The verdict
Groq appears in 2 AI-ranked categories — best position #1 for cheap speech-to-text api.
Positioning brief — for the Groq team
Why the models put Groq at #1 for cheap speech-to-text api
- accurate multilingual transcription Claude · GPT“accurate multilingual transcription at $0.04/hour”
- extremely fast inference Claude · GPT · Gemini“extremely fast inference”
- nothing hosted comes close on price Claude · GPT · Gemini“nothing hosted comes close on price-per-accurate-minute”
- easy OpenAI-compatible API GPT“an easy OpenAI-compatible API make it unusually practical”
What would move the rank — the models’ fix lines, unified
- no streaming GPT · Claude“no streaming”
- bare-bones feature set GPT · Claude“bare-bones feature set”
- strict rate limits Claude · Gemini“strict rate limits on request concurrency and volume”
Restructured from verbatim model output · nothing invented · every quote machine-verified
Cheapest hosted transcription that's still genuinely accurate — roughly $0.04/hour (~$0.0007/min) for OpenAI's Whisper large-v3-turbo weights served on Groq's LPUs, with faster-than-real-time turnaround measured in seconds; for the typical developer batch-transcribing podcasts, calls, or user audio, nothing hosted comes close on price-per-accurate-minute
GPT Near-tied for first: accurate multilingual transcription at $0.04/hour, extremely fast inference, and an easy OpenAI-compatible API make it unusually practical.
Gemini Delivers near-instantaneous transcription speed (up to 200x real-time) at $0.00067/min for Whisper Large V3 Turbo, using highly optimized LPU hardware.
Where Groq falls short, per the models
- GPT File transcription rather than true streaming, with minimum-duration billing and fewer speech-specific features than specialist APIs.
- Claude Batch/pre-recorded only with a bare-bones feature set — no streaming, weak diarization, and rate limits on lower tiers make it wrong for real-time voice agents or enterprise SLAs
- Gemini Subject to strict rate limits on request concurrency and volume, making it difficult to scale without enterprise negotiation.
Top alternatives per the models: Cloudflare Workers AI · AssemblyAI · Deepgram · DeepInfra
Unmatched token generation throughput and latency via LPU architecture (consistently 300–800+ tokens/sec), making it the gold standard for real-time voice agents and multi-step agentic execution loops.
Grok Unmatched real-world latency and throughput via custom LPU silicon (often 300-800+ tok/s and sub-150ms TTFT on supported models), competitive pricing relative to the speed advantage, OpenAI-compatible, zero cold-start feel on curated menu, excellent for interactive/real-time/voice/coding agents where every token compounds; near-tie with Fireworks when latency is the dominant constraint
GPT Exceptional token-generation speed and low latency on supported models, straightforward OpenAI-compatible integration, competitive token pricing, and discounted batch processing make it the strongest choice for latency-sensitive interactive applications.
Claude Unmatched tokens/sec and time-to-first-token via custom LPU hardware; when interactive latency or high-throughput agentic loops dominate, nothing serverless is faster, with clean OpenAI-compatible API and low per-token cost
Where Groq falls short, per the models
- GPT The curated model catalog and hardware-specific support are substantially narrower than Fireworks or Together, limiting model choice and customization.
- Claude Narrow curated model menu and periodic capacity/rate limits — not for teams needing a long tail of models or guaranteed dedicated capacity
- Gemini Restricted model selection constrained by on-chip SRAM capacity, with no capability for hosting custom model architectures or dynamic serverless LoRA adapters.
- Grok Narrow curated model list with limited/no custom weights or fine-tuning, plus occasional capacity constraints at peak
Poll history — On this board 10 of 10 polls since Jun 29 · #3 the last 7
#3 → #1 → #4 → #3 → #3 → #3 → #3 → #3 → #3 → #3
What changed in the models’ minds
ClaudeJul 14 → Aug 14 poll
- Newtime-to-first-token
- Newclean OpenAI-compatible API
- Droppedslow-moving model menu
- Droppedno custom-model or fine-tuned deployment“no custom-model or fine-tuned deployment support”
GrokJul 12 → Aug 14 poll
- Newcompetitive pricing relative to the speed advantage
- NewOpenAI-compatible
- Newlimited custom weights and peak capacity constraints“limited/no custom weights or fine-tuning, plus occasional capacity constraints at peak”
GeminiJul 15 → Aug 14 poll
- Newmulti-step agentic execution loops
- Newmodel selection constrained by on-chip SRAM“Restricted model selection constrained by on-chip SRAM capacity”
- Newcustom model architectures or serverless LoRA“no capability for hosting custom model architectures or dynamic serverless LoRA adapters”
- DroppedHigh rate limits
+1 more change
Top alternatives per the models: Fireworks AI · Together AI · DeepInfra · Cerebras
Head-to-head — how the models call it
Watch Groq
Boards re-poll weekly and the models change their minds. One short email only when Groq's standing moves — a rank change, a rival overtaking, or new reasoning from the models. Nothing otherwise.
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Groq ranks #1 for best cheap speech-to-text api by AI-model consensus. Put the badge in your README, docs or site — it updates automatically as the models re-rank.
[](https://modelsagree.com/best/best-cheap-speech-to-text-api?utm_source=badge&utm_medium=embed&utm_campaign=badge-groq)<a href="https://modelsagree.com/best/best-cheap-speech-to-text-api?utm_source=badge&utm_medium=embed&utm_campaign=badge-groq"><img src="https://modelsagree.com/badge/groq.svg" alt="Groq — ranked #1 for Best cheap speech-to-text API by AI models on ModelsAgree" height="28"></a>Rankings are computed from what the models answer, re-polled on demand · raw reasoning shown verbatim · methodology