{ "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": "Google Cloud Speech-to-Text scores 66.6 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in 5 of 7 scored categories. Giggy Speech to Text leads on payments \u0026 pricing and maintenance \u0026 community.", "b": { "slug": "google-speech-to-text", "name": "Google Cloud Speech-to-Text", "vendor": "Google Cloud", "vendorUrl": "https://cloud.google.com/speech-to-text", "kind": "model", "category": "speech-to-text", "summary": "Google Cloud's transcription API.", "url": "https://www.anchorterminal.com/tools/google-speech-to-text", "markdownUrl": "https://www.anchorterminal.com/tools/google-speech-to-text.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/google-speech-to-text.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/google-speech-to-text.json", "dns": "google-speech-to-text.grade.anchorterminal.com", "repo": "https://github.com/googleapis/google-cloud-python/tree/main/packages/google-cloud-speech", "license": "Apache-2.0 (SDKs)", "transports": [ "http" ], "remoteUrl": "https://speech.googleapis.com/v2", "packages": [ { "registry": "pypi", "name": "google-cloud-speech" }, { "registry": "npm", "name": "@google-cloud/speech" } ], "auth": "oauth", "authNotes": "OAuth 2.0 bearer token from a service account or `gcloud` (Application Default Credentials) on a project with billing and the API turned on. Chirp 3 runs on the `us` and `eu` multi-region endpoints such as `us-speech.googleapis.com`.", "pricing": "freemium", "pricingNotes": "V2 standard recognition, which covers Chirp 3, is $0.016 a minute to 500,000 minutes a month, then $0.01, $0.008 and $0.004 past 2M. Dynamic batch is $0.003 a minute. Billed per second, per channel. V1 has 60 free minutes a month and charges $0.024 without data logging. Medical models $0.078 (https://cloud.google.com/speech-to-text/pricing).", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. Billing runs through a cloud account with a card or invoice.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 713013, "pypiWeekly": 3703632, "asOf": "2026-09-30" }, "docsUrl": "https://docs.cloud.google.com/speech-to-text/docs", "capabilities": [ "speech.stt", "speech.streaming", "speech.batch", "speech.diarisation", "speech.languages", "speech.translation" ], "tags": [ "hosted", "freemium", "closed-source", "python", "typescript", "enterprise", "streaming", "batch", "async-jobs", "card-required" ], "lastRelease": "2026-10-01", "graded": true, "anchor": { "graded": true, "score": 66.6, "grade": "B", "agentReady": false, "rank": 330, "ranked": true, "rankOf": 1349, "categoryRank": 12, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 70, "maintenance": 25, "payments": 20, "reliability": 75, "schema": 80, "security": 85, "transparency": 87 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-01" }, "negative": 0, "verdict": "Audio isn't stored or used for training unless the project opts in to data logging. No release note since 2025-11-13.", "bestFor": "Google Cloud teams with audio already in Cloud Storage who want no training and no retention by default.", "strengths": [ "Audio isn't stored or used for training unless the project opts in to data logging", "Only one Speech-to-Text incident on the Google Cloud status page since June 2025, confined to europe-west2 on 20 October 2026", "Dynamic batch at $0.003 a minute, and standard recognition tiers down to $0.004 past 2M minutes", "OAuth service accounts with IAM roles, and Cloud Audit Logs", "300 concurrent streams per region by default" ], "weaknesses": [ "No release note since 2025-11-13", "The OAuth token is accepted in the `access_token` query string, where it can end up in logs", "Sync requests stop at 1 minute and streams at 5 minutes, and batch reads only from Cloud Storage", "No API keys in the documented V2 flow, and the free minutes need a billed project", "The quotas page doesn't say what error a breach returns or how to back off" ], "agentNotes": [ "Call Chirp 3 on the `us` or `eu` endpoint. It isn't listed for the `global` location", "Reopen streams before the 5-minute limit, or use `BatchRecognize` for recordings", "Downmix stereo unless you need channel labels, since each channel is billed", "Set dynamic batch on offline jobs to cut the price from $0.016 to $0.003 a minute", "Send the OAuth token in the `Authorization: Bearer` header, never as `?access_token=`, and back off on `RESOURCE_EXHAUSTED`" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 66.6 } ], "editorialScores": { "ergonomics": 70, "maintenance": 25, "payments": 20, "reliability": 75, "schema": 80, "security": 85, "transparency": 75 }, "provenanceScore": 