{ "data": { "a": { "slug": "giggy-stt", "name": "Giggy Speech to Text", "vendor": "Giggy", "vendorUrl": "https://giggy.ai", "kind": "model", "category": "speech-to-text", "summary": "Giggy's hosted speech-to-text API transcribes 16 kHz mono WAV recordings in free Batch, prepaid Fast and Streaming modes, and live audio over a WebSocket, with Python and Node SDKs and a remote MCP server.", "url": "https://www.anchorterminal.com/tools/giggy-stt", "markdownUrl": "https://www.anchorterminal.com/tools/giggy-stt.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/giggy-stt.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/giggy-stt.json", "dns": "giggy-stt.grade.anchorterminal.com", "repo": "https://github.com/giggy-ai/giggy-js", "license": "Proprietary hosted service. The terms page draws its text by script and was not read. The Python and Node SDKs, the Pipecat adapter and the MCP repository are ISC (Copyright 2026 Giggy), the n8n node MIT", "transports": [ "http", "sse", "websocket", "streamable-http" ], "remoteUrl": "https://api.giggy.ai/v1", "packages": [ { "registry": "pypi", "name": "giggy" }, { "registry": "npm", "name": "@giggy-ai/sdk" }, { "registry": "pypi", "name": "pipecat-giggy" } ], "auth": "api-key", "authNotes": "Self-serve API key prefixed `giggy_sk_`, shown once when created or rotated, rejected immediately after revocation, up to ten active per Personal space or Workspace and tied for good to the space that created it. REST sends it in `xi-api-key`; the WebSocket upgrade and the MCP server take `Authorization: Bearer`. No key scopes or expiry were found, and no query-string option is documented (https://giggy.ai/docs/api-reference).", "pricing": "freemium", "pricingNotes": "Batch transcription is free, queued, for recordings of 0.5 seconds to 25 minutes. Fast costs 4,000 credits ($0.04) and Streaming 8,000 credits ($0.08) per input audio hour on Pro, Studio or Scale credits, rounded up to one credit per request. Credits come in one-time packs from $3 and expire a year after purchase. Personal accounts get free credits topped up to 10,000 a month. Whether a card is needed was not stated on any page read (https://giggy.ai/pricing).", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on the pricing page, the speech API docs, the API reference, llms.txt or llms-full.txt read on 2026-11-04. Credits are bought in prepaid packs; the payment method is not named on any page read.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-04" }, "docsUrl": "https://giggy.ai/docs/speech-api", "llmsTxt": "https://giggy.ai/llms.txt", "openapi": "https://api.giggy.ai/v1/openapi.json", "registryName": "io.github.GRQDigitalCapital/giggy-mcp", "capabilities": [ "speech.stt", "speech.batch", "speech.streaming", "speech.languages" ], "tags": [ "official", "hosted", "model", "closed-source", "streaming", "batch", "async-jobs", "free-tier", "python", "typescript", "openapi", "llms-txt", "mcp", "websocket", "new" ], "lastRelease": "2026-11-01", "graded": true, "anchor": { "graded": true, "score": 54.5, "grade": "C", "agentReady": false, "rank": 806, "ranked": true, "rankOf": 1349, "categoryRank": 15, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 68, "maintenance": 69, "payments": 30, "reliability": 50, "schema": 68, "security": 57, "transparency": 30 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "low", "date": "2026-11-04" }, "negative": 0, "verdict": "Fast transcription costs $0.04 an input audio hour and Batch is free up to 25 minutes, with published rate limits, Retry-After and a rule to check a generation before resubmitting. Input must be 16 kHz mono WAV, there are no timestamps or speaker labels, the status page covers text-to-speech only, and no company is named on pages we could read.", "bestFor": "Agents and voice pipelines that need plain transcripts of recorded or live speech at a few cents an hour, or free for clips under 25 minutes, and can convert audio to 16 kHz mono WAV first.", "strengths": [ "Fast is $0.04 and Streaming $0.08 per input audio hour on Pro credits, and Batch is free for recordings of 0.5 seconds to 25 minutes", "Per-credential rate limits are published with numbers, 429 carries `Retry-After`, and `RateLimit-*` headers report what is left", "The docs say to read a generation by UUID after a timeout or 504 instead of uploading again, and the SDKs never retry paid requests", "llms.txt, llms-full.txt and SDK READMEs state what the API does not do, including no diarisation, timestamps or OpenAI-compatible STT", "Official Python and Node SDKs at 0.2.1, a Pipecat adapter with live STT and a remote MCP server, all released within the last four weeks" ], "weaknesses": [ "Recorded input must be PCM16 mono 16 kHz WAV, so MP3, M4A, stereo or other sample rates need converting before upload", "No word timestamps, speaker labels, confidence scores or redaction, per the speech API docs", "The status page has one component, Text to speech, and no incident history, so speech-to-text availability isn't shown", "REST transcription has no idempotency key, and `client_request_id` is documented as not making a retried upload safe", "The terms, privacy policy, support and contact pages draw by script, and no company, address or security contact was found on any page read" ], "agentNotes": [ "Pass `mode=batch` explicitly for free transcription. Raw REST and MCP default to paid Fast when `mode` is omitted.", "Convert audio to PCM16 mono 16 kHz WAV first and send it as the raw body with `Content-Type: audio/wav`.", "Keep the `generation_uuid` from the 202 and poll `GET /v1/generations/{uuid}`. Never re-upload after a timeout or 504 before reading that generation.", "Fetch the transcript from the signed `generation.result.url` after completion, without the API key. It can disappear after retention cleanup.", "On the live WebSocket, replace earlier text with each cumulative `transcription` event and publish final text only after `input_complete`." ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "low", "grade": "C", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 54.5 } ], "editorialScores": { "ergonomics": 68, "maintenance": 69, "payments": 30, "reliability": 50, "schema": 68, "security": 57, "transparency": 23 }, "provenanceScore": 36, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "python -m pip install giggy==0.2.1 # or: npm install @giggy-ai/sdk", "http": "curl -X POST \"https://api.giggy.ai/v1/audio/transcriptions?mode=batch\u0026language=en\" \\\n -H \"xi-api-key: $GIGGY_API_KEY\" -H \"Content-Type: audio/wav\" \\\n --data-binary @recording.wav", "config": { "mcpServers": { "giggy-speech": { "headers": { "Authorization": "Bearer ${GIGGY_API_KEY}" }, "type": "http", "url": "https://giggy.ai/mcp" } } } }, "letme": { "capability": "https://letme.dev/speech.stt", "tool": "https://letme.dev/giggy-stt" }, "area": "voice", "unitPrices": [ { "item": "Fast, Pro, Studio or Scale credits", "unit": "audio-minute", "usd": 0.000667, "note": "published as $0.04 per input audio hour, rounded up to one credit per request" }, { "item": "Streaming, Pro, Studio or Scale credits", "unit": "audio-minute", "usd": 0.001333, "note": "published as $0.08 per input audio hour" }, { "item": "Fast, Starter pack", "unit": "audio-minute", "usd": 0.000765, "note": "$3 for 261,300 credits, $0.0459 an hour" }, { "item": "Streaming, Starter pack", "unit": "audio-minute", "usd": 0.00153, "note": "$0.0918 an hour" }, { "item": "Batch", "unit": "audio-minute", "usd": 0, "note": "free, queued, 0.5 seconds to 25 minutes a recording" } ], "provenance": { "legalEntity": "", "domain": "giggy.ai", "domainRegistered": "", "endpointOnVendorDomain": true, "terms": "https://giggy.ai/terms", "privacy": "https://giggy.ai/privacy", "statusPage": "https://giggy.ai/status", "changelog": "", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "unchecked: the legal entity. /terms, /privacy, /acceptable-use, /contact, /docs/support and /docs/privacy-rights returned only their titles and metadata, because their text is drawn by script, and /terms.md answered a client error. The about, pricing, grants and docs pages that did render