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AssemblyAI vs Baseten: Token Pricing, Speed & Intelligence

Full comparison of AssemblyAI and Baseten — live token pricing, latency, throughput, context window, strengths, weaknesses, and best use cases. Rates sourced from public APIs — verify before use.

AssemblyAI

Universal-2 speech-to-text with speaker diarisation and audio intelligence

AssemblyAI provides a speech-to-text and audio intelligence API. Its Universal-2 model offers high-accuracy transcription with built-in speaker diarisation, sentiment analysis, topic detection, and PII redaction. The Nano model targets cost-sensitive batch workloads. Pricing is per audio hour.

TranscriptionSpeaker diarisationSentiment analysisPII redactionMeeting intelligence
Proprietary models

Baseten

Production ML infrastructure — deploy any model with custom serving, autoscaling, and GPU selection

Baseten is a production ML infrastructure platform for deploying custom and open-weight models with full control over serving configuration, GPU selection, autoscaling, and cold-start behavior. Unlike managed inference APIs, Baseten lets you bring your own model weights, custom preprocessing, and serving logic. It supports Truss (Baseten's open-source model packaging format), vLLM, TensorRT-LLM, and custom Python serving code. Ideal for teams that need more control than a managed API but less overhead than raw Kubernetes.

Custom model deploymentFine-tuned modelsML infrastructureProduction servingOpen-weight models
Open-weight hostHosts open weights

Key metric comparison

Cheapest input ($/1M)

$0.00

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Cheapest output ($/1M)

$0.00

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Peak throughput

0 tok/s

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Best latency (TTFT)

800ms

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Intelligence score

0/100

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Context window

0K

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Live token pricing

AssemblyAIlive pricing

← Swipe to see all columns

ModelInputOutput
universal-2$0.00No current price available$0.00
nano$0.00No current price available$0.00
Basetenlive pricing

No live pricing data available.

Strengths and weaknesses

AssemblyAI

Universal-2 includes speaker diarisation, sentiment, topics, and PII redaction out of the box
Audio intelligence features reduce need for post-processing pipelines
Nano tier at $0.10/hour for cost-sensitive batch transcription
LeMUR feature enables LLM-powered Q&A over transcribed audio
Speech and audio only — no general-purpose LLM or image models
Per-hour pricing model differs from token-based LLM APIs
Advanced audio intelligence features add cost on top of base transcription

Baseten

Full control over model serving: custom preprocessing, postprocessing, and business logic
Bring your own weights — deploy any HuggingFace model or custom fine-tune
GPU selection: H100, A100, A10G, T4 with per-second billing
Autoscaling including scale-to-zero for cost efficiency
Truss open-source packaging format for reproducible model deployments
More setup required than managed APIs — not a drop-in OpenAI replacement
Cold starts on scale-to-zero deployments (configurable warm pool available)
Pricing is higher than shared inference APIs for low-volume workloads

Key differentiators

AssemblyAI

Universal-2 bundles transcription with speaker diarisation, sentiment, topic detection, and PII redaction — plus LeMUR for LLM-powered audio Q&A — in a single API call.

Baseten

The production ML platform that gives you managed-API convenience with custom-serving flexibility — deploy any model with your own preprocessing logic, GPU selection, and autoscaling without managing Kubernetes.

Frequently asked questions

AssemblyAI FAQs

How is AssemblyAI priced?

AssemblyAI charges per audio hour. Universal-2 is $0.37/hour and Nano is $0.10/hour. Additional audio intelligence features (diarisation, sentiment, PII redaction) are priced separately. See assemblyai.com/pricing for current rates.

What is Universal-2?

Universal-2 is AssemblyAI's flagship transcription model with built-in speaker diarisation, sentiment analysis, topic detection, and PII redaction. It is designed for meeting intelligence and call analytics use cases.

What is LeMUR?

LeMUR (Leveraging Large Language Models to Understand Recorded Audio) is an AssemblyAI feature that lets you run LLM-powered Q&A, summarisation, and action-item extraction directly over transcribed audio without building a separate pipeline.

Baseten FAQs

What is Baseten?

Baseten is a production ML infrastructure platform for deploying AI models with custom serving logic, GPU selection, and autoscaling. It supports any open-weight model or custom fine-tune via the Truss packaging format.

How does Baseten differ from Together AI or Replicate?

Baseten gives you full control over the serving stack — custom preprocessing, postprocessing, GPU selection, and autoscaling behavior. Together AI and Replicate are managed APIs with fixed serving; Baseten is for teams that need custom model serving logic.

What GPUs does Baseten support?

Baseten supports H100 SXM, H100 PCIe, A100 80GB, A10G, and T4 GPUs with per-second billing. You select the GPU type per deployment based on your model's memory and throughput requirements.

Provider resources

Key strengths compared

AssemblyAI

  • Universal-2 includes speaker diarisation, sentiment, topics, and PII redaction out of the box
  • Audio intelligence features reduce need for post-processing pipelines
  • Nano tier at $0.10/hour for cost-sensitive batch transcription
  • Speech and audio only — no general-purpose LLM or image models
  • Per-hour pricing model differs from token-based LLM APIs

Baseten

  • Full control over model serving: custom preprocessing, postprocessing, and business logic
  • Bring your own weights — deploy any HuggingFace model or custom fine-tune
  • GPU selection: H100, A100, A10G, T4 with per-second billing
  • More setup required than managed APIs — not a drop-in OpenAI replacement
  • Cold starts on scale-to-zero deployments (configurable warm pool available)

Key weaknesses compared

AssemblyAI

  • Speech and audio only — no general-purpose LLM or image models
  • Per-hour pricing model differs from token-based LLM APIs
  • Advanced audio intelligence features add cost on top of base transcription

Baseten

  • More setup required than managed APIs — not a drop-in OpenAI replacement
  • Cold starts on scale-to-zero deployments (configurable warm pool available)
  • Pricing is higher than shared inference APIs for low-volume workloads

Provider category context

AssemblyAI is a frontier lab, founded in 2017. Baseten is a inference api, founded in 2019. AssemblyAI as a frontier lab trains and serves its own proprietary models. Baseten as an inference API provider hosts open-weight models — typically offering lower prices for equivalent capability tiers but without access to proprietary frontier models.

How to choose between them

Choose AssemblyAI if you need Meeting intelligence. Choose Baseten if you need full control over model serving: custom preprocessing, postprocessing, and business logic. For high-volume production workloads, run a cost comparison using the token pricing table above with your actual prompt/completion token ratio — the cheapest provider depends heavily on your input-to-output token ratio.