98, "checked": { "categories": { "ergonomics": "2026-11-01", "maintenance": "2026-11-01", "payments": "2026-11-01", "reliability": "2026-11-01", "schema": "2026-11-01", "security": "2026-11-01", "transparency": "2026-11-01" }, "last": "2026-11-01", "lastMoved": "2026-11-01", "oldest": "2026-11-01", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install google-cloud-speech # or: npm i @google-cloud/speech", "http": "curl -X POST \"https://us-speech.googleapis.com/v2/projects/$GOOGLE_CLOUD_PROJECT/locations/us/recognizers/_:recognize\" \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" -H \"content-type: application/json\" \\\n -d '{\"config\":{\"model\":\"chirp_3\",\"languageCodes\":[\"en-US\"],\"autoDecodingConfig\":{}},\"uri\":\"gs://cloud-samples-data/speech/brooklyn_bridge.flac\"}'" }, "letme": { "capability": "https://letme.dev/speech.stt", "tool": "https://letme.dev/google-speech-to-text" }, "sameCompany": [ "gemini-api", "gemini-embedding", "vertex-ai-tuning", "google-model-armor", "google-imagen", "google-veo", "google-lyria", "gemini-live", "google-adk", "google-secret-manager", "google-cloud-document-ai", "google-weather-api", "chrome-devtools-mcp", "google-maps-platform", "google-cloud-translation", "google-calendar-api", "firebase-cloud-messaging", "google-drive-api", "gemini-enterprise", "gemini-cli", "google-search-console", "google-ads-api", "google-forms", "google-sheets-api", "gmail-api", "google-people-api" ], "area": "voice", "unitPrices": [ { "item": "V2 standard recognition (Chirp 3)", "unit": "audio-minute", "usd": 0.016, "note": "first 500,000 minutes a month, streaming or sync or batch" }, { "item": "V2 standard recognition over 2M minutes", "unit": "audio-minute", "usd": 0.004 }, { "item": "V2 dynamic batch", "unit": "audio-minute", "usd": 0.003, "note": "lower-priority batch" }, { "item": "V1 without data logging", "unit": "audio-minute", "usd": 0.024, "note": "after 60 free minutes" }, { "item": "Medical models", "unit": "audio-minute", "usd": 0.078 } ], "provenance": { "legalEntity": "Google LLC", "domain": "google.com", "domainRegistered": "1997-09-15", "domainNote": "The endpoint is on googleapis.com, Google's API domain. google.com was registered in 1997.", "endpointOnVendorDomain": true, "terms": "https://cloud.google.com/terms", "privacy": "https://policies.google.com/privacy", "statusPage": "https://status.cloud.google.com", "changelog": "https://docs.cloud.google.com/speech-to-text/docs/release-notes", "securityTxt": "valid", "checked": "2026-09-30", "score": 98 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/google-speech-to-text.json", "live": { "slug": "google-speech-to-text", "probe": { "target": "https://speech.googleapis.com/v2", "method": "get", "lastAt": "2026-11-04T21:39:25.329544023Z", "lastOk": true, "lastStatus": 404, "lastMs": 36, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 51, "p95ms24h": 107, "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": 272 }, { "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": 249 }, { "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 } ] }, "vendorStatus": { "page": "https://status.cloud.google.com", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-09-30T22:44:37.367865472Z" }, "versions": [ { "registry": "github", "name": "googleapis/google-cloud-python", "version": "google-auth-v2.62.1", "released": "2026-11-03", "seenAt": "2026-11-04T20:19:57.341938798Z" }, { "registry": "npm", "name": "@google-cloud/speech", "version": "8.2.1", "seenAt": "2026-11-04T20:19:56.530208244Z" }, { "registry": "pypi", "name": "google-cloud-speech", "version": "2.41.0", "released": "2026-10-01", "seenAt": "2026-11-04T20:19:56.335018149Z" } ], "githubStars": 5415, "npmWeekly": 910431, "pypiWeekly": 3384724, "securityTxt": { "url": "https://google.com/.well-known/security.txt", "state": "valid", "expires": "2030-04-01T00:00:00z", "checkedAt": "2026-11-04T15:53:07.646035261Z" }, "domain": { "domain": "google.com", "registered": "1997-09-15", "source": "https://rdap.verisign.com/com/v1/domain/google.com", "checkedAt": "2026-11-01T14:17:18.719851913Z" }, "pages": [ { "url": "https://docs.cloud.google.com/speech-to-text/docs/release-notes", "kind": "changelog", "status": 200, "checkedAt": "2026-11-04T08:20:40.004127323Z", "changedAt": "2026-11-02T07:13:57.009045741Z", "fingerprint": "814f7d976ad5" }, { "url": "https://cloud.google.com/speech-to-text/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-04T08:16:48.353412875Z", "changedAt": "2026-10-16T22:18:48.721763382Z", "fingerprint": "1d237481fe79" }, { "url": "https://cloud.google.com/terms", "kind": "terms", "status": 200, "checkedAt": "2026-10-01T13:11:34.992628421Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "6798e0f4fb24" } ], "github": { "repo": "googleapis/google-cloud-python", "checkedAt": "2026-11-02T08:52:16.502690608Z", "stars": 