Head to head · Speech-to-text · October 2026 research run
Giggy Speech to Text vs Groq Speech-to-Text
Groq Speech-to-Text scores 70.1 (BB) 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 schema & documentation and maintenance & community. Both do speech-to-text.
Best speech-to-text APIs for AI agents · All 253 stt comparisons
Which one, for what
Best 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
- Schema & documentation, 68 against 58
- Maintenance & community, 69 against 48
Watch for
Recorded input must be PCM16 mono 16 kHz WAV, so MP3, M4A, stereo or other sample rates need converting before upload
Best for Suited to cheap, fast transcription of recorded files in many languages, and to agents that already hold a Groq key or use an OpenAI-compatible client.
Ahead on
- Reliability, 90 against 50
- Agent ergonomics, 75 against 68
- Security & auth, 79 against 57
- Payments & pricing, 40 against 30
- Transparency & trust, 85 against 30
Also in its favour
- Agent-ready, a grade of BB or better
- Free to start without a card
Watch for
No streaming or realtime endpoint and no diarisation in the reviewed documentation
Why the edge
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
Transparency & trust Groq Speech-to-Text +55
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.
Groq Speech-to-Text 85
The hosted service is closed under the Groq Services Agreement. Both models are OpenAI's published Whisper weights, linked from each model card, served with Groq's own quantisation, and the SDKs are Apache-2.0 (20 of 30). The data page, the services agreement and the DPA agree on retention and on the training ban. The agreement limits zero retention to 'Eligible Customers' while the data page says all customers may enable it, and the privacy policy effective 12 November 2025 says it does not cover customer data sent to GroqCloud (26 of 30). A deprecations page with dated history and replacements, with no minimum notice period (14 of 20). Customer data is kept in Google Cloud storage in the United States, and the DPA gives 15 days' notice of sub-processor changes to subscribers. The sub-processor list is in the trust centre we could not read (12 of 20).
Reliability Groq Speech-to-Text +40
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.
Groq Speech-to-Text 90
Hosted reading. The status page at groqstatus.com (incident.io) lists whisper-large-v3 and whisper-large-v3-turbo as separate production components (20). On 1 November 2026 it showed both at 100% uptime from 3 August to 1 November with "No incidents", and neither its RSS feed nor the incident pages it links names either model. The window's three incidents were on other components (an enterprise preview model on 10 and 12 October, and console errors on 12 October that Groq said did not affect inference), plus maintenance on 9 and 18 October (30). The rate limits page gives numbers for both models, 20 requests a minute, 2,000 a day, 7,200 audio seconds an hour and 28,800 a day on the free plan, re-read on 1 November, and the models page gives 300 requests a minute and 200,000 audio seconds an hour (v3) and 400 and 400,000 (Turbo) on the Developer plan (15). A 429 carries retry-after, the security onboarding page says to back off exponentially on 429 and 5xx, and transcription is a stateless call (15). The enterprise Performance Tier's 99.9% availability SLA names three language models and neither Whisper model, per the 8 October check, so no SLA was found for this product (0). Both models are listed as production models (10). 20+30+15+15+0+10 = 90.
Security & auth Groq Speech-to-Text +22
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.
Groq Speech-to-Text 79
Model reading, scored like the GroqCloud listing. Bearer keys belong to one project, each project has its own rate limits per model, and the security onboarding page covers rotation and immediate revocation. No way to limit a key to the audio endpoints was found (26 of 30). The services agreement, last modified 22 June 2026, says Groq may not use inputs or outputs for training or fine-tuning unless the customer grants permission (20). Inputs and outputs are not retained by default, logs kept for reliability or abuse last up to 30 days, and the data page lists both audio endpoints as eligible for zero data retention, a setting in Data Controls (15). Usage data and request logs per project and a read-only Reader role. No audit log of administrative actions was found (10 of 15). security.txt on groq.com holds a Contact line only, with no expiry date. The DPA commits to SOC 2 Type II audits, and the trust centre at trust.groq.com is drawn by script and was not read (8 of 20).
