| 0 |
| 1 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $10/mo |
| Capabilities | 9 decomposed | 13 decomposed |
| Times Matched | 0 | 0 |
Automatically detects text selection in VS Code editor and displays translation results in a hover tooltip without modifying editor content. Routes short phrases to Youdao's proprietary API for fast dictionary-style translation, while routing longer text or Japanese-containing selections to Doubao LLM via Volcano Ark. The routing decision is made client-side based on text length heuristics and character set detection (kana detection for Japanese), eliminating unnecessary API calls for short terms.
Unique: Implements client-side intelligent routing between two distinct translation engines (Youdao for short text, Doubao for long text) based on text length heuristics and character set detection, avoiding unnecessary LLM API calls for simple dictionary lookups while preserving context-aware translation for complex text.
vs alternatives: Faster than pure-LLM translation tools for short phrases (uses Youdao's optimized API) while more context-aware than dictionary-only tools for longer text (uses Doubao LLM), creating a hybrid approach that balances latency and translation quality.
Extension automatically activates when VS Code window loads without requiring manual trigger or configuration. Uses VS Code's activation event system to register hover listeners and command handlers immediately upon window completion, eliminating cold-start friction. The activation is transparent to the user — translation functionality is immediately available without any setup steps beyond initial API key configuration.
Unique: Uses VS Code's onWindowLoad activation event to register all hover and command listeners immediately upon window completion, ensuring zero-latency availability without requiring users to manually trigger activation or run setup commands.
vs alternatives: More seamless than extensions requiring explicit activation commands (e.g., 'Enable Translation') or keybinding-first workflows, as translation is immediately available on any text selection without user action.
Allows users to specify which Doubao model to use for long-text translation by entering a model ID from Volcano Ark console (e.g., 'Doubao-1.5-pro-32k'). Additionally supports customization of the system prompt (role definition) sent to Doubao, enabling users to override the default multi-language-to-Chinese translation behavior with custom instructions. Configuration is stored in VS Code settings and validated via a built-in connectivity test function that verifies API key and model availability before use.
Unique: Provides both model ID selection and system prompt customization in a single settings interface, with a built-in connectivity test function that validates both API key and model availability before use, reducing trial-and-error configuration cycles.
vs alternatives: More flexible than fixed-model translation tools (allows model switching) while simpler than full Doubao API clients (hides authentication and request formatting complexity behind VS Code settings).
Detects presence of Japanese kana characters (hiragana, katakana) in selected text and automatically routes such selections exclusively to Doubao LLM, bypassing Youdao API entirely. This routing decision is made client-side before API calls are initiated, preventing unnecessary Youdao requests for Japanese text. The detection mechanism is character-set based (likely Unicode range checking for kana blocks U+3040-U+309F and U+30A0-U+30FF) and is non-configurable.
Unique: Implements automatic character-set detection for Japanese kana (U+3040-U+309F and U+30A0-U+30FF Unicode ranges) to trigger Doubao-exclusive routing, avoiding Youdao API calls for Japanese text without requiring user configuration or manual routing decisions.
vs alternatives: More intelligent than single-engine translation tools (automatically selects appropriate engine for Japanese) while more opaque than tools with visible routing logic (users cannot see or override routing decisions).
Provides an optional command palette entry ('translate' command) that can be invoked via keyboard shortcut (Ctrl+Alt+T on Windows/Linux, Cmd+Alt+T on macOS) to explicitly trigger translation of the current selection. This complements the default hover-based interaction, allowing users who prefer explicit command invocation or have keybinding muscle memory to trigger translation without hovering. The command executes the same routing logic and API calls as hover-triggered translation, but requires deliberate user action.
Unique: Provides both hover-based (passive) and command-palette-based (explicit) translation triggers, allowing users to choose interaction style while reusing the same underlying routing and API logic for both paths.
vs alternatives: More flexible than hover-only tools (accommodates keyboard-first workflows) while simpler than tools with extensive keybinding customization (uses standard VS Code command palette integration).
Routes text selections below an undocumented length threshold to Youdao's proprietary suggestion API for fast, dictionary-style translation. Youdao API is non-configurable (no API key or model selection available) and operates as a closed black-box service. The extension handles authentication and request formatting internally, presenting results in the same hover tooltip as Doubao translations. Youdao is selected for short text to minimize latency compared to LLM-based approaches.
Unique: Integrates Youdao's proprietary API as a lightweight, low-latency translation engine for short text, with client-side routing logic that automatically selects Youdao for phrases below an undocumented length threshold, reducing LLM API costs and latency for common short-text translation scenarios.
vs alternatives: Faster than pure-LLM translation for short phrases (avoids LLM overhead) while less transparent than documented APIs (Youdao API is proprietary and non-configurable).
Provides a built-in test function accessible from VS Code settings UI or command palette that validates Doubao API key and model ID connectivity before translations are attempted. The test function sends a minimal request to Volcano Ark API to verify authentication and model availability, providing immediate feedback on configuration correctness. This reduces trial-and-error debugging by catching misconfigured credentials or unavailable models before they cause translation failures.
Unique: Integrates a built-in connectivity test function directly into VS Code settings UI, allowing users to validate API credentials and model availability without leaving the settings panel or attempting actual translations.
vs alternatives: More convenient than manual API testing (no need to write test scripts) while less comprehensive than full API explorers (only validates connectivity, not quota or cost).
Displays translation results in a VS Code hover tooltip overlay that appears when user hovers over selected text. The tooltip is read-only and non-interactive — translations cannot be edited, copied directly from the tooltip, or inserted into the editor. This design keeps the editor content pristine and prevents accidental modifications, but limits the utility of translation results to viewing only. The tooltip automatically dismisses when the user moves the mouse away or continues editing.
Unique: Implements translation results as read-only hover tooltips that automatically dismiss on mouse movement, preventing accidental editor modifications while maintaining a non-intrusive viewing experience.
vs alternatives: Safer than inline translation insertion (no risk of accidental code changes) while less interactive than side-panel or inline-editable approaches (users cannot directly copy or edit translations).
+1 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 TranslationToolbox at 35/100. TranslationToolbox leads on ecosystem, while Supermaven is stronger on adoption and 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