5418, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-31T03:25:43Z", "openIssues": 466, "openPRs": 174, "issuesOpened90d": 124, "issuesClosed90d": 123, "prsMerged90d": 544, "ci": { "branch": "main", "runs": 50, "success": 50, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-10-30T19:55:00Z" }, "replies": { "sampled": 25, "unanswered": 23, "medianDays": 4 } }, "updatedAt": "2026-11-04T21:39:25.329544023Z" } }, "edges": [ { "by": 57, "category": "transparency", "leads": "google-speech-to-text", "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 under the Google Cloud terms (15). The data logging page, the terms and the privacy notice agree that audio isn't used for training without opt-in, and a data processing addendum and sub-processor list exist (25). Google Cloud's terms carry a notice period before a GA capability is discontinued, but we found no dated Speech-to-Text deprecation notices (15). `us` and `eu` multi-region endpoints and a public sub-processor list (20)." }, "scores": { "a": 30, "b": 87 } }, { "by": 44, "category": "maintenance", "leads": "giggy-stt", "name": "Maintenance \u0026 community", "reasons": { "a": "Read as a model, on the lines deepgram-stt and cartesia-ink-stt use (recency 30, dated releases 10, deprecation notice 10, support 15, issues 10, SDKs 15, health 10). The Python and Node SDKs released 0.2.1 and the Pipecat adapter 0.3.3 on 1 November 2026, and the examples and MCP repositories changed on 3 November (30). Since 7 October the Node SDK has four tagged releases, the Python SDK six and the Pipecat adapter six, the STT ones from 12 October (10). No deprecation policy or dated notice. The legacy `https://giggy.ai/v1` origin and older SDK transports are kept 'for existing integrations' with no end date (2 of 10). No service changelog; the support and contact pages drew by script, and GitHub issues is the support URL in the plugin manifest (5 of 15). GitHub issues and reply times could not be read, since the GitHub API was not available to this session (0 of 10). Official SDKs current, `giggy` and `@giggy-ai/sdk` at 0.2.1 on PyPI and npm (15). CI workflows in five repositories and publish workflows, the n8n node through npm OIDC with provenance, and two runtime dependencies in each SDK; run results not seen (7 of 10). 30+10+2+5+0+15+7 = 69.", "b": "The newest release note is still 2025-11-13, Chirp 3 preview in four more regions (page last updated 26 October 2026), 353 days ago (0). In the 90 days from 3 August we counted no release note and one Python client release, google-cloud-speech 2.41.0 on 1 October, whose only change is declaring Python 3.15 support. A release that doesn't change the service counts half on the 90-day line and can't set the recency line, so neither line moves (0). The last client release that touched the API was 2.37.0 on 26 February 2026 (endpointing sensitivity for streaming). Release notes, a public issue tracker and paid support (10). Official client libraries in seven or more languages (10). Package CI not checked (5). 0 + 0 + 10 + 10 + 5 = 25." }, "scores": { "a": 69, "b": 25 } }, { "by": 28, "category": "security", "leads": "google-speech-to-text", "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. OAuth 2.0 with service accounts and IAM roles, scoped per project, no API key in the documented V2 flow. The token can also travel in the URL. Google's OAuth guide accepts it as an `access_token` query parameter, the V2 discovery document (revision 20261001) lists `access_token`, `oauth_token` and `key` as query parameters, and on 1 November `speech.googleapis.com/v2/projects/example-project/locations/global/recognizers` answered 401 \"missing required authentication credential\" with no token and 401 \"invalid authentication credentials\" with a made-up `?access_token=`, so the token is read from the query string. That takes the 10-point deduction, as every Google API listing does in this run (Gmail, Sheets, Drive and Calendar on 17 October, Ads, Model Armor, Secret Manager and Document AI on 1 November) (20). Audio isn't used for training unless the project opts in to data logging (20). Streaming and sync audio is processed in memory and not stored, and batch results are kept for a short window (15). Cloud Audit Logs cover Google Cloud APIs, though we didn't confirm which Speech methods they record (10). Valid security.txt, Google's vulnerability reward programme, SOC 2 and ISO 27001, and public Cloud security bulletins (20). 