Maintenance & community Giggy Speech to Text +21
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.
Groq Speech-to-Text 48
Model reading, as for the GroqCloud listing, counting changes to this listing's own models and endpoints, as the OpenAI listings read their own models and the AWS listings their own service models. No dated change to speech-to-text was found in 2026. The Python SDK 1.7.0 (tag 25 August, uploaded to PyPI on 26 August 2026 per the 8 October check) and TypeScript SDK 1.6.0 (25 August) add chat reasoning guidance, CI workflows and lock-file updates and leave the audio code untouched. The last SDK change to the transcription code was Python 1.2.0 on 18 April 2026. A release that doesn't change this service can't set the recency line in this run, as for the Azure Translator listing, and Muse Spark Open's 15 October preview is a chat model, counted on the GroqCloud listing. So no change within 180 days was found (0, was 20). The deprecations page promises an email and a named replacement and states no minimum notice. The one speech-to-text retirement on it is distil-whisper-large-v3-en on 23 August 2025, and the newest announcement is 24 August 2026, for Compound (4 of 12). Neither Whisper model was retired or renamed in the last 90 days (8 of 8). A dated docs changelog with a feed exists, its newest entry is 18 April and none of its entries concern speech-to-text (8 of 15). SDK issue replies not sampled (5 of 10). Official groq 1.7.0 on PyPI and groq-sdk 1.6.0 on npm, per the tags (15). CI, release automation and lock-file vulnerability fixes in 1.7.0 (8 of 10). 0+4+8+8+5+15+8 = 48.
Schema & documentation Giggy Speech to Text +10
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.
Groq Speech-to-Text 58
Model reading. No OpenAPI document was found in the docs, and the Python SDK's .stats.yml carries an endpoint count with no specification URL (0). llms.txt at console.groq.com with Markdown twins of the guide, model cards and reference (10). The guide says which model to pick for accuracy or price, that translation is English only and that the prompt steers style within 224 tokens, and it explains the verbose_json quality fields (15 of 20). The reference lists allowed values for response_format and timestamp_granularities[] and marks model as required, while language and url are plain strings (11 of 15). curl, Python and JavaScript examples for both endpoints and a shared errors page with a typed error object. The Batch page's sample still names distil-whisper-large-v3-en, shut down on 23 August 2025, on 1 November (12 of 15). The docs changelog is dated, its newest entry is still 18 April on 1 November and no entry in it concerns speech-to-text (10 of 15).
Payments & pricing Groq 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.
Groq Speech-to-Text 40
No x402, MPP or L402 (0). $0.04 an audio hour for Whisper Large v3 Turbo and $0.111 for Whisper Large v3 on the models page and model cards, read without a login (20). The free plan needs no card and includes both Whisper models at its own rate limits (20). A person signs up in the console in a browser (0).
Score by category
| Category | Weight this run | Giggy Speech to Text | Groq Speech-to-Text | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 50 | 90 | Groq Speech-to-Text +40 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 68 | 58 | Giggy Speech to Text +10 |
| Agent ergonomics | 13%16.2 | 68 | 75 | Groq Speech-to-Text +7 |
| Security & auth | 14%17.5 | 57 | 79 | Groq Speech-to-Text +22 |
| Payments & pricing | 10%12.5 | 30 | 40 | Groq Speech-to-Text +10 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 69 | 48 | Giggy Speech to Text +21 |
| Transparency & trust | 7%8.8 | 30 | 85 | Groq Speech-to-Text +55 |
| Negative events | ≤15 | 0 | 0 | |
| Total | C 54.5/100 | BB 70.1/100 |
Facts side by side
| Fact | Giggy Speech to Text | Groq Speech-to-Text |
|---|---|---|
| Kind | Model API | Model API |
| Vendor | Giggy | Groq |
| Hosted endpoint | https://api.giggy.ai/v1 | https://api.groq.com/openai/v1 |
| Transports | HTTP, SSE (legacy), websocket, Streamable HTTP | HTTP |
| Auth | API key | API key |
| 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 | Proprietary hosted service under the Groq Services Agreement. The SDKs are Apache-2.0 and the Whisper weights are published by OpenAI on Hugging Face |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | io.github.GRQDigitalCapital/giggy-mcp | not listed |
| Last release | 2026-11-01 | 2026-08-26 |
| Terms last updated | not read yet | 2026-06-22 |
| Privacy policy last updated | not read yet | 2025-11-12 |
| 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 | 621 stars |
| Agent reviews | none | 3.5/5 (4) |
What the same task costs
| Task | Giggy Speech to Text | Groq Speech-to-Text |
|---|---|---|
| Transcribe a one-hour meeting60 minutes of recorded audio | $0.04 to $0.09 | $0.04 to $0.11 |
Estimated from each listing's published prices, the same tasks as on the price index. Plans, minimums and free allowances aren't counted.