name only Giggy, with 'Made in California' on the about page. The repositories' licences say 'Copyright 2026 Giggy'.", "The status page tracks one component, Text to speech, with 14-day availability and completion figures refreshed every 30 minutes and no incident history. It has no speech-to-text component.", "No service changelog was found. The SDK and Pipecat repositories carry CHANGELOG.md files, dated in the Python SDK and the Pipecat adapter.", "https://giggy.ai/.well-known/security.txt answered a client error. None of the six public repositories has a SECURITY.md.", "robots.txt on giggy.ai allows / and disallows /api/, /ops/, /app/ and /blog/*.md for `*` and for the named AI agents, with no Content-Signal line. api.giggy.ai's robots.txt could not be read (the fetch needed an approval that wasn't given), so nothing on that host was fetched, the OpenAPI file included.", "unchecked: RDAP for giggy.ai (refused for want of an approval on 4 November 2026)." ], "score": 36 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/giggy-stt.json", "live": { "slug": "giggy-stt", "probe": { "target": "https://api.giggy.ai/v1", "method": "get", "lastAt": "2026-11-04T21:39:24.734230033Z", "lastOk": true, "lastStatus": 404, "lastMs": 398, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 286, "p95ms24h": 654, "samples24h": 64, "samples30d": 64, "days": [ { "date": "2026-11-04", "probes": 64, "ok": 64 } ] }, "vendorStatus": { "page": "https://giggy.ai/status", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-04T21:25:54.463598549Z" }, "versions": [ { "registry": "github", "name": "giggy-ai/giggy-js", "version": "v0.1.0", "released": "2026-10-07", "seenAt": "2026-11-04T20:18:19.850001725Z" }, { "registry": "mcp-registry", "name": "io.github.GRQDigitalCapital/giggy-mcp", "version": "1.0.2", "seenAt": "2026-11-04T17:11:44.552009456Z" }, { "registry": "npm", "name": "@giggy-ai/sdk", "version": "0.2.1", "seenAt": "2026-11-04T20:18:17.973963585Z" }, { "registry": "pypi", "name": "giggy", "version": "0.2.1", "released": "2026-11-01", "seenAt": "2026-11-04T20:18:17.733675794Z" }, { "registry": "pypi", "name": "pipecat-giggy", "version": "0.3.3", "released": "2026-11-01", "seenAt": "2026-11-04T20:18:18.946085778Z" } ], "githubStars": 0, "npmWeekly": 209, "pypiWeekly": 32, "securityTxt": { "url": "https://giggy.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-04T15:54:29.107165985Z" }, "updatedAt": "2026-11-04T21:39:24.734230033Z" } }, "answer": "Gladia Speech-to-Text API + MCP scores 69.8 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category.", "b": { "slug": "gladia-stt", "name": "Gladia Speech-to-Text API + MCP", "vendor": "Gladia", "vendorUrl": "https://www.gladia.io", "kind": "model", "category": "speech-to-text", "summary": "Speech-to-text API for live and recorded audio, with multilingual transcription and code switching.", "url": "https://www.anchorterminal.com/tools/gladia-stt", "markdownUrl": "https://www.anchorterminal.com/tools/gladia-stt.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/gladia-stt.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/gladia-stt.json", "dns": "gladia-stt.grade.anchorterminal.com", "repo": "https://github.com/gladiaio/sdk", "license": "MIT (SDKs and MCP server)", "transports": [ "http", "stdio" ], "remoteUrl": "https://api.gladia.io/v2", "packages": [ { "registry": "npm", "name": "@gladiaio/sdk" }, { "registry": "pypi", "name": "gladiaio-sdk" }, { "registry": "npm", "name": "@gladiaio/mcp" } ], "auth": "api-key", "authNotes": "`x-gladia-key` header. Live sessions start with `POST /v2/live`, which returns a WebSocket URL. The MCP server reads `GLADIA_API_KEY` from the environment.", "pricing": "freemium", "pricingNotes": "Prepaid wallet, priced in euros. Self-serve async is 0.27€ an hour on `solaria-1` and 0.16€ on `solaria-3` for the first 100 hours a month, falling with volume to 0.21€ and 0.12€ above 10,000 hours. Real-time is 0.68€ an hour. Add-ons are billed per hour (summarisation 0.03€, sentiment 0.02€, translation 0.05€, NER and PII redaction 0.07€). Top-ups from 1,000€ earn 10 to 20 per cent bonus credit. New accounts get 50€ of free credit. Enterprise is custom (https://www.gladia.io/pricing).", "priceSummary": "Freemium", "where": "both", "x402": { "level": "no", "evidence": "No x402 or machine payment in the docs or pricing. Billed to a funded account (checked 2026-09-30).", "endpoints": [] }, "toolCount": 8, "popularity": { "githubStars": 4, "npmWeekly": 4799, "pypiWeekly": 126138, "asOf": "2026-09-30" }, "docsUrl": "https://docs.gladia.io", "llmsTxt": "https://docs.gladia.io/llms.txt", "openapi": "https://api.gladia.io/openapi.json", "capabilities": [ "speech.stt", "speech.streaming", "speech.batch", "speech.diarisation", "speech.languages", "speech.translation" ], "tags": [ "hosted", "freemium", "no-card", "mcp", "llms-txt", "openapi", "python", "typescript", "webhooks", "async-jobs", "streaming", "batch", "enterprise" ], "lastRelease": "2026-10-23", "graded": true, "anchor": { "graded": true, "score": 69.8, "grade": "B", "agentReady": false, "rank": 205, "ranked": true, "rankOf": 1349, "categoryRank": 7, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 70, "payments": 40, "reliability": 70, "schema": 95, "security": 65, "transparency": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "The `solaria-1` model transcribes live and recorded audio in over 100 languages with code switching, behind an OpenAPI file and SDKs in two languages. Self-serve audio is used for model training unless the account opts out, and Gladia's pages disagree on retention and training defaults.", "bestFor": "Multilingual meetings and calls where live and async transcription in 100+ languages is needed, and for teams who want an MCP server.", "strengths": [ "100+ languages on `solaria-1` with code switching, live and async", "Async from 0.16€ an hour on `solaria-3`, with automatic volume discounts", "OpenAPI file, llms.txt, JavaScript and Python SDKs at 2.2.1 and an official MCP server", "SOC 2 Type 1 and Type 2, a bug bounty programme and a 99.9% uptime SLA on Enterprise", "One-time 50€ credit for new accounts" ], "weaknesses": [ "Self-serve audio is used for model training by default unless the account opts out", "The security, retention and pricing pages give different retention and training defaults", "Add-ons such as translation, summaries and NER now cost extra per hour", "ISO 27001 is still in progress", "No Retry-After on 429s, and no SLA below Enterprise" ], "agentNotes": [ "Don't resubmit a pre-recorded job after a 200 or a `transcription.created` webhook. It's already queued", "Pick `solaria-3` only for async EN, FR, DE, ES or IT audio. Anything live or multilingual needs `solaria-1`", "A 429 means the concurrency limit, 3 async and 1 live on the free plan. Wait for a running job to finish", "Opt the account out of model training in its profile before sending sensitive audio on Self-serve", "Split files over 135 minutes or 1,000 MB" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 69.8 } ], "editorialScores": { "ergonomics": 75, "maintenance": 70, "payments": 40, "reliability": 70, "schema": 95, "security": 65, "transparency": 50 }, "provenanceScore": 80, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "http": "curl https://api.gladia.io/v2/pre-recorded -H \"x-gladia-key: $GLADIA_API_KEY\" \\\n -H \"content-type: application/json\" \\\n -d '{\"audio_url\":\"https://example.com/audio.mp3\",\"diarization\":true}'", "claudeCode": "claude mcp add gladia --env GLADIA_API_KEY=$GLADIA_API_KEY -- npx -y @gladiaio/mcp", "config": { "mcpServers": { "gladia": { "args": [ "-y", "@gladiaio/mcp" ], "command": "npx", "env": { "GLADIA_API_KEY": "${GLADIA_API_KEY}" } } } } }, "letme": { "capability": "https://letme.dev/speech.stt", "tool": "https://letme.dev/gladia-stt" }, "area": "voice", "provenance": { "legalEntity": "Gladia SAS", "domain": "gladia.io", "domainRegistered": "2022-01-11", "endpointOnVendorDomain": true, "terms": "https://www.gladia.io/terms-conditions", "privacy": "https://www.gladia.io/privacy-notice", "statusPage": "https://status.gladia.io", "changelog": "https://www.gladia.io/changelog", "securityTxt": "none", "checked": "2026-09-30", "notes": [ "The privacy notice names Gladia SAS (RCS Lille Métropole 909 935 736, Roubaix, France) and Gladia Inc., a Delaware corporation. Separate terms exist for each at https://www.gladia.io/terms-conditions-gladia-inc" ], "score": 80 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/gladia-stt.json", "live": { "slug": "gladia-stt", "probe": { "target": "https://api.gladia.io/v2", "method": "get", "lastAt": "2026-11-04T21:39:24.915280113Z", "lastOk": true, "lastStatus": 404, "lastMs": 612, "authRequired": false, "uptime24h": 100, "uptime30d": 99.91, "p50ms24h": 479, "p95ms24h": 1071, "samples24h": 247, "samples30d": 8090, "days": [ { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 272, "ok": 272 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 266 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 248, "ok": 248 }, { "date": "2026-10-30", "probes": 249, "ok": 248 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 223, "ok": 223 } ], "outages": [ { "start": "2026-10-07T12:49:45.159769611Z", "end": "2026-10-07T13:21:50.310567918Z", "note": "timed out" } ] }, "vendorStatus": { "page": "https://status.gladia.io", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-11-04T21:38:17.405529221Z" }, "versions": [ { "registry": "github", "name": "gladiaio/sdk", "version": "sdk-js@2.2.1", "released": "2026-10-23", "seenAt": "2026-11-04T20:18:36.431194132Z" }, { "registry": "npm", "name": "@gladiaio/mcp", "version": "0.1.1", "seenAt": "2026-11-04T20:18:35.291935831Z" }, { "registry": "npm", "name": "@gladiaio/sdk", "version": "2.2.1", "seenAt": "2026-11-04T20:18:34.21086314Z" }, { "registry": "pypi", "name": "gladiaio-sdk", "version": "2.2.1", "released": "2026-10-23", "seenAt": "2026-11-04T20:18:35.105942721Z" } ], "githubStars": 4, "npmWeekly": 11303, "pypiWeekly": 152501, "securityTxt": { "url": "https://gladia.io/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-04T15:54:17.904215634Z" }, "llmsTxt": { "url": "https://docs.gladia.io/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-04T15:23:05.790038899Z" }, "domain": { "domain": "gladia.io", "checkedAt": "2026-11-01T14:18:24.128393611Z" }, "pages": [ { "url": "https://www.gladia.io/changelog", "kind": "changelog", "status": 304, "checkedAt": "2026-11-04T08:40:30.004629341Z", "changedAt": "2026-10-31T06:27:50.8188043Z", "fingerprint": "2d9a97e569dd" }, { "url": "https://www.gladia.io/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-04T08:40:32.021344895Z", "changedAt": "2026-11-04T08:40:32.021344895Z", "fingerprint": "0ceaa29762d7" }, { "url": "https://www.gladia.io/privacy-notice", "kind": "privacy", "status": 304, "checkedAt": "2026-11-04T08:40:34.096106895Z", "changedAt": "2026-10-31T06:27:54.847451002Z", "fingerprint": "f9ff7892ae9b" }, { "url": "https://www.gladia.io/terms-conditions", "kind": "terms", "status": 304, "checkedAt": "2026-11-04T08:40:36.015573336Z", "changedAt": "2026-10-31T06:27:56.886711706Z", "fingerprint": "a8aaf82e03a4" } ], "github": { "repo": "gladiaio/sdk", "checkedAt": "2026-11-02T08:50:58.697165055Z", "stars": 4, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-30T14:44:22Z", "openIssues": 5, "openPRs": 1, "issuesOpened90d": 2, "issuesClosed90d": 2, "prsMerged90d": 20, "replies": { "sampled": 9, "unanswered": 5, "medianDays": 1.6 } }, "updatedAt": "2026-11-04T21:39:24.915280113Z" } }, "edges": [ { "by": 35, "category": "transparency", "leads": "gladia-stt", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed hosted service. The terms exist at /terms but draw by script and could not be read, so their clarity is unknown; the SDK, Pipecat and MCP repositories are ISC and the n8n node MIT (5 of 30). What could be read agrees with itself, no training on user data, an optional 12-hour retention flag, a seven-day window for Batch audio, and the EEA compute flag. The privacy policy, any DPA and a retention period for transcripts were not found or not readable (12 of 30). No deprecation policy or dated notices, only a statement that the legacy origin remains supported (3 of 20). No subprocessors or data locations are named; the EEA-adequate compute option implies processing outside the EEA by default without saying where (3 of 20). 5+12+3+3 = 23.", "b": "Closed service with an MIT SDK and MCP server and separate terms for Gladia SAS and Gladia Inc. (15). The statements disagree. The security page gives a 12-month default retention with custom policies for customers and says only Free plan data trains models, while the retention page gives 1 year on free, 3 weeks on paid and zero retention only on Enterprise, and the pricing page says Self-serve is opted in to training by default. ISO 27001 is described as in progress (15). Breaking changes are flagged with dates in the changelog, such as SDK 2.0.0 and the move to credit billing on 3 July 2026 with a 6 to 20 July rollout, but no deprecation policy was found (10). Hosting with a French provider is stated, and no sub-processor list was found (10)." }, "scores": { "a": 30, "b": 65 } }, { "by": 27, "category": "schema", "leads": "gladia-stt", "name": "Schema \u0026 documentation", "reasons": { "a": "Model reading, with the API reference. The docs and llms.txt link an OpenAPI 3.1 file at https://api.giggy.ai/v1/openapi.json, but api.giggy.ai's robots.txt could not be read, so the file wasn't fetched. We credit only what the reference pages show of it, typed `mode` values, the privacy booleans and a typed error body, and there is no AsyncAPI file for the live socket (12 of 25). llms.txt and llms-full.txt (10). The docs say when to use each mode and transport, that MCP is not a live transport, that an OpenAI base-URL swap does not work for STT, and which options have no equivalent, more than most listings say about when not to use something (17 of 20). `mode` is an enum of three values and the input format is fixed, but `language` is a free code or name with no published list, and the MCP input schemas were read only from the repository's docs, not from the server (11 of 15). Examples in the SDK READMEs, the examples repository and a Postman collection, and an error table of ten statuses with `type`, `code`, `message`, `status`, `request_id` and `param` fields, though only one code value is named (11 of 15). Paths are under `/v1` and the SDK and Pipecat repositories keep CHANGELOG.md files, dated in two of them, but there is no service changelog (7 of 15). 12+10+17+11+11+7 = 68.", "b": "OpenAPI file at api.gladia.io/openapi.json (25). llms.txt (10). Reference pages state purpose per endpoint and the model page says to use `solaria-3` only for async English, French, German, Spanish or Italian (15). Typed bodies with enums and required fields, `audio_url` the only required input for pre-recorded (15). Examples per endpoint and documented error codes (15). Versioned `/v2` paths and a dated changelog (15)." }, "scores": { "a": 68, "b": 95 } }, { "by": 20, "category": "reliability", "leads": "gladia-stt", "name": "Reliability", "reasons": { "a": "Hosted reading, as for deepgram-stt and cartesia-ink-stt. Giggy's own status page at https://giggy.ai/status lists one component, Text to speech, operational on 4 November 2026 with 98.61 per cent observed availability and 99.85 per cent completion over 14 days, refreshed every 30 minutes. It has no speech-to-text component and no incident log, so it shows nothing about this surface (5 of 20). No readable incident history, so the floor (5). Rate limits are published per credential, 60 Batch generation POSTs, 120 event-stream GETs, 600 reads and 120 MCP requests a minute, with eight live contexts per controller; Fast and Streaming POSTs have no per-credential limit and Batch queue capacity isn't given (15). 429 carries `Retry-After` with `RateLimit-*` headers, and the docs give a safe-retry rule for uploads, read the generation by UUID after a timeout or 504 and never upload the same recording again. REST transcription has no idempotency key, but the MCP `transcribe_audio` tool takes one (15). No SLA on the pricing page or in the docs; the terms could not be read (0). No beta or preview label on the API, the SDKs or the MCP server (10). 