Head to head · Speech-to-text · October 2026 research run

Giggy Speech to Text vs Mistral Voxtral Transcribe

Mistral Voxtral Transcribe scores 63.1 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category. Both do speech-to-text.

Best speech-to-text APIs for AI agents · All 253 stt comparisons

Which one, for what

Giggy Speech to Text C

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.

Also in its favour

  • No incidents deducted, where Mistral Voxtral Transcribe loses 6 points for them

Watch for

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

Mistral Voxtral Transcribe B

Best for Suited to low-cost batch transcription with diarisation in the 13 supported languages, and to live captions or voice agents that can run without speaker labels.

Ahead on

  • Schema & documentation, 85 against 68
  • Agent ergonomics, 77 against 68
  • Security & auth, 70 against 57
  • Payments & pricing, 40 against 30
  • Maintenance & community, 88 against 69
  • Transparency & trust, 83 against 30

Watch for

Voxtral Mini Transcribe 2 and Realtime 2602 retire on 30 April 2027, and their Voxtral 3 replacements are Public Preview with silent updates allowed

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 Mistral Voxtral Transcribe +53

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.

Mistral Voxtral Transcribe 83

The hosted service is closed under commercial terms. The Realtime weights are published on Hugging Face under Apache-2.0 and the SDKs are Apache-2.0, while Voxtral Mini Transcribe 2 has no public weights (20 of 30). The privacy policy effective 3 September 2026 (30 rolling days), the zero data retention page and the terms agree on retention, and the terms leave the API's training default unnamed (20 of 30). A model lifecycle page with notice periods per stage (20). Opt-in EU and US regional endpoints are documented, the global endpoint commits to no location, and the provider list is in a trust centre we could not read (13 of 20).

Maintenance & community Mistral Voxtral Transcribe +19

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.

Mistral Voxtral Transcribe 88

Model reading. Mistral released three Voxtral 3 transcription models (Mini Transcribe 3, Small Transcribe 3 and Mini Transcribe Realtime 3) in Public Preview on 20 October 2026, 13 days before this check (30). The lifecycle policy promises six months' notice for GA models, and Transcribe 2 and Realtime 2602 were deprecated on 31 October with retirement on 30 April 2027, 181 days (12 of 12). No transcription model was retired in the 90 days to 2 November; Voxtral Mini Transcribe (2507) retired on 31 May 2026 (8 of 8). Six dated changelog entries from 31 August to 22 October, one of them the Voxtral 3 release, read as mistral-api reads the same changelog (10 of 15). The eight newest open issues on client-python had zero or one comment per the 8 October check (5 of 10). Official mistralai 3.7.0 (1 November) per the client-python RELEASES.md, and @mistralai/mistralai, with a v2 to v3 migration guide (15). Both are generated from the OpenAPI document, with test, lint and example workflows in the repository (8 of 10). 30+12+8+10+5+15+8 = 88.

Schema & documentation Mistral Voxtral Transcribe +17

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.

Mistral Voxtral Transcribe 85

Model reading. The public OpenAPI document covers /v1/audio/transcriptions, its SSE streaming form and /v1/client/sessions. The realtime WebSocket messages are described by SDK types and guide examples, not by the document (22 of 25). llms.txt with Markdown twins of the speech-to-text, offline, realtime and client authentication pages (10). The guides say which model each endpoint runs, that timestamp_granularities and language cannot be combined and that realtime cannot diarise, and carry an OpenAI SDK compatibility table. In the OpenAPI document diarize, context_bias and temperature have no description (14 of 20). timestamp_granularities is an enum of segment and word, language is a two-letter pattern and context_bias items have a pattern, while model is a free string (12 of 15). curl, Python and TypeScript examples on each guide and a shared error glossary. The OpenAPI response example still names voxtral-mini-2507 (12 of 15). Dated model identifiers and a dated changelog (15).

Security & auth Mistral Voxtral Transcribe +13

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.

Mistral Voxtral Transcribe 70

Model reading, scored like the other Mistral listings. Keys are bound to one workspace, can carry an expiry date and a connector scope, and organisations can enforce a maximum key lifetime. Browser clients get rt_ tokens from POST /v1/client/sessions that last about 900 seconds, work for one model and travel in Sec-WebSocket-Protocol. A key cannot be limited to transcription (26 of 30). The commercial terms effective 25 September 2026 say Mistral will not train on customer data unless the customer opted in, or did not opt out where a product defaults to opt-in, without naming the API's default. The privacy and data controls page the docs link to returned 404 (10 of 20). Input and output are kept 30 rolling days for abuse monitoring, and /v1/audio/transcriptions is on the zero data retention list for paid plans, on request and subject to approval (12 of 15). Audit logs cover API key actions on Enterprise plans only (10 of 15). security.txt is valid until 5 May 2027 and names a HackerOne submission form, and the docs publish three security advisories for 2026. Certifications sit in a trust centre drawn by script that we could not read (12 of 20).

