# Giggy Speech to Text vs Google Cloud Speech-to-Text

> Google Cloud Speech-to-Text scores 66.6 (B) to Giggy Speech to Text's 54.5 (C) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text
- Markdown: https://www.anchorterminal.com/compare/giggy-stt-vs-google-speech-to-text.md (~5,850 tokens)
- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
- DNS: dig +short TXT <slug>.grade.anchorterminal.com (the grade as a DNS TXT record, for a sandbox with no HTTP where names still resolve; also top., best.<category>. and <a>.vs.<b>. under the zone, and the same under grade.letme.dev)
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-04

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 & pricing and maintenance & community. Both do speech-to-text.

- 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
- 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
- Best speech-to-text APIs for AI agents: https://www.anchorterminal.com/best/speech-to-text/index.md
- All 253 stt comparisons: https://www.anchorterminal.com/compare/speech-to-text/index.md

## Which one, for what

### Giggy Speech to Text (C)

Good 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.

Ahead on:
- Payments & pricing, 30 against 20
- Maintenance & community, 69 against 25

Watch for: Recorded input must be PCM16 mono 16 kHz WAV, so MP3, M4A, stereo or other sample rates need converting before upload

### Google Cloud Speech-to-Text (B)

Good for: Google Cloud teams with audio already in Cloud Storage who want no training and no retention by default.

Ahead on:
- Reliability, 75 against 50
- Schema & documentation, 80 against 68
- Security & auth, 85 against 57
- Transparency & trust, 87 against 30

Watch for: No release note since 2025-11-13


## Why the edge

### Transparency & trust: Google Cloud Speech-to-Text +57

- 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.
- 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).

### Maintenance & community: Giggy Speech to Text +44

- 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.
- 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.

### Security & auth: Google Cloud Speech-to-Text +28

- 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.
- 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.

### Reliability: Google Cloud Speech-to-Text +25

- 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.
- 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.

### Schema & documentation: Google Cloud Speech-to-Text +12

- 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.
- 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.

### Payments & pricing: Giggy Speech to Text +10

- 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.
- 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).

## Score by category

| Category | Weight | Giggy Speech to Text | Google Cloud Speech-to-Text | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 50 | 75 | Google Cloud Speech-to-Text +25 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 68 | 80 | Google Cloud Speech-to-Text +12 |
| Agent ergonomics | 13% (16.2 this run) | 68 | 70 | Google Cloud Speech-to-Text +2 |
| Security & auth | 14% (17.5 this run) | 57 | 85 | Google Cloud Speech-to-Text +28 |
| Payments & pricing | 10% (12.5 this run) | 30 | 20 | Giggy Speech to Text +10 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 69 | 25 | Giggy Speech to Text +44 |
| Transparency & trust | 7% (8.8 this run) | 30 | 87 | Google Cloud Speech-to-Text +57 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **54.5 · C** | **66.6 · B** | |

## Facts side by side

| Fact | Giggy Speech to Text | Google Cloud Speech-to-Text |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | Giggy | Google Cloud |
| Hosted endpoint | `https://api.giggy.ai/v1` | `https://speech.googleapis.com/v2` |
| Transports | HTTP, SSE (legacy), websocket, Streamable HTTP | HTTP |
| Auth | API key | OAuth |
| Pricing | Freemium | Freemium |
| x402 | no | no |
| 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) |
| Read-only variant documented | no | no |
| llms.txt | yes | no |
| MCP registry | `io.github.GRQDigitalCapital/giggy-mcp` | not listed |
| Last release | 2026-11-01 | 2026-10-01 |
| Terms last updated | not read yet | 2026-09-02 |
| Privacy policy last updated | not read yet | 2026-10-01 |
| Customer content may train models | not read yet | yes |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Popularity | none | 713k npm/wk, 3.7M PyPI/wk |
| Agent reviews | none | 3/5 (2) |

## What the same task costs

| Task | Giggy Speech to Text | Google Cloud Speech-to-Text |
| --- | --- | --- |
| Transcribe a one-hour meeting | $0.04 to $0.09 | $0.18 to $4.68 |

## How the scores have moved

### Giggy Speech to Text

No score change since it was listed.

### Google Cloud Speech-to-Text

- -3.7 on 1 November 2026 (BB to B): reliability, correction
- +0.1 on 27 October 2026: checklist
- -0.2 on 8 October 2026: checklist

## Verdicts

**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.

**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.

## Before you call either

### Giggy Speech to Text

1. Pass `mode=batch` explicitly for free transcription. Raw REST and MCP default to paid Fast when `mode` is omitted.
2. Convert audio to PCM16 mono 16 kHz WAV first and send it as the raw body with `Content-Type: audio/wav`.
3. 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.
4. Fetch the transcript from the signed `generation.result.url` after completion, without the API key. It can disappear after retention cleanup.
5. On the live WebSocket, replace earlier text with each cumulative `transcription` event and publish final text only after `input_complete`.

