# Giggy Speech to Text vs Speechmatics Speech-to-Text (slim)

> Speechmatics Speech-to-Text scores 67.8 (B) to Giggy Speech to Text's 54.5 (C) for speech-to-text. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/giggy-stt-vs-speechmatics-stt.md (~5,650 tokens) · this version ~3,480 tokens · JSON https://www.anchorterminal.com/compare/giggy-stt-vs-speechmatics-stt.json · canonical https://www.anchorterminal.com/compare/giggy-stt-vs-speechmatics-stt
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-04
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

Speechmatics Speech-to-Text scores 67.8 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category. Both do speech-to-text.

- Giggy Speech to Text: C 54.5, rank #806 of 1349 · https://www.anchorterminal.com/tools/giggy-stt.min.md
- Speechmatics Speech-to-Text: B 67.8, rank #280 of 1349 · https://www.anchorterminal.com/tools/speechmatics-stt.min.md
- Giggy Speech to Text, 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. Also No incidents deducted, where Speechmatics Speech-to-Text loses 3 points for them.
- Speechmatics Speech-to-Text, good for Regulated or privacy-sensitive audio, multilingual batch with Melia 1, and voice agents that want speaker-attributed turns. Ahead on Reliability, 70 against 50; Schema & documentation, 90 against 68; Agent ergonomics, 80 against 68; Security & auth, 65 against 57; Payments & pricing, 40 against 30; Transparency & trust, 76 against 30. Also Free to start without a card.

| Category | Giggy Speech to Text | Speechmatics Speech-to-Text |
| --- | --- | --- |
| Reliability (16%) | 50 | 70 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 68 | 90 |
| Agent ergonomics (13%) | 68 | 80 |
| Security & auth (14%) | 57 | 65 |
| Payments & pricing (10%) | 30 | 40 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 69 | 70 |
| Transparency & trust (7%) | 30 | 76 |

| Fact (where they differ) | Giggy Speech to Text | Speechmatics Speech-to-Text |
| --- | --- | --- |
| Vendor | Giggy | Speechmatics |
| Hosted endpoint | `https://api.giggy.ai/v1` | `https://eu1.asr.api.speechmatics.com/v2` |
| Transports | HTTP, SSE (legacy), websocket, Streamable HTTP | HTTP |
| Pricing | Freemium | Pay per use |
| Price for speech-to-text | not published | $0.0025 per minute of audio |
| Licence | Proprietary hosted service. The terms page draws its text by script and was not read. The Python and Node SDKs, the Pipecat adapter and the MCP repository are ISC (Copyright 2026 Giggy), the n8n node MIT | MIT (SDKs) |
| MCP registry | `io.github.GRQDigitalCapital/giggy-mcp` | not listed |
| Last release | 2026-11-01 | 2026-10-26 |
| Terms last updated | not read yet | no date given |
| Privacy policy last updated | not read yet | 2026-05-27 |
| Customer content may train models | not read yet | not found in the text |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | yes |
| 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 | 20 stars, 58k npm/wk, 48k PyPI/wk |
| Agent reviews | none | 3.5/5 (2) |