20 + 20 + 15 + 10 + 20 = 85." }, "scores": { "a": 57, "b": 85 } }, { "by": 25, "category": "reliability", "leads": "google-speech-to-text", "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": "Google Cloud status page with a per-product history (20). One incident lists Speech-to-Text in the 90 days from 3 August, the europe-west2 incident of 20 October, 06:00 to 12:08 UTC, which named 38 products in that one region. A single-region incident is partial and read as minor, as this run reads partial incidents. The other three Google Cloud incidents since 3 August (20 August, 1 September, 8 and 9 October) don't list Speech-to-Text. The public page only shows broad incidents. Minor only (20). Quotas published with numbers, 300 concurrent streams, 300 sync and 150 batch requests a minute per region, streams up to 5 minutes and sync up to 1 minute (15). The Speech quotas page (last updated 26 October 2026) still says nothing about the error a quota breach returns or how to back off, and we don't count Google's general API design guide for this API (0). Speech-to-Text SLA of 99.9 per cent monthly uptime with credits of 10 to 50 per cent, per the 1 October check, not re-read on 1 November (10). Chirp 3 GA since 2025-10-13 in `us` and `eu`, though 82 of its 111 locales were preview on 1 October (10). 20 + 20 + 15 + 0 + 10 + 10 = 75." }, "scores": { "a": 50, "b": 75 } }, { "by": 12, "category": "schema", "leads": "google-speech-to-text", "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": "The API surface is public as protocol buffers and a discovery document, a machine-readable contract (25). No llms.txt found (0). Method descriptions state purpose, and the model pages say which model suits which audio, but not when to avoid sync or streaming (15). Typed proto messages with enums and required fields, no free-form blobs (15). Errors follow Google's standard status codes, with samples in the docs but little per-method error detail (10). Versioned v1 and v2 with release notes (15). The V2 discovery document read on 1 November is revision 20261001, with 26 methods and 69 schemas." }, "scores": { "a": 68, "b": 80 } }, { "by": 10, "category": "payments", "leads": "giggy-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-minute prices with volume tiers published without a login (20). The 60 free V1 minutes and the $300 new-account credit both need a billing account with a card (0). A person signs up in a browser (0)." }, "scores": { "a": 30, "b": 20 } } ], "facts": [ { "a": "Model API", "b": "Model API", "name": "Kind" }, { "a": "Giggy", "b": "Google Cloud", "name": "Vendor" }, { "a": "https://api.giggy.ai/v1", "b": "https://speech.googleapis.com/v2", "name": "Hosted endpoint" }, { "a": "HTTP, SSE (legacy), websocket, Streamable HTTP", "b": "HTTP", "name": "Transports" }, { "a": "API key", "b": "OAuth", "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": "Apache-2.0 (SDKs)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "io.github.GRQDigitalCapital/giggy-mcp", "b": "not listed", "name": "MCP registry" }, { "a": "2026-11-01", "b": "2026-10-01", "name": "Last release" }, { "a": "not read yet", "b": "2026-09-02", "name": "Terms last updated" }, { "a": "not read yet", "b": "2026-10-01", "name": "Privacy policy last updated" }, { "a": "not read yet", "b": "yes", "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": "713k npm/wk, 3.7M PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "3/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Google Cloud Speech-to-Text scores 66.6 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in 5 of 7 scored categories. Giggy Speech to Text leads on payments \u0026 pricing and maintenance \u0026 community.", "question": "Which is better for AI agents, Giggy Speech to Text or Google Cloud Speech-to-Text?" }, { "answer": "Giggy Speech to Text needs an API key. Google Cloud Speech-to-Text uses an OAuth sign-in.", "question": "Do Giggy Speech to Text and Google Cloud Speech-to-Text need an API key?" }, { "answer": "Yes. Giggy Speech to Text has a hosted endpoint at https://api.giggy.ai/v1 and Google Cloud Speech-to-Text at https://speech.googleapis.com/v2.", "question": "Can an agent call Giggy Speech to Text and Google Cloud Speech-to-Text without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Payments \u0026 pricing, 30 against 20", "Maintenance \u0026 community, 69 against 25" ], "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, 75 against 50", "Schema \u0026 documentation, 80 against 68", "Security \u0026 auth, 85 against 57", "Transparency \u0026 trust, 87 against 30" ], "also": null, "goodFor": "Google Cloud teams with audio already in Cloud Storage who want no training and no retention by default.", "slug": "google-speech-to-text", "watchFor": "No release note since 2025-11-13" } ], "history": { "giggy-stt": null, "google-speech-to-text": [ { "causes": [ "reliability", "correction" ], "date": "2026-11-01", "delta": -3.7, "from": 70.3, "fromGrade": "BB", "to": 66.6, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-27", "delta": 0.1, "from": 70.2, "fromGrade": "BB", "to": 