5+5+15+15+0+10 = 50.", "b": "incident.io status page with per-component uptime bars and incident pages, and an RSS feed read on 1 November (20). One major incident in the 90 days from 3 August, a global Pre-Recorded and Real-Time incident on 23 September 2026 from 07:05 to 08:10 caused by a provider network fault, as read on 1 October. The rest are partial and read as minor, a 20-minute full outage and a timeouts incident on 22 September, slower processing on the afternoon of 23 September, and Europe-only degradations on 2, 10, 14 to 15 (elevated errors and timeouts in Europe from 09:07 on 14 September to 13:58 on 15 September), 21, 22 and 28 September and on 3, 4 and 7 October (Pre-Recorded v2 in Europe) (10). Concurrency limits published with numbers, 25 parallel async jobs plus 300 queued and 30 live sessions on paid plans, 3 and 1 on free (15). The docs say a 429 means the concurrency limit, but we found no backoff guidance or Retry-After (5). The pricing page's plan comparison, read on 1 November, lists a 99.9% uptime SLA for Enterprise (10). `solaria-1` and `solaria-3` are GA (10). 20 + 10 + 15 + 5 + 10 + 10 = 70." }, "scores": { "a": 50, "b": 70 } }, { "by": 10, "category": "payments", "leads": "gladia-stt", "name": "Payments \u0026 pricing", "reasons": { "a": "No x402, MPP or L402 (0). Per-hour prices for Batch, Fast and Streaming and every credit pack published without a login (20). Free Batch transcription and Personal free credits topped up to 10,000 a month, but no page read says whether a card is needed, so half, as other listings read an unstated card requirement (10 of 20). A person signs up in a browser and creates the key there; no programmatic key route was found (0). 0+20+10+0 = 30.", "b": "No x402, MPP or L402 (0). Per-hour prices in euros published without a login, re-read on 1 November, async from 0.27€ an hour on `solaria-1` and 0.16€ on `solaria-3`, real-time 0.68€, add-ons per hour (20). A one-time €50 credit, with no card per the 1 October check (20). A person signs up in a browser (0)." }, "scores": { "a": 30, "b": 40 } }, { "by": 8, "category": "security", "leads": "gladia-stt", "name": "Security \u0026 auth", "reasons": { "a": "Model reading of the checklist, with training and retention in place of the least-privilege and injection lines, as for deepgram-stt and cartesia-ink-stt. Keys prefixed `giggy_sk_` are shown once on creation or rotation, rejected immediately after revocation, limited to ten per space and tied to the space that made them, with REST budgets that Workspace members can set. No scopes or expiry were found. The key travels in a header only, with no query-string option documented (22 of 30). The workspace privacy guide states 'Giggy does not use user data to train models'. The privacy policy and terms draw by script and could not be read to confirm it (18 of 20). Requests can opt into 12-hour content retention and EEA-adequate compute, and a guide gives Batch audio a seven-day window, but no retention period for transcripts was found and results can vanish after an unstated 'retention cleanup' (9 of 15). Generation history per space and a request ID on errors; no audit log of key or admin actions was found (8 of 15). /.well-known/security.txt answered a client error, none of the six repositories has a SECURITY.md, and no disclosure policy, bug bounty or certification was found on the pages that rendered; the support page that may name a reporting route drew by script (0 of 20). 22+18+9+8+0 = 57.", "b": "Model reading of the checklist, with training and retention in place of least-privilege and injection lines. Plain revocable API keys in the `x-gladia-key` header. Live sessions connect to a WebSocket URL minted per session by `POST /v2/live`, which we don't deduct for (20). The pricing page, read on 1 November, says Self-serve, the paid pay-as-you-go plan, is opted in to model training by default with a free opt-out in the profile, and Enterprise is opted out by default. The security page still says only Free plan data is used for training. We score the pricing page's default, as for AWS's default use with an opt-out (10 of 20). Retention is documented and jobs can be deleted, but zero retention needs Enterprise per the retention page (10). Job history through the list endpoint and dashboard, no audit log of key actions found (10). SOC 2 Type 1 and Type 2, a bug bounty programme that doubles as the disclosure route, no security.txt (404 on 1 November) and no public advisories found. The SDKs fixed an API key leak on cross-origin redirects in 2.1.0 (September) and limited list pagination to the configured API in 2.2.0 (13 October), both released. ISO 27001 is in progress, not held (15). 20 + 10 + 10 + 10 + 15 = 65." }, "scores": { "a": 57, "b": 65 } }, { "by": 7, "category": "ergonomics", "leads": "gladia-stt", "name": "Agent ergonomics", "reasons": { "a": "API reading, as for the other speech-to-text listings. The transcript is compact, text, detected languages, audio duration and model metadata, with no word array to trim; on an MCP reading five tools would score 25 (20 of 25). Nothing to page through and no output options, no timestamps, subtitles or speaker labels, and recorded input must be PCM16 mono 16 kHz WAV, so the caller converts everything else; a 12-hour recording goes up in one request (10 of 20). Errors are structured with a type, code, message, status, request ID and parameter, and the reference says what each status means and what to do after a 504, but no list of code values was found and the SDK error classes expose only the status and the raw body (13 of 20). Upload retries are left to the caller with clear rules, read the generation first and never re-upload after a timeout; REST has no idempotency key and `client_request_id` is documented as no guarantee, while MCP `transcribe_audio` takes an `idempotency_key`. The SDKs never retry, and closing an unfinished live socket cancels it (13 of 20). Only the audio is required, with official Python and Node SDKs, but raw REST and MCP default to paid Fast while the SDKs default to free Batch (12 of 15). 20+10+13+13+12 = 68.", "b": "API reading of the checklist. Add-ons such as summaries, NER and translation are opt-in, so a plain request stays small, but there's no field selection (15). Pre-recorded jobs list with offset, limit and filters (20). Documented error codes, with a 429 for concurrency (15). No idempotency key. The docs warn that a job is already queued once the 200 or `transcription.created` webhook arrives, which is safe-retry guidance of a sort (10). One required parameter and official SDKs in JavaScript and Python (15). The official MCP server adds 8 tools for async jobs, which this API reading doesn't score." }, "scores": { "a": 68, "b": 75 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Giggy", "b": "Gladia", "name": "Vendor" }, { "a": "https://api.giggy.ai/v1", "b": "https://api.gladia.io/v2", "name": "Hosted endpoint" }, { "a": "HTTP, SSE (legacy), websocket, Streamable HTTP", "b": "HTTP, stdio", "name": "Transports" }, { "a": "API key", "b": "API key", "name": "Auth" }, { "a": "Freemium", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary hosted service. The terms page draws its text by script and was not read. The Python and Node SDKs, the Pipecat adapter and the MCP repository are ISC (Copyright 2026 Giggy), the n8n node MIT", "b": "MIT (SDKs and MCP server)", "name": "Licence" }, { "a": "none", "b": "8", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "io.github.GRQDigitalCapital/giggy-mcp", "b": "not listed", "name": "MCP registry" }, { "a": "2026-11-01", "b": "2026-10-23", "name": "Last release" }, { "a": "not read yet", "b": "no date given", "name": "Terms last updated" }, { "a": "not read yet", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not read yet", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not read yet", "b": "not found in the text", "name": "Arbitration or class-action waiver" }, { "a": "none", "b": "4 stars, 4.8k npm/wk, 126k PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "3/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Gladia Speech-to-Text API + MCP scores 69.8 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category.", "question": "Which is better for AI agents, Giggy Speech to Text or Gladia Speech-to-Text API + MCP?" }, { "answer": "Both need an API key.", "question": "Do Giggy Speech to Text and Gladia Speech-to-Text API + MCP need an API key?" }, { "answer": "Yes. Giggy Speech to Text has a hosted endpoint at https://api.giggy.ai/v1 and Gladia Speech-to-Text API + MCP at https://api.gladia.io/v2.", "question": "Can an agent call Giggy Speech to Text and Gladia Speech-to-Text API + MCP without installing anything?" } ], "goodFor": [ { "aheadOn": null, "also": null, "goodFor": "Agents and voice pipelines that need plain transcripts of recorded or live speech at a few cents an hour, or free for clips under 25 minutes, and can convert audio to 16 kHz mono WAV first.", "slug": "giggy-stt", "watchFor": "Recorded input must be PCM16 mono 16 kHz WAV, so MP3, M4A, stereo or other sample rates need converting before upload" }, { "aheadOn": [ "Reliability, 70 against 50", "Schema \u0026 documentation, 95 against 68", "Agent ergonomics, 75 against 68", "Security \u0026 auth, 65 against 57", "Payments \u0026 pricing, 40 against 30", "Transparency \u0026 trust, 65 against 30" ], "also": [ "Runs on your own machine", "Free to start without a card" ], "goodFor": "Multilingual meetings and calls where live and async transcription in 100+ languages is needed, and for teams who want an MCP server.", "slug": "gladia-stt", "watchFor": "Self-serve audio is used for model training by default unless the account opts out" } ], "history": { "giggy-stt": null, "gladia-stt": [ { "causes": [ "terms", "correction" ], "date": "2026-11-01", "delta": 0.2, "from": 69.6, "fromGrade": "B", "to": 69.8, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.1, "from": 69.5, "fromGrade": "B", "to": 69.6, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.2, "from": 69.7, "fromGrade": "B", "to": 69.5, "toGrade": "B" } ] }, "job": { "capability": "speech.stt", "name": "Speech-to-text" }, "others": [ { "json": "https://www.anchorterminal.com/compare/amazon-transcribe-vs-giggy-stt.json", "title": "Amazon Transcribe vs Giggy Speech to Text", "url": "https://www.anchorterminal.com/compare/amazon-transcribe-vs-giggy-stt" }, { "json": "https://www.anchorterminal.com/compare/amazon-transcribe-vs-gladia-stt.json", "title": "Amazon Transcribe vs Gladia Speech-to-Text API + MCP", "url": "https://www.anchorterminal.com/compare/amazon-transcribe-vs-gladia-stt" }, { "json": "https://www.anchorterminal.com/compare/assemblyai-stt-vs-giggy-stt.json", "title": "AssemblyAI Speech-to-Text (Universal) vs Giggy Speech to Text", "url": "https://www.anchorterminal.com/compare/assemblyai-stt-vs-giggy-stt" }, { "json": "https://www.anchorterminal.com/compare/assemblyai-stt-vs-gladia-stt.json", "title": "AssemblyAI Speech-to-Text (Universal) vs Gladia Speech-to-Text API + MCP", "url": "https://www.anchorterminal.com/compare/assemblyai-stt-vs-gladia-stt" }, { "json": "https://www.anchorterminal.com/compare/azure-speech-to-text-vs-giggy-stt.json", "title": "Azure AI Speech speech-to-text vs Giggy Speech to Text", "url": "https://www.anchorterminal.com/compare/azure-speech-to-text-vs-giggy-stt" }, { "json": "https://www.anchorterminal.com/compare/azure-speech-to-text-vs-gladia-stt.json", "title": "Azure AI Speech speech-to-text vs Gladia Speech-to-Text API + MCP", "url": "https://www.anchorterminal.com/compare/azure-speech-to-text-vs-gladia-stt" }, { "json": "https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-giggy-stt.json", "title": "Cartesia Ink vs Giggy Speech to Text", "url": "https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-giggy-stt" }, { "json": "https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-gladia-stt.json", "title": "Cartesia Ink vs Gladia Speech-to-Text API + MCP", "url": "https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-gladia-stt" }, { "json": "https://www.anchorterminal.com/compare/deepgram-stt-vs-giggy-stt.json", "title": "Deepgram Speech-to-Text (Nova-3, Flux) vs Giggy Speech to Text", "url": "https://www.anchorterminal.com/compare/deepgram-stt-vs-giggy-stt" }, { "json": "https://www.anchorterminal.com/compare/deepgram-stt-vs-gladia-stt.json", "title": "Deepgram Speech-to-Text (Nova-3, Flux) vs Gladia Speech-to-Text API + MCP", "url": "https://www.anchorterminal.com/compare/deepgram-stt-vs-gladia-stt" }, { "json": "https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-giggy-stt.json", "title": "ElevenLabs Scribe Speech to Text API vs Giggy Speech to Text", "url": "https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-giggy-stt" }, { "json": "https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-gladia-stt.json", "title": "ElevenLabs Scribe Speech to Text API vs Gladia Speech-to-Text API + MCP", "url": "https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-gladia-stt" }, { "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text.json", "title": "Giggy Speech to Text vs Google Cloud Speech-to-Text", "url": "https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text" }, { "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-groq-speech-to-text.json", "title": "Giggy Speech to Text vs Groq Speech-to-Text", "url": "https://www.anchorterminal.com/compare/giggy-stt-vs-groq-speech-to-text" }, { "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-mistral-voxtral-transcribe.json", "title": "Giggy Speech to Text vs Mistral Voxtral Transcribe", "url": "https://www.anchorterminal.com/compare/giggy-stt-vs-mistral-voxtral-transcribe" }, { "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-openai-speech-to-text.json", "title": "Giggy Speech to Text vs OpenAI Speech to Text", "url": "https://www.anchorterminal.com/compare/giggy-stt-vs-openai-speech-to-text" }, { "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-rev-ai-stt.json", "title": "Giggy Speech to Text vs Rev AI Speech-to-Text API", "url": "https://www.anchorterminal.com/compare/giggy-stt-vs-rev-ai-stt" }, { "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-soniox-stt.json", "title": "Giggy Speech to Text vs Soniox Speech-to-Text", "url": "https://www.anchorterminal.com/compare/giggy-stt-vs-soniox-stt" }, { "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-speechmatics-stt.json", "title": "Giggy Speech to Text vs Speechmatics Speech-to-Text", "url": "https://www.anchorterminal.com/compare/giggy-stt-vs-speechmatics-stt" }, { "json": "https://www.anchorterminal.com/compare/gladia-stt-vs-google-speech-to-text.json", "title": "Gladia Speech-to-Text API + MCP vs Google Cloud Speech-to-Text", "url": "https://www.anchorterminal.com/compare/gladia-stt-vs-google-speech-to-text" }, { "json": "https://www.anchorterminal.com/compare/gladia-stt-vs-groq-speech-to-text.json", "title": "Gladia Speech-to-Text API + MCP vs Groq Speech-to-Text", "url": "https://www.anchorterminal.com/compare/gladia-stt-vs-groq-speech-to-text" }, { "json": "https://www.anchorterminal.com/compare/gladia-stt-vs-mistral-voxtral-transcribe.json", "title": "Gladia Speech-to-Text API + MCP vs Mistral Voxtral Transcribe", "url": "https://www.anchorterminal.com/compare/gladia-stt-vs-mistral-voxtral-transcribe" }, { "json": "https://www.anchorterminal.com/compare/gladia-stt-vs-openai-speech-to-text.json", "title": "Gladia Speech-to-Text API + MCP vs OpenAI Speech to Text", "url": "https://www.anchorterminal.com/compare/gladia-stt-vs-openai-speech-to-text" }, { "json": "https://www.anchorterminal.com/compare/gladia-stt-vs-rev-ai-stt.json", "title": "Gladia Speech-to-Text API + MCP vs Rev AI Speech-to-Text API", "url": "https://www.anchorterminal.com/compare/gladia-stt-vs-rev-ai-stt" }, { "json": "https://www.anchorterminal.com/compare/gladia-stt-vs-soniox-stt.json", "title": "Gladia Speech-to-Text API + MCP vs Soniox Speech-to-Text", "url": "https://www.anchorterminal.com/compare/gladia-stt-vs-soniox-stt" }, { "json": "https://www.anchorterminal.com/compare/gladia-stt-vs-speechmatics-stt.json", "title": "Gladia