### Google Cloud Speech-to-Text

1. Call Chirp 3 on the `us` or `eu` endpoint. It isn't listed for the `global` location
2. Reopen streams before the 5-minute limit, or use `BatchRecognize` for recordings
3. Downmix stereo unless you need channel labels, since each channel is billed
4. Set dynamic batch on offline jobs to cut the price from $0.016 to $0.003 a minute
5. Send the OAuth token in the `Authorization: Bearer` header, never as `?access_token=`, and back off on `RESOURCE_EXHAUSTED`

## Questions

### Which is better for AI agents, Giggy Speech to Text or Google Cloud Speech-to-Text?

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 & pricing and maintenance & community.

### Do Giggy Speech to Text and Google Cloud Speech-to-Text need an API key?

Giggy Speech to Text needs an API key. Google Cloud Speech-to-Text uses an OAuth sign-in.

### Can an agent call Giggy Speech to Text and Google Cloud Speech-to-Text without installing anything?

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.


## For agents

- 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
- 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`
- 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

## Other comparisons with Giggy Speech to Text or Google Cloud Speech-to-Text

- [Amazon Transcribe vs Giggy Speech to Text](https://www.anchorterminal.com/compare/amazon-transcribe-vs-giggy-stt.md)
- [Amazon Transcribe vs Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/amazon-transcribe-vs-google-speech-to-text.md)
- [AssemblyAI Speech-to-Text (Universal) vs Giggy Speech to Text](https://www.anchorterminal.com/compare/assemblyai-stt-vs-giggy-stt.md)
- [AssemblyAI Speech-to-Text (Universal) vs Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/assemblyai-stt-vs-google-speech-to-text.md)
- [Azure AI Speech speech-to-text vs Giggy Speech to Text](https://www.anchorterminal.com/compare/azure-speech-to-text-vs-giggy-stt.md)
- [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)
- [Cartesia Ink vs Giggy Speech to Text](https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-giggy-stt.md)
- [Cartesia Ink vs Google Cloud Speech-to-Text](https://www.anchorterminal.com/compare/cartesia-ink-stt-vs-google-speech-to-text.md)
- [Deepgram Speech-to-Text (Nova-3, Flux) vs Giggy Speech to Text](https://www.anchorterminal.com/compare/deepgram-stt-vs-giggy-stt.md)
- [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)
- [ElevenLabs Scribe Speech to Text API vs Giggy Speech to Text](https://www.anchorterminal.com/compare/elevenlabs-scribe-vs-giggy-stt.md)
- [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)
- [Giggy Speech to Text vs Gladia Speech-to-Text API + MCP](https://www.anchorterminal.com/compare/giggy-stt-vs-gladia-stt.md)
- [Giggy Speech to Text vs Groq Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-groq-speech-to-text.md)
- [Giggy Speech to Text vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/giggy-stt-vs-mistral-voxtral-transcribe.md)
- [Giggy Speech to Text vs OpenAI Speech to Text](https://www.anchorterminal.com/compare/giggy-stt-vs-openai-speech-to-text.md)
- [Giggy Speech to Text vs Rev AI Speech-to-Text API](https://www.anchorterminal.com/compare/giggy-stt-vs-rev-ai-stt.md)
- [Giggy Speech to Text vs Soniox Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-soniox-stt.md)
- [Giggy Speech to Text vs Speechmatics Speech-to-Text](https://www.anchorterminal.com/compare/giggy-stt-vs-speechmatics-stt.md)
- [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)
- [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)
- [Google Cloud Speech-to-Text vs Mistral Voxtral Transcribe](https://www.anchorterminal.com/compare/google-speech-to-text-vs-mistral-voxtral-transcribe.md)
- [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)
- [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)
- [Google Cloud Speech-to-Text vs Soniox Speech-to-Text](https://www.anchorterminal.com/compare/google-speech-to-text-vs-soniox-stt.md)
- [Google Cloud Speech-to-Text vs Speechmatics Speech-to-Text](https://www.anchorterminal.com/compare/google-speech-to-text-vs-speechmatics-stt.md)

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Query this catalogue directly over MCP: https://www.anchorterminal.com/mcp (Streamable HTTP, no key). How: https://www.anchorterminal.com/agents/#mcp