AssemblyAI vs StepFun: Token Pricing, Speed & Intelligence
Full comparison of AssemblyAI and StepFun — 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.
StepFun
Step-5 — Chinese frontier LLM with strong multimodal and reasoning capability
StepFun is a Chinese AI startup developing the Step model series. Step-5 Preview is the frontier tier, competing with top Chinese and international models on reasoning and multimodal benchmarks. Step-3.7 Flash is the efficient tier for cost-sensitive workloads. StepFun is backed by Tencent and focuses on enterprise and developer API access.
Key metric comparison
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Live token pricing
Strengths and weaknesses
AssemblyAI
StepFun
Key differentiators
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.
Step-5 is StepFun's frontier reasoning model with multimodal capability, backed by Tencent — positioned as a competitive alternative to Qwen and ERNIE for Chinese enterprise workloads.
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.
StepFun FAQs
What is StepFun?
StepFun is a Chinese AI startup backed by Tencent, developing the Step model series. Step-5 Preview is the frontier tier and Step-3.7 Flash is the efficient tier, both available via the StepFun API.
How much does the StepFun API cost?
Step-5 Preview is $1.00/$2.70 per 1M input/output tokens. Step-3.7 Flash is $0.20/$1.15 per 1M tokens. See platform.stepfun.com/docs/pricing for current rates.
Does Step-5 support multimodal input?
Yes. Step-5 Preview supports text, image, and video understanding in a single API call, making it suitable for multimodal enterprise applications.
Provider resources
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.
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.
StepFun — Step-5 — Chinese frontier LLM with strong multimodal and reasoning capability
StepFun is a Chinese AI startup developing the Step model series. Step-5 Preview is the frontier tier, competing with top Chinese and international models on reasoning and multimodal benchmarks. Step-3.7 Flash is the efficient tier for cost-sensitive workloads. StepFun is backed by Tencent and focuses on enterprise and developer API access.
Step-5 is StepFun's frontier reasoning model with multimodal capability, backed by Tencent — positioned as a competitive alternative to Qwen and ERNIE for Chinese enterprise workloads.
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
StepFun
- Step-5 Preview is competitive with top Chinese frontier models on reasoning benchmarks
- Step-3.7 Flash at $0.20/$1.15 per 1M tokens offers strong value for efficient inference
- Multimodal capability on Step-5 (text, image, video understanding)
- Newer entrant — smaller track record than established frontier labs
- Documentation and support primarily in Chinese
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
StepFun
- Newer entrant — smaller track record than established frontier labs
- Documentation and support primarily in Chinese
- Limited international ecosystem and third-party integrations
Provider category context
AssemblyAI is a frontier lab, founded in 2017. StepFun is a frontier lab, founded in 2023. Both are frontier lab providers — the comparison is primarily about pricing, model selection, and feature differentiation within the same tier.
How to choose between them
Both AssemblyAI and StepFun are frontier labs with proprietary models. Choose based on benchmark performance for your specific task: AssemblyAI leads on universal-2 includes speaker diarisation, sentiment, topics, and pii redaction out of the box, while StepFun leads on step-5 preview is competitive with top chinese frontier models on reasoning benchmarks. For cost-sensitive workloads, compare the cheapest model tier from each provider in the pricing table above — the gap between efficient-tier models is often larger than between flagship models.