{"slug":"assemblyai","name":"AssemblyAI","domain":"assemblyai.com","verdict":"As of 2026-08-09, Claude, Gemini collectively rank AssemblyAI first for transcription apis for speaker diarization in meetings (one of 8 leaderboards it appears on). Source: https://modelsagree.com/product/assemblyai (modelsagree.com, CC BY 4.0).","best_rank":1,"categories":8,"entries":[{"slug":"best-transcription-apis-for-speaker-diarization-in-meetings","title":"Best transcription APIs for speaker diarization in meetings","rank":1,"of":7,"score":9,"appearances":2,"modelRanks":{"Claude":2,"Gemini":1},"reason":"Exceptional turnkey accuracy for multi-speaker meeting diarization, strong handling of overlapping speech and speaker turn-taking, and unified integration with speech-to-text and LLM meeting intelligence APIs. Near-tie with Deepgram for the top spot, assuming turnkey developer experience and diarization precision take precedence over raw streaming speed.","reasons":[{"model":"Gemini","reason":"Exceptional turnkey accuracy for multi-speaker meeting diarization, strong handling of overlapping speech and speaker turn-taking, and unified integration with speech-to-text and LLM meeting intelligence APIs. Near-tie with Deepgram for the top spot, assuming turnkey developer experience and diarization precision take precedence over raw streaming speed."},{"model":"Claude","reason":"Excellent word-level accuracy with tightly integrated speaker labels, clean developer experience, and meeting-relevant extras (summarization, sentiment, LeMUR-style LLM steps) on the same async job, making it the strongest all-around choice for building a meeting product without stitching tools together."}],"fixes":[{"model":"Claude","fix":"Diarization is solid but not category-leading on many-speaker or heavily overlapping audio, and its best real-time story lags its batch strength — recorded meetings are the sweet spot."},{"model":"Gemini","fix":"Higher per-minute cost than raw model providers and lacks self-hosted deployment options for strict air-gapped enterprise compliance."}],"updated":"2026-08-09","api":"https://modelsagree.com/api/v1/best/best-transcription-apis-for-speaker-diarization-in-meetings.json"},{"slug":"best-ai-transcription-api","title":"Best AI transcription API","rank":2,"of":8,"score":15,"appearances":4,"modelRanks":{"ChatGPT":3,"Claude":2,"Gemini":2,"Grok":2},"reason":"Near-tie with Deepgram — Universal-2 delivers comparable real-world accuracy, and it bundles the richest post-transcription stack (speaker diarization, PII redaction, sentiment, summarization, and the LeMUR layer for LLM operations over transcripts) with excellent documentation, making it the fastest path when you need more than raw text.","reasons":[{"model":"Claude","reason":"Near-tie with Deepgram — Universal-2 delivers comparable real-world accuracy, and it bundles the richest post-transcription stack (speaker diarization, PII redaction, sentiment, summarization, and the LeMUR layer for LLM operations over transcripts) with excellent documentation, making it the fastest path when you need more than raw text."},{"model":"Gemini","reason":"Industry-leading developer experience for post-transcription analysis, offering robust APIs and native Audio Intelligence features like summaries and PII redaction via Universal-3.5 Pro."},{"model":"Grok","reason":"Exceptional developer experience with clean SDKs, built-in audio intelligence (sentiment, topics, entities, summarization via LeMUR), high accuracy on challenging audio, generous free tier/credits for prototyping."},{"model":"ChatGPT","reason":"Universal-3 Pro delivers strong customizable batch transcription across 99 languages, while Universal-3.5 Pro Realtime handles code-switching, contextual prompting, diarization, and voice-focused streaming; clean APIs and rich speech-understanding features make it especially practical."}],"fixes":[{"model":"ChatGPT","fix":"Capability is fragmented across models—flagship realtime language coverage is much narrower than batch, and diarization or other add-ons can raise cost."},{"model":"Claude","fix":"Streaming latency and per-minute cost have historically lagged Deepgram, and its strength is English-centric with narrower language coverage than the hyperscalers or Whisper."},{"model":"Gemini","fix":"Advanced analysis and LLM features require expensive add-on fees, and the API is not optimized for ultra-low-latency conversational streaming."