70.3, "toGrade": "BB" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.2, "from": 70.4, "fromGrade": "BB", "to": 70.2, "toGrade": "BB" } ] }, "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-google-speech-to-text.json", "title": "Amazon Transcribe vs Google Cloud Speech-to-Text", "url": "https://www.anchorterminal.com/compare/amazon-transcribe-vs-google-speech-to-text" }, { "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-google-speech-to-text.json", "title": "AssemblyAI Speech-to-Text (Universal) vs Google Cloud Speech-to-Text", "url": "https://www.anchorterminal.com/compare/assemblyai-stt-vs-google-speech-to-text" }, { "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-google-speech-to-text.json", "title": "Azure AI Speech speech-to-text vs Google Cloud Speech-to-Text", "url": "https://www.anchorterminal.com/compare/azure-speech-to-text-vs-google-speech-to-text" }, { "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-google-speech-to-text.json", "title": "Cartesia Ink vs Google Cloud Speech-to-Text", "url": "https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-google-speech-to-text" }, { "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-google-speech-to-text.json", "title": "Deepgram Speech-to-Text (Nova-3, Flux) vs Google Cloud Speech-to-Text", "url": "https://www.anchorterminal.com/compare/deepgram-stt-vs-google-speech-to-text" }, { "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-google-speech-to-text.json", "title": "ElevenLabs Scribe Speech to Text API vs Google Cloud Speech-to-Text", "url": "https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-google-speech-to-text" }, { "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt.json", "title": "Giggy Speech to Text vs Gladia Speech-to-Text API + MCP", "url": "https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt" }, { "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/google-speech-to-text-vs-groq-speech-to-text.json", "title": "Google Cloud Speech-to-Text vs Groq Speech-to-Text", "url": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-groq-speech-to-text" }, { "json": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-mistral-voxtral-transcribe.json", "title": "Google Cloud Speech-to-Text vs Mistral Voxtral Transcribe", "url": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-mistral-voxtral-transcribe" }, { "json": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-openai-speech-to-text.json", "title": "Google Cloud Speech-to-Text vs OpenAI Speech to Text", "url": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-openai-speech-to-text" }, { "json": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-rev-ai-stt.json", "title": "Google Cloud Speech-to-Text vs Rev AI Speech-to-Text API", "url": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-rev-ai-stt" }, { "json": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-soniox-stt.json", "title": "Google Cloud Speech-to-Text vs Soniox Speech-to-Text", "url": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-soniox-stt" }, { "json": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-speechmatics-stt.json", "title": "Google Cloud Speech-to-Text vs Speechmatics Speech-to-Text", "url": "https://www.anchorterminal.com/compare/google-speech-to-text-vs-speechmatics-stt" } ], "panel": null, "scores": [ { "by": 25, "edge": "google-speech-to-text", "giggy-stt": 50, "google-speech-to-text": 75, "key": "reliability", "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 12, "edge": "google-speech-to-text", "giggy-stt": 68, "google-speech-to-text": 80, "key": "schema", "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 2, "edge": "google-speech-to-text", "giggy-stt": 68, "google-speech-to-text": 70, "key": "ergonomics", "name": "Agent ergonomics", "weight": 13 }, { "by": 28, "edge": "google-speech-to-text", "giggy-stt": 57, "google-speech-to-text": 85, "key": "security", "name": "Security \u0026 auth", "weight": 14 }, { "by": 10, "edge": "giggy-stt", "giggy-stt": 30, "google-speech-to-text": 20, "key": "payments", "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 44, "edge": "giggy-stt", "giggy-stt": 69, "google-speech-to-text": 25, "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 57, "edge": "google-speech-to-text", "giggy-stt": 30, "google-speech-to-text": 87, "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Google Cloud Speech-to-Text scores 66.6 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in 5 of 7 scored categories. Giggy Speech to Text leads on payments \u0026 pricing and maintenance \u0026 community. Both do speech-to-text.", "tasks": [ { "a": "$0.04 to $0.09", "b": "$0.18 to $4.68", "cheaper": "giggy-stt", "task": "Transcribe a one-hour meeting", "what": "60 minutes of recorded audio" } ], "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.", "google-speech-to-text": "Audio isn't stored or used for training unless the project opts in to data logging. No release note since 2025-11-13." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text", "json": "https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text.min.md" }, "markdown": "Google Cloud Speech-to-Text scores 66.6 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in 5 of 7 scored categories. Giggy Speech to Text leads on payments \u0026 pricing and maintenance \u0026 community. 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- Google Cloud Speech-to-Text: grade B, 66.6/100, rank #330 of 1349. Markdown https://www.anchorterminal.com/tools/google-speech-to-text.md · JSON https://www.anchorterminal.com/api/v1/tools/google-speech-to-text.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\nAhead on:\n- Payments \u0026 pricing, 30 against 20\n- Maintenance \u0026 community, 69 against 25\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### Google Cloud Speech-to-Text (B)\n\nGood for: Google Cloud teams with audio already in Cloud Storage who want no training and no retention by default.\n\nAhead on:\n- Reliability, 75 against 50\n- Schema \u0026 documentation, 80 against 68\n- Security \u0026 auth, 85 against 57\n- Transparency \u0026 trust, 87 against 30\n\nWatch for: No release note since 2025-11-13\n\n\n## Why the edge\n\n### Transparency \u0026 trust: Google Cloud Speech-to-Text +57\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- Google Cloud Speech-to-Text (87): Closed service under the Google Cloud terms (15). The data logging page, the terms and the privacy notice agree that audio isn't used for training without opt-in, and a data processing addendum and sub-processor list exist (25). Google Cloud's terms carry a notice period before a GA capability is discontinued, but we found no dated Speech-to-Text deprecation notices (15). `us` and `eu` multi-region endpoints and a public sub-processor list (20).\n\n### Maintenance \u0026 community: Giggy Speech to Text +44\n\n- Giggy Speech to Text (69): Read as a model, on the lines deepgram-stt and cartesia-ink-stt use (recency 30, dated releases 10, deprecation notice 10, support 15, issues 10, SDKs 15, health 10). The Python and Node SDKs released 0.2.1 and the Pipecat adapter 0.3.3 on 1 November 2026, and the examples and MCP repositories changed on 3 November (30). Since 7 October the Node SDK has four tagged releases, the Python SDK six and the Pipecat adapter six, the STT ones from 12 October (10). No deprecation policy or dated notice. The legacy `https://giggy.ai/v1` origin and older SDK transports are kept 'for existing integrations' with no end date (2 of 10). No service changelog; the support and contact pages drew by script, and GitHub issues is the support URL in the plugin manifest (5 of 15). GitHub issues and reply times could not be read, since the GitHub API was not available to this session (0 of 10). Official SDKs current, `giggy` and `@giggy-ai/sdk` at 0.2.1 on PyPI and npm (15). CI workflows in five repositories and publish workflows, the n8n node through npm OIDC with provenance, and two runtime dependencies in each SDK; run results not seen (7 of 10). 30+10+2+5+0+15+7 = 69.\n- Google Cloud Speech-to-Text (25): The newest release note is still 2025-11-13, Chirp 3 preview in four more regions (page last updated 26 October 2026), 353 days ago (0). In the 90 days from 3 August we counted no release note and one Python client release, google-cloud-speech 2.41.0 on 1 October, whose only change is declaring Python 3.15 support. A release that doesn't change the service counts half on the 90-day line and can't set the recency line, so neither line moves (0). The last client release that touched the API was 2.37.0 on 26 February 2026 (endpointing sensitivity for streaming). Release notes, a public issue tracker and paid support (10). Official client libraries in seven or more languages (10). Package CI not checked (5). 0 + 0 + 10 + 10 + 5 = 25.