Payments & pricing Mistral Voxtral Transcribe +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.

Mistral Voxtral Transcribe 40

No x402, MPP or L402 (0). $0.003 a minute for Voxtral Mini Transcribe 2 and $0.006 a minute for Voxtral Realtime on public pages (20). Free mode gives API access with no card, within limits shown in the console (20). A person signs up in a browser (0).

Agent ergonomics Mistral Voxtral Transcribe +9

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.

Mistral Voxtral Transcribe 77

API reading, as for the other speech-to-text listings. Segments, word timestamps and speaker labels are returned only when asked for, and the default response is the text, the language and usage. No subtitle or plain-text output format was found (18 of 25). There is no transcript store to page through. Volume goes through the batch API, which accepts /v1/audio/transcriptions (12 of 20). Errors return type, param and code with a fix per status in the glossary (17 of 20). The call is stateless and safe to retry, the SDKs retry with backoff, and no idempotency key exists or is needed (15 of 20). model is the only required field beside the audio source, and there are official Python and TypeScript SDKs plus OpenAI SDK compatibility for the batch endpoint (15).

Score by category

CategoryWeight this runGiggy Speech to TextMistral Voxtral TranscribeEdge
Reliability16%205053Mistral Voxtral Transcribe +3
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.26885Mistral Voxtral Transcribe +17
Agent ergonomics13%16.26877Mistral Voxtral Transcribe +9
Security & auth14%17.55770Mistral Voxtral Transcribe +13
Payments & pricing10%12.53040Mistral Voxtral Transcribe +10
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.86988Mistral Voxtral Transcribe +19
Transparency & trust7%8.83083Mistral Voxtral Transcribe +53
Negative events≤150-6
TotalC 54.5/100B 63.1/100

Facts side by side

FactGiggy Speech to TextMistral Voxtral Transcribe
KindModel APIModel API
VendorGiggyMistral AI
Hosted endpointhttps://api.giggy.ai/v1https://api.mistral.ai/v1
TransportsHTTP, SSE (legacy), websocket, Streamable HTTPHTTP, websocket
AuthAPI keyAPI key
PricingFreemiumFreemium
x402nono
LicenceProprietary 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 MITProprietary hosted service under Mistral's commercial terms. Voxtral Mini 4B Realtime weights and the SDKs are Apache-2.0
Read-only variant documentednono
llms.txtyesyes
MCP registryio.github.GRQDigitalCapital/giggy-mcpnot listed
Last release2026-11-012026-10-20
Terms last updatednot read yet2026-09-25
Privacy policy last updatednot read yet2026-09-03
Customer content may train modelsnot read yetyes, with an opt-out
Terms restrict automated accessnot read yetnot found in the text
Terms restrict benchmarkingnot read yetyes
Terms or service can change without noticenot read yetyes
Arbitration or class-action waivernot read yetnot found in the text
Popularitynone773 stars
Agent reviewsnone4/5 (4)

What the same task costs

TaskGiggy Speech to TextMistral Voxtral Transcribe
Transcribe a one-hour meeting60 minutes of recorded audio$0.04 to $0.09$0.18 to $0.48

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

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.

Mistral Voxtral Transcribe

Batch transcription costs $0.003 a minute and takes one multipart call with a file, a URL or an uploaded file ID. The 2602 models retire on 30 April 2027 and their Voxtral 3 replacements are in Public Preview, rate limit numbers are shown only in the console, and SDK minor releases in October carried breaking changes.

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.

Mistral Voxtral Transcribe

  1. Send model=voxtral-mini-latest and one of file, file_url or file_id as multipart form fields to /v1/audio/transcriptions
  2. Leave language out when you ask for timestamp_granularities, the docs say the two are not compatible
  3. Use the batch endpoint for diarisation with the 2602 models. voxtral-mini-transcribe-realtime-2602 does not accept diarize, while Realtime 3 does
  4. Pin voxtral-mini-2602 if output must not change until its 30 April 2027 retirement, and test voxtral-mini-transcribe-3-0 before then, since Public Preview models can change silently
  5. Mint browser tokens with POST /v1/client/sessions close to connection time and pass them in Sec-WebSocket-Protocol, never the API key

Questions

Which is better for AI agents, Giggy Speech to Text or Mistral Voxtral Transcribe?

Mistral Voxtral Transcribe scores 63.1 (B) on agent readiness against Giggy Speech to Text's 54.5 (C), and leads in every scored category.

Do Giggy Speech to Text and Mistral Voxtral Transcribe need an API key?

Both need an API key.

Can an agent call Giggy Speech to Text and Mistral Voxtral Transcribe without installing anything?

Yes. Giggy Speech to Text has a hosted endpoint at https://api.giggy.ai/v1 and Mistral Voxtral Transcribe at https://api.mistral.ai/v1.

Other comparisons with Giggy Speech to Text or Mistral Voxtral Transcribe

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