},{"model":"Grok","fix":"Reduce pricing for high-volume streaming/real-time to undercut Deepgram more aggressively on cost-efficiency"}],"updated":"2026-07-13","rank_history":{"days":["2026-07-11","2026-07-12","2026-07-13"],"ranks":[2,2,2]},"reasoning_shift":[{"model":"Gemini","from":"2026-07-12","to":"2026-07-13","added":[{"t":"Expensive add-on fees","q":"Advanced analysis and LLM features require expensive add-on fees"}],"dropped":[{"t":"Sentiment analysis","q":"sentiment analysis"},{"t":"Highly accurate speaker diarization","q":"highly accurate speaker diarization"},{"t":"Pricing closer to Deepgram","q":"pricing closer to Deepgram's hyper-competitive rates"}]},{"model":"Claude","from":"2026-07-12","to":"2026-07-13","added":[{"t":"Sentiment","q":"sentiment"},{"t":"English-centric with narrower language coverage","q":"its strength is English-centric with narrower language coverage than the hyperscalers or Whisper"}],"dropped":[]}],"api":"https://modelsagree.com/api/v1/best/best-ai-transcription-api.json"},{"slug":"best-speech-to-text-api","title":"Best speech-to-text API","rank":2,"of":8,"score":15,"appearances":4,"modelRanks":{"ChatGPT":3,"Claude":2,"Gemini":2,"Grok":2},"reason":"Universal-2 sits at or near the top of independent accuracy benchmarks with the strongest bundled audio intelligence — speaker diarization, PII redaction, sentiment, chapters — plus clean docs and SDKs, so one API covers what elsewhere takes three services.","reasons":[{"model":"Claude","reason":"Universal-2 sits at or near the top of independent accuracy benchmarks with the strongest bundled audio intelligence — speaker diarization, PII redaction, sentiment, chapters — plus clean docs and SDKs, so one API covers what elsewhere takes three services."},{"model":"Gemini","reason":"Unmatched out-of-the-box Audio Intelligence suite (including LeMUR for LLM-powered summarization, speaker diarization, and PII redaction natively integrated) and superior accuracy in specialized technical/medical domains. Near-tie with OpenAI Whisper for batch processing, but wins on feature completeness."},{"model":"Grok","reason":"Top-tier accuracy especially on challenging real-world audio with fewer hallucinations, rich built-in audio intelligence (diarization, topics, PII), strong developer tools for voice agents and analytics"},{"model":"ChatGPT","reason":"Excellent developer experience plus strong transcription, diarization, formatting, language detection, and speech-intelligence features that reduce downstream engineering"}],"fixes":[{"model":"ChatGPT","fix":"Not the best value when only basic high-volume transcription is needed"},{"model":"Claude","fix":"cloud-only with no self-hosted deployment, and real-time streaming is weaker and more English-centric than Deepgram's — wrong choice for on-prem/compliance-bound or latency-critical voice agents."},{"model":"Gemini","fix":"Premium cost structure is significantly more expensive at scale compared to raw transcript competitors, and latency is too high for real-time voice agents."},{"model":"Grok","fix":"Further reduce streaming latency to sub-200ms consistently and expand real-time language/code-switching coverage"}],"updated":"2026-07-15","rank_history":{"days":["2026-06-29","2026-06-30","2026-07-08","2026-07-09","2026-07-10","2026-07-12","2026-07-13","2026-07-14","2026-07-15"],"ranks":[2,2,3,2,1,2,1,2,2]},"reasoning_shift":[{"model":"Gemini","from":"2026-07-14","to":"2026-07-15","added":[{"t":"superior accuracy in specialized domains","q":"superior accuracy in specialized technical/medical domains"},{"t":"Near-tie with OpenAI Whisper","q":"Near-tie with OpenAI Whisper for batch processing"},{"t":"Premium cost structure","q":"Premium cost structure is significantly more expensive at scale compared to raw transcript competitors"}],"dropped":[{"t":"Near-tie with Deepgram","q":"Near-tie with Deepgram"},{"t":"sentiment analysis","q":"sentiment analysis"},{"t":"limited multilingual support","q":"limited multilingual support"}]}],"api":"https://modelsagree.com/api/v1/best/best-speech-to-text-api.json"},{"slug":"best-realtime-speech-to-text-api","title":"Best real-time speech-to-text API","rank":2,"of":9,"score":14,"appearances":4,"modelRanks":{"ChatGPT":3,"Claude":2,"Gemini":2,"Grok":3},"reason":"Near-tie with Deepgram — ~300ms immutable-transcript streaming designed specifically for voice-agent turn-taking (no late revisions to already-emitted words), excellent English accuracy on telephony audio, transparent unlimited-concurrency pricing, and the best developer docs/DX in the category.","reasons":[{"model":"Claude","reason":"Near-tie with Deepgram — ~300ms immutable-transcript streaming designed specifically for voice-agent turn-taking (no late revisions to already-emitted words), excellent English accuracy on telephony audio, transparent unlimited-concurrency pricing, and the best developer docs/DX in the category."