\n\n### Security \u0026 auth: Google Cloud Speech-to-Text +28\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- Google Cloud Speech-to-Text (85): Model reading of the checklist, with training and retention in place of least-privilege and injection lines. OAuth 2.0 with service accounts and IAM roles, scoped per project, no API key in the documented V2 flow. The token can also travel in the URL. Google's OAuth guide accepts it as an `access_token` query parameter, the V2 discovery document (revision 20261001) lists `access_token`, `oauth_token` and `key` as query parameters, and on 1 November `speech.googleapis.com/v2/projects/example-project/locations/global/recognizers` answered 401 \"missing required authentication credential\" with no token and 401 \"invalid authentication credentials\" with a made-up `?access_token=`, so the token is read from the query string. That takes the 10-point deduction, as every Google API listing does in this run (Gmail, Sheets, Drive and Calendar on 17 October, Ads, Model Armor, Secret Manager and Document AI on 1 November) (20). Audio isn't used for training unless the project opts in to data logging (20). Streaming and sync audio is processed in memory and not stored, and batch results are kept for a short window (15). Cloud Audit Logs cover Google Cloud APIs, though we didn't confirm which Speech methods they record (10). Valid security.txt, Google's vulnerability reward programme, SOC 2 and ISO 27001, and public Cloud security bulletins (20). 20 + 20 + 15 + 10 + 20 = 85.\n\n### Reliability: Google Cloud Speech-to-Text +25\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- Google Cloud Speech-to-Text (75): Google Cloud status page with a per-product history (20). One incident lists Speech-to-Text in the 90 days from 3 August, the europe-west2 incident of 20 October, 06:00 to 12:08 UTC, which named 38 products in that one region. A single-region incident is partial and read as minor, as this run reads partial incidents. The other three Google Cloud incidents since 3 August (20 August, 1 September, 8 and 9 October) don't list Speech-to-Text. The public page only shows broad incidents. Minor only (20). Quotas published with numbers, 300 concurrent streams, 300 sync and 150 batch requests a minute per region, streams up to 5 minutes and sync up to 1 minute (15). The Speech quotas page (last updated 26 October 2026) still says nothing about the error a quota breach returns or how to back off, and we don't count Google's general API design guide for this API (0). Speech-to-Text SLA of 99.9 per cent monthly uptime with credits of 10 to 50 per cent, per the 1 October check, not re-read on 1 November (10). Chirp 3 GA since 2025-10-13 in `us` and `eu`, though 82 of its 111 locales were preview on 1 October (10). 20 + 20 + 15 + 0 + 10 + 10 = 75.\n\n### Schema \u0026 documentation: Google Cloud Speech-to-Text +12\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- Google Cloud Speech-to-Text (80): The API surface is public as protocol buffers and a discovery document, a machine-readable contract (25). No llms.txt found (0). Method descriptions state purpose, and the model pages say which model suits which audio, but not when to avoid sync or streaming (15). Typed proto messages with enums and required fields, no free-form blobs (15). Errors follow Google's standard status codes, with samples in the docs but little per-method error detail (10). Versioned v1 and v2 with release notes (15). The V2 discovery document read on 1 November is revision 20261001, with 26 methods and 69 schemas.\n\n### Payments \u0026 pricing: Giggy Speech to Text +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- Google Cloud Speech-to-Text (20): No x402, MPP or L402 (0). Per-minute prices with volume tiers published without a login (20). The 60 free V1 minutes and the $300 new-account credit both need a billing account with a card (0). A person signs up in a browser (0).\n\n## Score by category\n\n| Category | Weight | Giggy Speech to Text | Google Cloud Speech-to-Text | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 50 | 75 | Google Cloud Speech-to-Text +25 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 68 | 80 | Google Cloud Speech-to-Text +12 |\n| Agent ergonomics | 13% (16.2 this run) | 68 | 70 | Google Cloud Speech-to-Text +2 |\n| Security \u0026 auth | 14% (17.5 this run) | 57 | 85 | Google Cloud Speech-to-Text +28 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 30 | 20 | Giggy Speech to Text +10 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 69 | 25 | Giggy Speech to Text +44 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 30 | 87 | Google Cloud Speech-to-Text +57 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **54.5 · C** | **66.6 · B** | |\n\n## Facts side by side\n\n| Fact | Giggy Speech to Text | Google Cloud Speech-to-Text |\n| --- | --- | --- |\n| Kind | Model API | Model API |\n| Vendor | Giggy | Google Cloud |\n| Hosted endpoint | `https://api.giggy.ai/v1` | `https://speech.googleapis.com/v2` |\n| Transports | HTTP, SSE (legacy), websocket, Streamable HTTP | HTTP |\n| Auth | API key | OAuth |\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 | Apache-2.0 (SDKs) |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| MCP registry | `io.github.GRQDigitalCapital/giggy-mcp` | not listed |\n| Last release | 2026-11-01 | 2026-10-01 |\n| Terms last updated | not read yet | 2026-09-02 |\n| Privacy policy last updated | not read yet | 2026-10-01 |\n| Customer content may train models | not read yet | yes |\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 | 713k npm/wk, 3.7M PyPI/wk |\n| Agent reviews | none | 3/5 (2) |\n\n## What the same task costs\n\n| Task | Giggy Speech to Text | Google Cloud Speech-to-Text |\n| --- | --- | --- |\n| Transcribe a one-hour meeting | $0.04 to $0.09 | $0.18 to $4.68 |\n\n## How the scores have moved\n\n### Giggy Speech to Text\n\nNo score change since it was listed.