: Explicitly documented as 'still in development,' signaling that the extension is actively evolving and may undergo breaking changes; this transparency about maturity is rare among VS Code extensions, but creates uncertainty about long-term stability and feature completeness
vs alternatives: More transparent about development status than many extensions that hide maturity issues, but less stable and feature-complete than mature voice tools (OS-native voice APIs, established voice platforms) that have reached production readiness
Reads chat responses aloud using text-to-speech synthesis when the `accessibility.voice.autoSynthesize` setting is enabled AND the user initiated the chat message via voice input. The extension uses Azure Speech SDK for TTS with language selection matching the STT language. Audio playback occurs automatically after the AI response is generated, providing audio feedback without requiring manual activation.
Unique: Conditionally activates TTS only when STT was used as input (voice-in-voice-out pattern), rather than offering universal TTS for all chat responses; this reduces cognitive load and audio clutter for text-input users while providing full audio feedback for voice-first users
vs alternatives: More contextually aware than generic TTS tools (OS-level screen readers, browser extensions) because it only synthesizes when voice input was used and integrates with Copilot Chat's response lifecycle, but lacks fine-grained control over voice selection and playback parameters
Supports speech-to-text and text-to-speech across 26 languages via the `accessibility.voice.speechLanguage` setting, which applies uniformly to both STT and TTS operations. Language selection is configurable via VS Code's Settings Editor and persists across sessions. The extension uses Azure Speech SDK's language models for both recognition and synthesis, with language detection and processing handled transparently without user intervention.
Unique: Provides unified language configuration (single `accessibility.voice.speechLanguage` setting) that applies to both STT and TTS, ensuring consistency across voice input/output workflows; leverages Azure Speech SDK's multilingual models rather than requiring separate language-specific tools
vs alternatives: Broader language support (26 languages) than many open-source STT tools (Whisper supports ~99 languages but with variable quality), but less granular than enterprise speech platforms (Google Cloud Speech-to-Text, AWS Transcribe) which offer per-request language selection and custom vocabulary
Provides keyboard shortcuts to start, stop, and submit voice input sessions without mouse interaction. Default keybindings are Ctrl+I (Windows/Linux) or Cmd+I (macOS) for chat voice (hold-to-submit or toggle mode), and Ctrl+Alt+V (Windows/Linux) or Cmd+Alt+V (macOS) for editor dictation. Keybindings are fully customizable via VS Code's Keybinding Shortcuts Editor, with conditional activation via `when` clauses (e.g., `!voiceChatInProgress`, `!editorDictation.inProgress`) to prevent conflicts.
Unique: Integrates with VS Code's native keybinding system and `when` clause conditions, allowing voice session control to be composed with other editor state checks (e.g., `when: editorFocus && !voiceChatInProgress`); supports both toggle and hold-to-submit modes via keybinding configuration
vs alternatives: More flexible than fixed voice activation buttons (Copilot Chat's microphone icon) because it respects VS Code's keybinding customization system and conditional activation, but requires manual configuration compared to out-of-the-box voice tools with preset keybindings
Processes speech-to-text and text-to-speech operations using Azure Speech SDK, which the extension claims performs local processing on the user's machine without requiring internet connectivity or API keys. The SDK handles audio capture, buffering, language detection, and transcription/synthesis internally. However, the documentation does not explicitly clarify whether Azure Speech SDK calls are truly local or cloud-based, creating ambiguity about data privacy and network requirements.
Unique: Claims local speech processing via Azure Speech SDK without requiring API keys or internet connectivity, positioning as a privacy-first alternative to cloud-based STT/TTS services; however, the actual architecture (local vs. cloud) is not transparently documented, creating uncertainty about data handling
vs alternatives: Avoids the API key management and cloud service costs of Google Speech-to-Text or AWS Transcribe, but lacks the transparency and offline-first guarantees of local Whisper models; Azure Speech SDK's true processing location (local vs. cloud) is ambiguous compared to clearly local alternatives
Embeds a microphone button directly into the GitHub Copilot Chat interface, providing visual affordance for voice input without requiring keybinding knowledge. The button appears in the chat input area and triggers voice capture when clicked or held, with visual feedback indicating recording state. Integration is seamless when both VS Code Speech and GitHub Copilot Chat extensions are installed; the microphone button is unavailable if Copilot Chat is not present.
Unique: Provides native UI integration with GitHub Copilot Chat's chat input area via a microphone button, rather than requiring users to discover and memorize keybindings; the button is context-aware and only appears when Copilot Chat is available, avoiding UI clutter
vs alternatives: More discoverable than keybinding-only voice input (Copilot Chat's default) because the microphone button provides visual affordance, but less flexible than keybinding-driven activation because it's limited to Copilot Chat and cannot be customized or extended to other chat interfaces
+3 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 VS Code Speech at 44/100. VS Code Speech leads on adoption and ecosystem, while Supermaven is stronger on quality.
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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