},{"model":"Gemini","reason":"Outstanding audio intelligence features (including speaker diarization and sentiment analysis) paired with direct LLM orchestration via LeMUR on highly accurate streams; a near-tie with Deepgram for developer experience when downstream analysis is required."},{"model":"ChatGPT","reason":"Excellent voice-agent accuracy and fast word emission, with strong keyterm prompting, straightforward WebSocket integration, unlimited concurrency, and attractive practitioner-friendly pricing; narrowly trails the leaders mainly on language breadth."},{"model":"Grok","reason":"High accuracy with built-in intelligence (diarization, prompting, NLU-like features), solid sub-300-500ms latency, broad language support, high uptime, and strong developer tooling/pricing tiers; shines for apps needing structured output beyond raw transcription."}],"fixes":[{"model":"ChatGPT","fix":"Its strongest streaming models support only a small set of major languages, making it unsuitable for broadly multilingual products."},{"model":"Claude","fix":"Streaming is effectively English-first (multilingual support much thinner than its async models), and there's no self-hosted option."},{"model":"Gemini","fix":"Higher latency overhead and premium pricing make it less optimal for rapid, sub-300ms conversational loops."},{"model":"Grok","fix":"Latency slightly higher than pure speed leaders in some tests; more focused on combined transcription+intelligence than raw minimal-latency streaming alone."}],"updated":"2026-07-15","api":"https://modelsagree.com/api/v1/best/best-realtime-speech-to-text-api.json"},{"slug":"best-transcription-apis-for-real-time-voice-applications","title":"Best transcription APIs for real-time voice applications","rank":2,"of":8,"score":14,"appearances":4,"modelRanks":{"ChatGPT":2,"Claude":2,"Gemini":4,"Grok":2},"reason":"Near-tie for first on recognition quality, especially names, numbers, emails, and domain terms; combines roughly 150ms post-endpoint latency with semantic endpointing, dynamic keyterm prompting, immutable finals, straightforward WebSockets, and an unusually practical self-hosting option.","reasons":[{"model":"ChatGPT","reason":"Near-tie for first on recognition quality, especially names, numbers, emails, and domain terms; combines roughly 150ms post-endpoint latency with semantic endpointing, dynamic keyterm prompting, immutable finals, straightforward WebSockets, and an unusually practical self-hosting option."},{"model":"Claude","reason":"Universal-Streaming closed the gap with Deepgram on latency (~300ms immutable transcripts) while generally edging it on English accuracy, and its endpointing/turn-detection tuned for voice agents reduces the awkward-interruption problem that plagues LLM voice bots. Strong docs and per-second billing make it easy to adopt. Near-tie with Deepgram — Deepgram wins on price and deployment options, AssemblyAI on out-of-box turn handling."},{"model":"Grok","reason":"Leading accuracy in independent voice-agent benchmarks (lowest WER ~7% and standout entity error rates with context carryover), configurable latency modes, strong NLU integration/diarization/prompting for production apps, handles noisy environments and multilingual switching well; excels for complex conversational flows where correctness and structured output matter most."},{"model":"Gemini","reason":"Excellent developer experience with robust SDKs, offering sub-second latency alongside direct streaming integration with their audio intelligence suite for features like PII redaction."}],"fixes":[{"model":"ChatGPT","fix":"At about $0.45 per session-hour it costs materially more than value-oriented alternatives, while self-hosting requires a substantial commercial commitment."},{"model":"Claude","fix":"Streaming is English-centric (multilingual streaming support lags well behind its batch offering), and there's no self-hosted option for data-residency-constrained teams."},{"model":"Grok","fix":"Higher pricing (~$0.45/hr base) and slightly higher median latency than pure speed leaders; not ideal for ultra-cost-sensitive or extreme-scale simple transcription."}],"updated":"2026-07-18","api":"https://modelsagree.com/api/v1/best/best-transcription-apis-for-real-time-voice-applications.json"},{"slug":"best-speech-to-text-api-for-call-centers","title":"Best speech-to-text API for call centers","rank":2,"of":8,"score":12,"appearances":3,"modelRanks":{"ChatGPT":2,"Claude":2,"Gemini":2},"reason":"Near-tie for first on recorded calls, with excellent messy-speech and entity accuracy, natural-language prompting, keyterms, speaker labeling, PII redaction, and unusually straightforward pricing","reasons":[{"model":"ChatGPT","reason":"Near-tie for first on recorded calls, with excellent messy-speech and entity accuracy, natural-language prompting, keyterms, speaker labeling, PII