Groq (hosted Whisper) vs OpenAI Whisper (API)

On the heaviest attribute, batch price per audio minute, Groq charges 0.002 dollars versus OpenAI's 0.006 dollars, a 3x cost advantage that is decisive at scale for high call volumes. Groq also offers a 50% volume discount batch option, which could push costs even lower. Both tools lack speaker diarizationdiarization - Splitting a transcript by speaker, so you can see who said what., PII redaction, and sentiment analysis equally, so those attributes cancel out. OpenAI holds an edge on concurrency, scaling to 10,000 RPM at Tier 5, but cost dominates this use case at a weight of 5 out of 5. The margin is narrow rather than clear because the missing diarization and PII redaction hurt both tools equally, and concurrency gives OpenAI a real operational advantage at high volumes.

On pricing, Groq charges 0.002 dollars per audio minute versus 0.006 dollars for OpenAI, making Groq 3x cheaper, which is decisive given that batch price carries the heaviest weight. On websocket streaming both tools score equally with no support. On official SDKs, OpenAI offers Python, JS/TS,.NET, Ruby, Java, and Go while Groq offers only Python and JS/TS, giving OpenAI a clear SDK breadth advantage. On word-level timestampsword-level timestamps - The API reports exactly when each word is spoken in the audio, for subtitles and highlighting. and supported audio formats, both tools are identical. Pricing dominates at weight 4 out of 5 and Groq wins that attribute decisively, offsetting OpenAI's SDK advantage.

The deciding attributes for this use case are platform support for dictation apps, local versus cloud processing, AI formatting features, app pricing, and app integrations. The available facts cover API pricing, accuracy, and compliance, but say nothing about dictation-specific platform coverage, local on-device processing capabilities, AI formatting or editing features, one-time versus subscription app pricing, or app integrations for either tool. Groq does support self-hostingself-host - Run the software on your own servers instead of the vendor’s cloud. while OpenAI does not, which hints at local processing potential, but no facts confirm dictation-app platform support or formatting features for either. With the most important attributes entirely unaddressed, neither tool can be declared a winner.

The heaviest attribute for clinical transcription under US healthcare privacy law is HIPAA BAAHIPAA BAA - A signed Business Associate Agreement that lets you handle protected health information under US healthcare privacy law. availability. OpenAI Whisper API has a verified HIPAA BAA, while no such fact exists for Groq. This is a gate-level requirement: without a BAA, Groq cannot be used for covered healthcare data under HIPAA. On the next two equally weighted attributes, both tools tie on PII redaction (neither supports it) and custom vocabulary (both support it). Both also qualify on SOC 2 Type II. On self-hosting, Groq has an edge. But none of these secondary factors can override the absence of a BAA at weight 5 out of 5, which is the definitive gate for this use case.

Both tools score identically on the two heaviest attributes: neither supports speaker diarizationdiarization - Splitting a transcript by speaker, so you can see who said what. and neither offers a summarization endpoint, so those decisive criteria cancel out. Moving to the next tier, Groq supports 99 languages versus 57 for OpenAI, a meaningful advantage for multilingual meetings. On file size, Groq allows up to 100 MB per request on its dev tier while OpenAI caps at 25 MB, which matters for longer recorded meetings. Word-level timestamps are available on both. With Groq leading on two of the remaining attributes and trailing on none, it edges ahead despite the top two criteria being a wash.

For self-hostedself-host - Run the software on your own servers instead of the vendor’s cloud. deployment, the two heaviest attributes are the self-host option and the model weights license. Groq's hosted Whisper explicitly supports a self-host and on-premises option, while OpenAI's API does not offer any self-host or on-premises option at all. On the weights license, OpenAI Whisper carries an MIT license, meaning the weights are freely usable, but the API product itself blocks self-hosting entirely. Groq's offering, which runs Whisper-compatible infrastructure, does permit self-hosted deployment. The self-host option attribute carries a weight of 5 out of 5 and Groq wins it outright, making it the decisive factor even before considering any other attributes.

For live voice agent transcription, the two most critical attributes are streaming latency and websocket streaming support. Both tools report no websocket streaming API available, and neither publishes a verified streaming latency figure. Without these decisive facts favoring either tool, the heaviest weighted attributes cannot break the deadlock. On the next tier, concurrencyconcurrency - How many phone calls the platform can handle at the same time. data exists only for OpenAI at 500 RPM on tier 1, which is a point in its favor, but both tools tie on custom vocabulary support. Neither tool is positioned well for this use case, and the facts do not differentiate them on the attributes that matter most.