Speech-to-Text API + MCP vs Speechmatics Speech-to-Text", "url": "https://www.anchorterminal.com/compare/gladia-stt-vs-speechmatics-stt" } ], "panel": null, "scores": [ { "by": 20, "edge": "gladia-stt", "giggy-stt": 50, "gladia-stt": 70, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 27, "edge": "gladia-stt", "giggy-stt": 68, "gladia-stt": 95, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 7, "edge": "gladia-stt", "giggy-stt": 68, "gladia-stt": 75, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 8, "edge": "gladia-stt", "giggy-stt": 57, "gladia-stt": 65, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 10, "edge": "gladia-stt", "giggy-stt": 30, "gladia-stt": 40, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 1, "edge": "gladia-stt", "giggy-stt": 69, "gladia-stt": 70, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 35, "edge": "gladia-stt", "giggy-stt": 30, "gladia-stt": 65, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Gladia Speech-to-Text API + MCP scores 69.8 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category. Both do speech-to-text.", "tasks": null, "tutorials": [], "verdicts": { "giggy-stt": "Fast transcription costs $0.04 an input audio hour and Batch is free up to 25 minutes, with published rate limits, Retry-After and a rule to check a generation before resubmitting. Input must be 16 kHz mono WAV, there are no timestamps or speaker labels, the status page covers text-to-speech only, and no company is named on pages we could read.", "gladia-stt": "The `solaria-1` model transcribes live and recorded audio in over 100 languages with code switching, behind an OpenAPI file and SDKs in two languages. Self-serve audio is used for model training unless the account opts out, and Gladia's pages disagree on retention and training defaults." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt", "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt.min.md" }, "markdown": "Gladia Speech-to-Text API + MCP scores 69.8 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category. Both do speech-to-text.\n\n- Giggy Speech to Text: grade C, 54.5/100, rank #806 of 1349. Markdown https://www.anchorterminal.com/tools/giggy-stt.md · JSON https://www.anchorterminal.com/api/v1/tools/giggy-stt.json\n- Gladia Speech-to-Text API + MCP: grade B, 69.8/100, rank #205 of 1349. Markdown https://www.anchorterminal.com/tools/gladia-stt.md · JSON https://www.anchorterminal.com/api/v1/tools/gladia-stt.json\n- Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md\n- All 253 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md\n\n## Which one, for what\n\n### Giggy Speech to Text (C)\n\nGood for: Agents and voice pipelines that need plain transcripts of recorded or live speech at a few cents an hour, or free for clips under 25 minutes, and can convert audio to 16 kHz mono WAV first.\n\nWatch for: Recorded input must be PCM16 mono 16 kHz WAV, so MP3, M4A, stereo or other sample rates need converting before upload\n\n### Gladia Speech-to-Text API + MCP (B)\n\nGood for: Multilingual meetings and calls where live and async transcription in 100+ languages is needed, and for teams who want an MCP server.\n\nAhead on:\n- Reliability, 70 against 50\n- Schema \u0026 documentation, 95 against 68\n- Agent ergonomics, 75 against 68\n- Security \u0026 auth, 65 against 57\n- Payments \u0026 pricing, 40 against 30\n- Transparency \u0026 trust, 65 against 30\n\nAlso in its favour:\n- Runs on your own machine\n- Free to start without a card\n\nWatch for: Self-serve audio is used for model training by default unless the account opts out\n\n\n## Why the edge\n\n### Transparency \u0026 trust: Gladia Speech-to-Text API + MCP +35\n\n- Giggy Speech to Text (30): Closed hosted service. The terms exist at /terms but draw by script and could not be read, so their clarity is unknown; the SDK, Pipecat and MCP repositories are ISC and the n8n node MIT (5 of 30). What could be read agrees with itself, no training on user data, an optional 12-hour retention flag, a seven-day window for Batch audio, and the EEA compute flag. The privacy policy, any DPA and a retention period for transcripts were not found or not readable (12 of 30). No deprecation policy or dated notices, only a statement that the legacy origin remains supported (3 of 20). No subprocessors or data locations are named; the EEA-adequate compute option implies processing outside the EEA by default without saying where (3 of 20). 5+12+3+3 = 23.\n- Gladia Speech-to-Text API + MCP (65): Closed service with an MIT SDK and MCP server and separate terms for Gladia SAS and Gladia Inc. (15). The statements disagree. The security page gives a 12-month default retention with custom policies for customers and says only Free plan data trains models, while the retention page gives 1 year on free, 3 weeks on paid and zero retention only on Enterprise, and the pricing page says Self-serve is opted in to training by default. ISO 27001 is described as in progress (15). Breaking changes are flagged with dates in the changelog, such as SDK 2.0.0 and the move to credit billing on 3 July 2026 with a 6 to 20 July rollout, but no deprecation policy was found (10). Hosting with a French provider is stated, and no sub-processor list was found (10).\n\n### Schema \u0026 documentation: Gladia Speech-to-Text API + MCP +27\n\n- Giggy Speech to Text (68): Model reading, with the API reference. The docs and llms.txt link an OpenAPI 3.1 file at https://api.giggy.ai/v1/openapi.json, but api.giggy.ai's robots.txt could not be read, so the file wasn't fetched. We credit only what the reference pages show of it, typed `mode` values, the privacy booleans and a typed error body, and there is no AsyncAPI file for the live socket (12 of 25). llms.txt and llms-full.txt (10). The docs say when to use each mode and transport, that MCP is not a live transport, that an OpenAI base-URL swap does not work for STT, and which options have no equivalent, more than most listings say about when not to use something (17 of 20). `mode` is an enum of three values and the input format is fixed, but `language` is a free code or name with no published list, and the MCP input schemas were read only from the repository's docs, not from the server (11 of 15). Examples in the SDK READMEs, the examples repository and a Postman collection, and an error table of ten statuses with `type`, `code`, `message`, `status`, `request_id` and `param` fields, though only one code value is named (11 of 15). Paths are under `/v1` and the SDK and Pipecat repositories keep CHANGELOG.md files, dated in two of them, but there is no service changelog (7 of 15). 12+10+17+11+11+7 = 68.\n- Gladia Speech-to-Text API + MCP (95): OpenAPI file at api.gladia.io/openapi.json (25). llms.txt (10). Reference pages state purpose per endpoint and the model page says to use `solaria-3` only for async English, French, German, Spanish or Italian (15). Typed bodies with enums and required fields, `audio_url` the only required input for pre-recorded (15). Examples per endpoint and documented error codes (15). Versioned `/v2` paths and a dated changelog (15).\n\n### Reliability: Gladia Speech-to-Text API + MCP +20\n\n- Giggy Speech to Text (50): Hosted reading, as for deepgram-stt and cartesia-ink-stt. Giggy's own status page at https://giggy.ai/status lists one component, Text to speech, operational on 4 November 2026 with 98.61 per cent observed availability and 99.85 per cent completion over 14 days, refreshed every 30 minutes. It has no speech-to-text component and no incident log, so it shows nothing about this surface (5 of 20). No readable incident history, so the floor (5). Rate limits are published per credential, 60 Batch generation POSTs, 120 event-stream GETs, 600 reads and 120 MCP requests a minute, with eight live contexts per controller; Fast and Streaming POSTs have no per-credential limit and Batch queue capacity isn't given (15). 