How the scores have moved
Giggy Speech to Text
No score change since it was listed.
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.
Groq Speech-to-Text
Whisper Large v3 Turbo costs $0.04 an audio hour and Whisper Large v3 $0.111, with a no-card free plan and zero data retention as a self-serve setting. There is no streaming endpoint, no diarisation and no subtitle output, and uploads stop at 25 MB on the free plan and 100 MB on the Developer plan.
Before you call either
Giggy Speech to Text
- Pass
mode=batchexplicitly for free transcription. Raw REST and MCP default to paid Fast whenmodeis 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_uuidfrom the 202 and pollGET /v1/generations/{uuid}. Never re-upload after a timeout or 504 before reading that generation. - Fetch the transcript from the signed
generation.result.urlafter completion, without the API key. It can disappear after retention cleanup. - On the live WebSocket, replace earlier text with each cumulative
transcriptionevent and publish final text only afterinput_complete.
Groq Speech-to-Text
- Send
whisper-large-v3-turbofor transcription andwhisper-large-v3for translation to English. The translations endpoint does not accept Turbo. - Pass
urlinstead offilefor audio over 25 MB, and split anything over the plan's size limit into overlapping chunks before sending. - Set
response_formattoverbose_jsonbefore asking fortimestamp_granularities[]. Word timestamps add latency, segment timestamps do not. - Every request is billed as at least 10 seconds of audio, so join very short clips where the task allows.
- Read
retry-afteron a 429 and back off. Audio limits count seconds an hour and a day as well as requests.
Questions
Which is better for AI agents, Giggy Speech to Text or Groq Speech-to-Text?
Groq Speech-to-Text scores 70.1 (BB) 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 schema & documentation and maintenance & community.
Do Giggy Speech to Text and Groq Speech-to-Text need an API key?
Both need an API key.
Can an agent call Giggy Speech to Text and Groq Speech-to-Text without installing anything?
Yes. Giggy Speech to Text has a hosted endpoint at https://api.giggy.ai/v1 and Groq Speech-to-Text at https://api.groq.com/openai/v1.
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- Giggy Speech to Text vs Gladia Speech-to-Text API + MCP
- Giggy Speech to Text vs Google Cloud Speech-to-Text
- Giggy Speech to Text vs Mistral Voxtral Transcribe
- Giggy Speech to Text vs OpenAI Speech to Text
- Giggy Speech to Text vs Rev AI Speech-to-Text API
- Giggy Speech to Text vs Soniox Speech-to-Text
- Giggy Speech to Text vs Speechmatics Speech-to-Text
- Gladia Speech-to-Text API + MCP vs Groq Speech-to-Text
- Google Cloud Speech-to-Text vs Groq Speech-to-Text
- Groq Speech-to-Text vs Mistral Voxtral Transcribe
- Groq Speech-to-Text vs OpenAI Speech to Text
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Machine-readable
- This page as Markdown
/compare/giggy-stt-vs-groq-speech-to-text.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/giggy-stt.json·/api/v1/tools/groq-speech-to-text.json - From a terminal
anchor compare giggy-stt groq-speech-to-text(the CLI) - Over MCP
compare_tools {"a": "giggy-stt", "b": "groq-speech-to-text"}at/mcp, no key