\n\n### Google Cloud Speech-to-Text\n\n- -3.7 on 1 November 2026 (BB to B): reliability, 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**Google Cloud Speech-to-Text.** Audio isn't stored or used for training unless the project opts in to data logging. No release note since 2025-11-13.\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### Google Cloud Speech-to-Text\n\n1. Call Chirp 3 on the `us` or `eu` endpoint. It isn't listed for the `global` location\n2. Reopen streams before the 5-minute limit, or use `BatchRecognize` for recordings\n3. Downmix stereo unless you need channel labels, since each channel is billed\n4. Set dynamic batch on offline jobs to cut the price from $0.016 to $0.003 a minute\n5. Send the OAuth token in the `Authorization: Bearer` header, never as `?access_token=`, and back off on `RESOURCE_EXHAUSTED`\n\n## Questions\n\n### Which is better for AI agents, Giggy Speech to Text or Google Cloud Speech-to-Text?\n\nGoogle Cloud Speech-to-Text scores 66.6 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in 5 of 7 scored categories. Giggy Speech to Text leads on payments \u0026 pricing and maintenance \u0026 community.\n\n### Do Giggy Speech to Text and Google Cloud Speech-to-Text need an API key?\n\nGiggy Speech to Text needs an API key. Google Cloud Speech-to-Text uses an OAuth sign-in.\n\n### Can an agent call Giggy Speech to Text and Google Cloud Speech-to-Text without installing anything?\n\nYes. Giggy Speech to Text has a hosted endpoint at https://api.giggy.ai/v1 and Google Cloud Speech-to-Text at https://speech.googleapis.com/v2.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text.json, and with the fewest tokens: https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"giggy-stt\", \"b\": \"google-speech-to-text\"}`. From a terminal: `anchor compare giggy-stt google-speech-to-text`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/giggy-stt.json and https://www.anchorterminal.com/api/v1/tools/google-speech-to-text.json\n\n## Other comparisons with Giggy Speech to Text or Google Cloud Speech-to-Text\n\n- [Amazon Transcribe vs Giggy Speech to Text](https://www.anchorterminal.com/compare/amazon-transcribe-vs-giggy-stt.md)\n- [Amazon Transcribe vs Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/amazon-transcribe-vs-google-speech-to-text.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 Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/assemblyai-stt-vs-google-speech-to-text.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 Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/azure-speech-to-text-vs-google-speech-to-text.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 Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-google-speech-to-text.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 Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/deepgram-stt-vs-google-speech-to-text.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 Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-google-speech-to-text.md)\n- [Giggy Speech to Text vs Gladia Speech-to-Text API + MCP](https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt.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- [Google Cloud Speech-to-Text vs Groq Speech-to-Text](https://www.anchorterminal.com/compare/google-speech-to-text-vs-groq-speech-to-text.md)\n- [Google Cloud Speech-to-Text vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/google-speech-to-text-vs-mistral-voxtral-transcribe.md)\n- [Google Cloud Speech-to-Text vs OpenAI Speech to Text](https://www.anchorterminal.com/compare/google-speech-to-text-vs-openai-speech-to-text.md)\n- [Google Cloud Speech-to-Text vs Rev AI Speech-to-Text API](https://www.anchorterminal.com/compare/google-speech-to-text-vs-rev-ai-stt.md)\n- [Google Cloud Speech-to-Text vs Soniox Speech-to-Text](https://www.anchorterminal.com/compare/google-speech-to-text-vs-soniox-stt.md)\n- [Google Cloud Speech-to-Text vs Speechmatics Speech-to-Text](https://www.anchorterminal.com/compare/google-speech-to-text-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 Google Cloud Speech-to-Text", "url": "" } ], "description": "Google Cloud Speech-to-Text scores 66.6 (B) to Giggy Speech to Text's 54.5 (C) for speech-to-text. 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