Why the edge:
- Transparency & trust, Speechmatics Speech-to-Text +46: 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.); Speechmatics Speech-to-Text 76 (Closed service with clear terms and MIT SDKs (15). The pricing page, limits pages and security page agree on opt-in training, 7-day batch retention and no storage for realtime (25). The changelog announces behaviour changes in advance, such as the 23 September 2026 switch to waiting polls, but we found no deprecation policy (10). EU1, US1 and AU1 regions documented per endpoint and the service named as Azure-hosted, but no sub-processor list was found (15).)
- Schema & documentation, Speechmatics Speech-to-Text +22: 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.); Speechmatics Speech-to-Text 90 (A Swagger 2.0 file for the Batch API (5 paths, `/jobs`, `/jobs/{jobid}`, its transcript and log, and `/usage`) is linked from the API reference as a download, and has been since July 2025, and the public docs repository holds AsyncAPI 3.0 files for Realtime and Agent STT (25). llms.txt and Markdown pages (10). Reference and guide pages state purpose, and the models page says where Melia 1 and Oak 1 differ from Enhanced (15). Options are documented with types and enums, but a batch job's options travel as a JSON string in the multipart `config` field (10). Examples for each capability and documented errors, 429 reasons, 404 `expired` after 7 days and `Job rejected` (15). Versioned `/v2` paths and a dated public changelog (15).)
- Reliability, Speechmatics Speech-to-Text +20: 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.); Speechmatics Speech-to-Text 70 (Statuspage at status.speechmatics.com with components per region and history (20). Since 3 August, minor incidents only, each touching one region, one mode or a subset of requests. Batch AU slower for 2 hours on 10 August, a subset of Batch EU1, US1 and US2 jobs failing or slow for 56 minutes on 19 August, Realtime 4003 errors in the EU and US for 37 minutes on 4 September, and TLS errors for a subset of US Realtime sessions for about 2 hours on 10 September. The rest were scheduled database maintenance, a portal maintenance and a billing credit error, and nothing was posted after 10 September (20). Limits published with numbers, 10 new batch jobs and 50 status calls a second, 20,000 concurrent jobs, and 2 or 50 realtime sessions by plan (15). Both batch limits return 429 with a reason, but the docs only suggest notifications instead of polling and give no backoff or Retry-After (5). No SLA found for self-serve plans (0). Batch, Realtime and Agent STT on `/v2/agent` are GA (10).)
- Agent ergonomics, Speechmatics Speech-to-Text +12: Giggy Speech to Text 68 (API reading, as for the other speech-to-text listings. The transcript is compact, text, detected languages, audio duration and model metadata, with no word array to trim; on an MCP reading five tools would score 25 (20 of 25). Nothing to page through and no output options, no timestamps, subtitles or speaker labels, and recorded input must be PCM16 mono 16 kHz WAV, so the caller converts everything else; a 12-hour recording goes up in one request (10 of 20). Errors are structured with a type, code, message, status, request ID and parameter, and the reference says what each status means and what to do after a 504, but no list of code values was found and the SDK error classes expose only the status and the raw body (13 of 20). Upload retries are left to the caller with clear rules, read the generation first and never re-upload after a timeout; REST has no idempotency key and `client_request_id` is documented as no guarantee, while MCP `transcribe_audio` takes an `idempotency_key`. The SDKs never retry, and closing an unfinished live socket cancels it (13 of 20). Only the audio is required, with official Python and Node SDKs, but raw REST and MCP default to paid Fast while the SDKs default to free Batch (12 of 15). 20+10+13+13+12 = 68.); Speechmatics Speech-to-Text 80 (API reading of the checklist. Transcripts can be fetched as `txt`, `json-v2` or `srt` (20). The jobs list pages by creation date and limit (20). Documented status codes and realtime error messages an agent can act on (15). No idempotency key on job creation (10). A batch job needs a file and a language. Official SDKs in Python and JavaScript, split into batch and realtime packages (15).)
- Payments & pricing, Speechmatics 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.); Speechmatics Speech-to-Text 40 (No x402, MPP or L402 (0). Per-hour prices for every model published without a login, with credits at $1 each before discounts (20). $100 credit with no card (20). A person signs up in a browser (0).)
- Security & auth, Speechmatics Speech-to-Text +8: 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.); Speechmatics Speech-to-Text 65 (Model reading of the checklist, with training and retention in place of least-privilege and injection lines. API keys as bearer tokens, with a separate management token for key administration (20). Browser and realtime clients pass temporary keys as `?jwt=` on the WebSocket URL, with a lifetime the caller sets from 60 to 86,400 seconds, so we deduct half (minus 5). Training is opt-in only, and opting in buys a 33 per cent discount (20). Realtime audio isn't stored, batch data is deleted after 7 days or on request (15). A usage reporting service exists, but we found no per-request audit log (10). ISO/IEC 27001:2022 and SOC 2 Type II with a SafeBase trust centre. No security.txt (404 on 1 November), disclosure policy, bug bounty or public advisories found (5).)

| Task | Giggy Speech to Text | Speechmatics Speech-to-Text |
| --- | --- | --- |
| Transcribe a one-hour meeting | $0.04 to $0.09 | $0.12 to $0.40 |