429 carries `Retry-After` with `RateLimit-*` headers, and the docs give a safe-retry rule for uploads, read the generation by UUID after a timeout or 504 and never upload the same recording again. REST transcription has no idempotency key, but the MCP `transcribe_audio` tool takes one (15). No SLA on the pricing page or in the docs; the terms could not be read (0). No beta or preview label on the API, the SDKs or the MCP server (10). 5+5+15+15+0+10 = 50.\n- Gladia Speech-to-Text API + MCP (70): incident.io status page with per-component uptime bars and incident pages, and an RSS feed read on 1 November (20). One major incident in the 90 days from 3 August, a global Pre-Recorded and Real-Time incident on 23 September 2026 from 07:05 to 08:10 caused by a provider network fault, as read on 1 October. The rest are partial and read as minor, a 20-minute full outage and a timeouts incident on 22 September, slower processing on the afternoon of 23 September, and Europe-only degradations on 2, 10, 14 to 15 (elevated errors and timeouts in Europe from 09:07 on 14 September to 13:58 on 15 September), 21, 22 and 28 September and on 3, 4 and 7 October (Pre-Recorded v2 in Europe) (10). Concurrency limits published with numbers, 25 parallel async jobs plus 300 queued and 30 live sessions on paid plans, 3 and 1 on free (15). The docs say a 429 means the concurrency limit, but we found no backoff guidance or Retry-After (5). The pricing page's plan comparison, read on 1 November, lists a 99.9% uptime SLA for Enterprise (10). `solaria-1` and `solaria-3` are GA (10). 20 + 10 + 15 + 5 + 10 + 10 = 70.\n\n### Payments \u0026 pricing: Gladia Speech-to-Text API + MCP +10\n\n- Giggy Speech to Text (30): No x402, MPP or L402 (0). Per-hour prices for Batch, Fast and Streaming and every credit pack published without a login (20). Free Batch transcription and Personal free credits topped up to 10,000 a month, but no page read says whether a card is needed, so half, as other listings read an unstated card requirement (10 of 20). A person signs up in a browser and creates the key there; no programmatic key route was found (0). 0+20+10+0 = 30.\n- Gladia Speech-to-Text API + MCP (40): No x402, MPP or L402 (0). Per-hour prices in euros published without a login, re-read on 1 November, async from 0.27€ an hour on `solaria-1` and 0.16€ on `solaria-3`, real-time 0.68€, add-ons per hour (20). A one-time €50 credit, with no card per the 1 October check (20). A person signs up in a browser (0).\n\n### Security \u0026 auth: Gladia Speech-to-Text API + MCP +8\n\n- Giggy Speech to Text (57): Model reading of the checklist, with training and retention in place of the least-privilege and injection lines, as for deepgram-stt and cartesia-ink-stt. Keys prefixed `giggy_sk_` are shown once on creation or rotation, rejected immediately after revocation, limited to ten per space and tied to the space that made them, with REST budgets that Workspace members can set. No scopes or expiry were found. The key travels in a header only, with no query-string option documented (22 of 30). The workspace privacy guide states 'Giggy does not use user data to train models'. The privacy policy and terms draw by script and could not be read to confirm it (18 of 20). Requests can opt into 12-hour content retention and EEA-adequate compute, and a guide gives Batch audio a seven-day window, but no retention period for transcripts was found and results can vanish after an unstated 'retention cleanup' (9 of 15). Generation history per space and a request ID on errors; no audit log of key or admin actions was found (8 of 15). /.well-known/security.txt answered a client error, none of the six repositories has a SECURITY.md, and no disclosure policy, bug bounty or certification was found on the pages that rendered; the support page that may name a reporting route drew by script (0 of 20). 22+18+9+8+0 = 57.\n- Gladia Speech-to-Text API + MCP (65): Model reading of the checklist, with training and retention in place of least-privilege and injection lines. Plain revocable API keys in the `x-gladia-key` header. Live sessions connect to a WebSocket URL minted per session by `POST /v2/live`, which we don't deduct for (20). The pricing page, read on 1 November, says Self-serve, the paid pay-as-you-go plan, is opted in to model training by default with a free opt-out in the profile, and Enterprise is opted out by default. The security page still says only Free plan data is used for training. We score the pricing page's default, as for AWS's default use with an opt-out (10 of 20). Retention is documented and jobs can be deleted, but zero retention needs Enterprise per the retention page (10). Job history through the list endpoint and dashboard, no audit log of key actions found (10). SOC 2 Type 1 and Type 2, a bug bounty programme that doubles as the disclosure route, no security.txt (404 on 1 November) and no public advisories found. The SDKs fixed an API key leak on cross-origin redirects in 2.1.0 (September) and limited list pagination to the configured API in 2.2.0 (13 October), both released. ISO 27001 is in progress, not held (15). 20 + 10 + 10 + 10 + 15 = 65.\n\n### Agent ergonomics: Gladia Speech-to-Text API + MCP +7\n\n- Giggy Speech to Text (68): API reading, as for the other speech-to-text listings. The transcript is compact, text, detected languages, audio duration and model metadata, with no word array to trim; on an MCP reading five tools would score 25 (20 of 25). Nothing to page through and no output options, no timestamps, subtitles or speaker labels, and recorded input must be PCM16 mono 16 kHz WAV, so the caller converts everything else; a 12-hour recording goes up in one request (10 of 20). Errors are structured with a type, code, message, status, request ID and parameter, and the reference says what each status means and what to do after a 504, but no list of code values was found and the SDK error classes expose only the status and the raw body (13 of 20). Upload retries are left to the caller with clear rules, read the generation first and never re-upload after a timeout; REST has no idempotency key and `client_request_id` is documented as no guarantee, while MCP `transcribe_audio` takes an `idempotency_key`. The SDKs never retry, and closing an unfinished live socket cancels it (13 of 20). Only the audio is required, with official Python and Node SDKs, but raw REST and MCP default to paid Fast while the SDKs default to free Batch (12 of 15). 20+10+13+13+12 = 68.\n- Gladia Speech-to-Text API + MCP (75): API reading of the checklist. Add-ons such as summaries, NER and translation are opt-in, so a plain request stays small, but there's no field selection (15). Pre-recorded jobs list with offset, limit and filters (20). Documented error codes, with a 429 for concurrency (15). No idempotency key. The docs warn that a job is already queued once the 200 or `transcription.created` webhook arrives, which is safe-retry guidance of a sort (10). One required parameter and official SDKs in JavaScript and Python (15). The official MCP server adds 8 tools for async jobs, which this API reading doesn't score.