AssemblyAI vs Parasail: Token Pricing, Speed & Intelligence
Full comparison of AssemblyAI and Parasail — 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.
Parasail
Serverless inference — Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, Llama 4
Parasail is a serverless LLM inference platform offering a broad catalog of open-weight models including Kimi K3, Kimi K2.6, GLM-5.3, GLM-5.3 Flash, MiniMax M3, DeepSeek V4 Pro/Flash, Qwen3.5 397B-A17B, Qwen3 235B-A22B, Llama 4 Maverick, Llama 3.3 70B, Mistral Small 3.2 24B, MiMo v2.5, Gemma 4 31B, gpt-oss-120b, and gpt-oss-20b. Pricing is published at parasail.io/pricing.
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Live token pricing
Strengths and weaknesses
AssemblyAI
Parasail
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.
One of the broadest serverless open-weight catalogs available — Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, and Llama 4 Maverick at competitive per-token rates.
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.
Parasail FAQs
What is Parasail?
Parasail is a serverless LLM inference platform offering a broad catalog of open-weight models. See parasail.io/pricing for current rates and model availability.
What models does Parasail offer?
Parasail's catalog includes Kimi K3, Kimi K2.6, GLM-5.3, GLM-5.3 Flash, MiniMax M3, DeepSeek V4 Pro/Flash, Qwen3.5 397B-A17B, Qwen3 235B-A22B, Llama 4 Maverick, Llama 3.3 70B, Mistral Small 3.2 24B, MiMo v2.5, Gemma 4 31B, gpt-oss-120b, and gpt-oss-20b. See parasail.io/pricing for current rates.
How much does Parasail cost?
As of October 2026: Kimi K3 $3.00/$15.00, Kimi K2.6 $0.75/$3.50, GLM-5.3 $1.40/$4.40, GLM-5.3 Flash $0.15/$0.50, MiniMax M3 $0.30/$1.20, DeepSeek V4 Pro $1.74/$3.48, DeepSeek V4 Flash $0.14/$0.28. See parasail.io/pricing for current rates.
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.
Parasail — Serverless inference — Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, Llama 4
Parasail is a serverless LLM inference platform offering a broad catalog of open-weight models including Kimi K3, Kimi K2.6, GLM-5.3, GLM-5.3 Flash, MiniMax M3, DeepSeek V4 Pro/Flash, Qwen3.5 397B-A17B, Qwen3 235B-A22B, Llama 4 Maverick, Llama 3.3 70B, Mistral Small 3.2 24B, MiMo v2.5, Gemma 4 31B, gpt-oss-120b, and gpt-oss-20b. Pricing is published at parasail.io/pricing.
One of the broadest serverless open-weight catalogs available — Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, and Llama 4 Maverick at competitive per-token rates.
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
Parasail
- Broad open-weight model catalog: Kimi K3, GLM-5.3, MiniMax M3, DeepSeek V4, Qwen3.5, Llama 4
- Competitive serverless pricing across all tiers
- Kimi K3 and Kimi K2.6 availability — rare outside Chinese providers
- Newer platform — less battle-tested than Together AI or Fireworks
- No proprietary frontier models
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
Parasail
- Newer platform — less battle-tested than Together AI or Fireworks
- No proprietary frontier models
- Smaller community and ecosystem
Provider category context
AssemblyAI is a frontier lab, founded in 2017. Parasail is a inference api, founded in 2023. AssemblyAI as a frontier lab trains and serves its own proprietary models. Parasail 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 Parasail if you need broad open-weight model catalog: kimi k3, glm-5.3, minimax m3, deepseek v4, qwen3.5, llama 4. 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.