redaction, and unusually straightforward pricing"},{"model":"Claude","reason":"Universal-2 and Slam-1 models are at or near state-of-the-art WER on noisy phone audio, and it bundles the deepest audio-intelligence stack for call centers — PII/PCI redaction (critical for payment calls), sentiment, topic detection, speaker diarization, and LLM-powered summarization via LeMUR — so a small team gets QA-ready output from one API. Near-tie with Deepgram; it wins if your workload is batch/post-call analytics, loses if it's live agent-assist"},{"model":"Gemini","reason":"Exceptional post-call semantic accuracy and the most mature Audio Intelligence suite, under the assumption that post-call analytics and compliance formatting are prioritized over live agent interactions. Its LeMUR framework allows developers to query transcripts using LLMs natively, and its robust built-in PII redaction and sentiment analysis are highly optimized for QA and analytics workflows."}],"fixes":[{"model":"ChatGPT","fix":"Its strongest model supports far fewer languages than the broad multilingual alternatives"},{"model":"Claude","fix":"Real-time streaming has historically lagged Deepgram in latency and telephony tuning, making it a weaker choice when live captioning or in-call agent assist is the primary use"},{"model":"Gemini","fix":"Real-time streaming latency is too high for interactive, conversational voice bots, making it best suited for asynchronous post-call analytics."}],"updated":"2026-07-15","api":"https://modelsagree.com/api/v1/best/best-speech-to-text-api-for-call-centers.json"},{"slug":"best-cheap-speech-to-text-api","title":"Best cheap speech-to-text API","rank":3,"of":10,"score":5,"appearances":3,"modelRanks":{"ChatGPT":4,"Claude":5,"Gemini":4},"reason":"At $0.21/hour, it pairs strong messy-speech and entity accuracy with prompting, custom spelling, language detection, formatting, and word timestamps; worth the small premium for transcript usability.","reasons":[{"model":"ChatGPT","reason":"At $0.21/hour, it pairs strong messy-speech and entity accuracy with prompting, custom spelling, language detection, formatting, and word timestamps; worth the small premium for transcript usability."},{"model":"Gemini","reason":"Exceptional accuracy on noisy audio and accents for $0.0025/min (Universal-2) or $0.0035/min (Universal-3 Pro Async), combined with robust speaker diarization and audio intelligence tools."},{"model":"Claude","reason":"Aggressive price cuts brought Universal to ~$0.0025-0.003/min (~$0.15/hr) with accuracy competitive with Deepgram and the strongest bundled extras at this price — diarization, sentiment, PII redaction, and audio-intelligence add-ons that would cost extra elsewhere"}],"fixes":[{"model":"ChatGPT","fix":"Supports far fewer languages than Whisper or Speechmatics, and diarization or other intelligence features can raise the effective price."},{"model":"Claude","fix":"Cheapest rates assume prepaid/volume tiers and the add-ons that justify choosing it each bill separately; pure transcription users on small volumes pay more per minute than Groq or gpt-4o-mini-transcribe"},{"model":"Gemini","fix":"Advanced features (like diarization and summarization) carry modular add-on costs that can quickly double or triple the base price."}],"updated":"2026-07-15","api":"https://modelsagree.com/api/v1/best/best-cheap-speech-to-text-api.json"},{"slug":"best-speech-to-text-api-for-medical-transcription","title":"Best speech-to-text API for medical transcription","rank":4,"of":11,"score":5,"appearances":1,"modelRanks":{"Grok":1},"reason":"Lowest missed entity rate (3.2% MER) on medical benchmarks among API providers, strong real-time streaming (<300ms), built-in PII redaction, speaker diarization, BAA/HIPAA support, developer-friendly with audio intelligence features; excels in clinical terminology accuracy for typical practitioner dictation workflows.","reasons":[{"model":"Grok","reason":"Lowest missed entity rate (3.2% MER) on medical benchmarks among API providers, strong real-time streaming (<300ms), built-in PII redaction, speaker diarization, BAA/HIPAA support, developer-friendly with audio intelligence features; excels in clinical terminology accuracy for typical practitioner dictation workflows."}],"fixes":[{"model":"Grok","fix":"Higher cost with Medical Mode add-on; not ideal for teams needing fully structured ambient notes without additional LLM post-processing."}],"updated":"2026-07-15","api":"https://modelsagree.com/api/v1/best/best-speech-to-text-api-for-medical-transcription.json"}],"page":"https://modelsagree.com/product/assemblyai","check":"https://modelsagree.com/check?q=AssemblyAI","updated":"2026-08-10T18:18:45.051Z","attribution":"modelsagree.com, CC BY 4.0"}