\n\n## Score by category\n\n| Category | Weight | Giggy Speech to Text | Gladia Speech-to-Text API + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 70 | Gladia Speech-to-Text API + MCP +20 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 68 | 95 | Gladia Speech-to-Text API + MCP +27 |\n| Agent ergonomics | 13% (16.2 this run) | 68 | 75 | Gladia Speech-to-Text API + MCP +7 |\n| Security \u0026 auth | 14% (17.5 this run) | 57 | 65 | Gladia Speech-to-Text API + MCP +8 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 40 | Gladia Speech-to-Text API + MCP +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 69 | 70 | Gladia Speech-to-Text API + MCP +1 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 30 | 65 | Gladia Speech-to-Text API + MCP +35 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **54.5 · C** | **69.8 · B** | |\n\n## Facts side by side\n\n| Fact | Giggy Speech to Text | Gladia Speech-to-Text API + MCP |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Giggy | Gladia |\n| Hosted endpoint | `https://api.giggy.ai/v1` | `https://api.gladia.io/v2` |\n| Transports | HTTP, SSE (legacy), websocket, Streamable HTTP | HTTP, stdio |\n| Auth | API key | API key |\n| Pricing | Freemium | Freemium |\n| x402 | no | no |\n| Licence | Proprietary hosted service. The terms page draws its text by script and was not read. The Python and Node SDKs, the Pipecat adapter and the MCP repository are ISC (Copyright 2026 Giggy), the n8n node MIT | MIT (SDKs and MCP server) |\n| Tools exposed | none | 8 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| MCP registry | `io.github.GRQDigitalCapital/giggy-mcp` | not listed |\n| Last release | 2026-11-01 | 2026-10-23 |\n| Terms last updated | not read yet | no date given |\n| Privacy policy last updated | not read yet | no date given |\n| Customer content may train models | not read yet | not found in the text |\n| Terms restrict automated access | not read yet | not found in the text |\n| Terms restrict benchmarking | not read yet | not found in the text |\n| Terms or service can change without notice | not read yet | not found in the text |\n| Arbitration or class-action waiver | not read yet | not found in the text |\n| Popularity | none | 4 stars, 4.8k npm/wk, 126k PyPI/wk |\n| Agent reviews | none | 3/5 (2) |\n\n## How the scores have moved\n\n### Giggy Speech to Text\n\nNo score change since it was listed.\n\n### Gladia Speech-to-Text API + MCP\n\n- +0.2 on 1 November 2026: terms, correction\n- +0.1 on 27 October 2026: checklist\n- -0.2 on 8 October 2026: checklist\n\n## Verdicts\n\n**Giggy Speech to Text.** Fast transcription costs $0.04 an input audio hour and Batch is free up to 25 minutes, with published rate limits, Retry-After and a rule to check a generation before resubmitting. Input must be 16 kHz mono WAV, there are no timestamps or speaker labels, the status page covers text-to-speech only, and no company is named on pages we could read.\n\n**Gladia Speech-to-Text API + MCP.** The `solaria-1` model transcribes live and recorded audio in over 100 languages with code switching, behind an OpenAPI file and SDKs in two languages. Self-serve audio is used for model training unless the account opts out, and Gladia's pages disagree on retention and training defaults.\n\n## Before you call either\n\n### Giggy Speech to Text\n\n1. Pass `mode=batch` explicitly for free transcription. Raw REST and MCP default to paid Fast when `mode` is omitted.\n2. Convert audio to PCM16 mono 16 kHz WAV first and send it as the raw body with `Content-Type: audio/wav`.\n3. Keep the `generation_uuid` from the 202 and poll `GET /v1/generations/{uuid}`. Never re-upload after a timeout or 504 before reading that generation.\n4. Fetch the transcript from the signed `generation.result.url` after completion, without the API key. It can disappear after retention cleanup.\n5. On the live WebSocket, replace earlier text with each cumulative `transcription` event and publish final text only after `input_complete`.\n\n### Gladia Speech-to-Text API + MCP\n\n1. Don't resubmit a pre-recorded job after a 200 or a `transcription.created` webhook. It's already queued\n2. Pick `solaria-3` only for async EN, FR, DE, ES or IT audio. Anything live or multilingual needs `solaria-1`\n3. A 429 means the concurrency limit, 3 async and 1 live on the free plan. Wait for a running job to finish\n4. Opt the account out of model training in its profile before sending sensitive audio on Self-serve\n5. Split files over 135 minutes or 1,000 MB\n\n## Questions\n\n### Which is better for AI agents, Giggy Speech to Text or Gladia Speech-to-Text API + MCP?\n\nGladia Speech-to-Text API + MCP scores 69.8 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category.\n\n### Do Giggy Speech to Text and Gladia Speech-to-Text API + MCP need an API key?\n\nBoth need an API key.\n\n### Can an agent call Giggy Speech to Text and Gladia Speech-to-Text API + MCP without installing anything?\n\nYes. Giggy Speech to Text has a hosted endpoint at https://api.giggy.ai/v1 and Gladia Speech-to-Text API + MCP at https://api.gladia.io/v2.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt.json, and with the fewest tokens: https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"giggy-stt\", \"b\": \"gladia-stt\"}`. From a terminal: `anchor compare giggy-stt gladia-stt`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/giggy-stt.json and https://www.anchorterminal.com/api/v1/tools/gladia-stt.json\n\n## Other comparisons with Giggy Speech to Text or Gladia Speech-to-Text API + MCP\n\n- [Amazon Transcribe vs Giggy Speech to Text](https://www.anchorterminal.com/compare/amazon-transcribe-vs-giggy-stt.md)\n- [Amazon Transcribe vs Gladia Speech-to-Text API + MCP](https://www.anchorterminal.com/compare/amazon-transcribe-vs-gladia-stt.md)\n- [AssemblyAI Speech-to-Text (Universal) vs Giggy Speech to Text](https://www.anchorterminal.com/compare/assemblyai-stt-vs-giggy-stt.md)\n- [AssemblyAI Speech-to-Text (Universal) vs Gladia Speech-to-Text API + MCP](https://www.anchorterminal.com/compare/assemblyai-stt-vs-gladia-stt.md)\n- [Azure AI Speech speech-to-text vs Giggy Speech to Text](https://www.anchorterminal.com/compare/azure-speech-to-text-vs-giggy-stt.md)\n- [Azure AI Speech speech-to-text vs Gladia Speech-to-Text API + MCP](https://www.anchorterminal.com/compare/azure-speech-to-text-vs-gladia-stt.md)\n- [Cartesia Ink vs Giggy Speech to Text](https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-giggy-stt.md)\n- [Cartesia Ink vs Gladia Speech-to-Text API + MCP](https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-gladia-stt.md)\n- [Deepgram Speech-to-Text (Nova-3, Flux) vs Giggy Speech to Text](https://www.anchorterminal.com/compare/deepgram-stt-vs-giggy-stt.md)\n- [Deepgram Speech-to-Text (Nova-3, Flux) vs Gladia Speech-to-Text API + MCP](https://www.anchorterminal.com/compare/deepgram-stt-vs-gladia-stt.md)\n- [ElevenLabs Scribe Speech to Text API vs Giggy Speech to Text](https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-giggy-stt.md)\n- [ElevenLabs Scribe Speech to Text API vs Gladia Speech-to-Text API + MCP](https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-gladia-stt.md)\n- [Giggy Speech to Text vs Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text.md)\n- [Giggy Speech to Text vs Groq Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-groq-speech-to-text.md)\n- [Giggy Speech to Text vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/giggy-stt-vs-mistral-voxtral-transcribe.md)\n- [Giggy Speech to Text vs OpenAI Speech to Text](https://www.anchorterminal.com/compare/giggy-stt-vs-openai-speech-to-text.md)\n- [Giggy Speech to Text vs Rev AI Speech-to-Text API](https://www.anchorterminal.com/compare/giggy-stt-vs-rev-ai-stt.md)\n- [Giggy Speech to Text vs Soniox Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-soniox-stt.md)\n- [Giggy Speech to Text vs Speechmatics Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-speechmatics-stt.md)\n- [Gladia Speech-to-Text API + MCP vs Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/gladia-stt-vs-google-speech-to-text.md)\n- [Gladia Speech-to-Text API + MCP vs Groq Speech-to-Text](https://www.anchorterminal.com/compare/gladia-stt-vs-groq-speech-to-text.md)\n- [Gladia Speech-to-Text API + MCP vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/gladia-stt-vs-mistral-voxtral-transcribe.md)\n- [Gladia Speech-to-Text API + MCP vs OpenAI Speech to Text](https://www.anchorterminal.com/compare/gladia-stt-vs-openai-speech-to-text.md)\n- [Gladia Speech-to-Text API + MCP vs Rev AI Speech-to-Text API](https://www.anchorterminal.com/compare/gladia-stt-vs-rev-ai-stt.md)\n- [Gladia Speech-to-Text API + MCP vs Soniox Speech-to-Text](https://www.anchorterminal.com/compare/gladia-stt-vs-soniox-stt.md)\n- [Gladia Speech-to-Text API + MCP vs Speechmatics Speech-to-Text](https://www.anchorterminal.com/compare/gladia-stt-vs-speechmatics-stt.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-04", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Giggy Speech to Text vs Gladia Speech-to-Text API + MCP", "url": "" } ], "description": "Gladia Speech-to-Text scores 69.8 (B) to Giggy Speech to Text's 54.5 (C) for speech-to-text. 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