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AssemblyAI Universal-2

Up to 30%

Transcribe speech with AssemblyAI Universal-2 on LLM.API—batch or streaming audio to text with the same developer surface as your other models.

Start Using API

What is AssemblyAI Universal-2?

With AssemblyAI Universal-2, LLM.API turns audio into text for product voice features. Speech-to-text model by Assemblyai. The model id `universal-2` keeps STT alongside your other endpoints.

Providers

LLM.API routes AssemblyAI Universal-2 to the providers below, with discounted effective rates versus list price.

ProviderPricingContextCapabilities
assemblyai30% offin $0.0025; out — per minute of audio——

Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.

Try this model

Test AssemblyAI Universal-2 right here — free to start.

AssemblyAI Universal-2
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call AssemblyAI Universal-2 through the OpenAI-compatible API — STT via LLM.API (see docs for audio endpoints).

python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_LLMAP_KEY",
    base_url="https://api.llmapi.ai/v1",
)

resp = client.chat.completions.create(
    model="universal-2",
    messages=[
        {"role": "system", "content": "You are a precise product assistant."},
        {"role": "user", "content": "Give me three crisp launch checklist items."},
    ],
)
print(resp.choices[0].message.content)
{
  "model": "universal-2",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Meeting capture

    Fits voice notes, calls, and meeting recording pipelines. Tuned to how teams typically call AssemblyAI Universal-2.

  • Caption generation

    Produces base transcripts for subtitle workflows. Relevant for `universal-2` workloads on LLM.API.

  • Voice UX input

    Powers voice-driven product interfaces and IVR handoffs.

  • Downstream LLM prep

    Feeds transcripts into summarization and action-item extractors. Reflects speech-to-text positioning for this endpoint.

  • Streaming recognition

    Supports low-latency partial transcripts when the provider offers streaming STT. Grounded in the model's stt role rather than generic chat claims.

6 Most Valuable Use Cases

  • Podcast and video caption drafts with AssemblyAI Universal-2
  • Voice command capture in mobile apps
  • Meeting notes and searchable recordings with AssemblyAI Universal-2
  • Call-center transcription and QA
  • Feeding voice input into LLM agents with AssemblyAI Universal-2
  • Live captioning prototypes

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Intelligent AI Routing

    Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.

    One endpoint, every model.

  • Cost-Aware Execution

    Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.

    More performance, less spend.

  • Resilient Fallback Flows

    Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.

    Never go dark on users.

  • Deep LLM Observability

    Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.

    See every token, everywhere.

  • Task-Level Orchestration

    Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.

    Think tasks, not models.

  • High-Throughput Batch APIs

    Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.

    Scale from 1 to millions.

Why run AssemblyAI Universal-2 on LLM.API?

  • Unified AI Routing

    Reach AssemblyAI Universal-2 and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Compare provider price points and keep spend visible as you scale AssemblyAI Universal-2.

  • Reliability Layer

    Practical: Retry and route across configured providers when a single upstream blips.

  • Observability

    Trace prompts, tokens, and errors for AssemblyAI Universal-2 alongside the rest of your stack.

  • Drop-in SDKs

    Production: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.

  • Model Breadth

    Swap AssemblyAI Universal-2 for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

  • You will pipe transcripts into search or LLM summarization (AssemblyAI Universal-2)
  • Voice is a primary input modality in your product (AssemblyAI Universal-2)
  • You need speech-to-text for batch or streaming audio (AssemblyAI Universal-2)

Avoid if...

  • Your audio cannot leave your compliance boundary and you lack an approved provider path
  • You require guaranteed perfect transcripts for every accent without evaluation
  • You need text-to-speech or chat generation instead of transcription

COMMUNITY

What developers say about speech-to-text models

Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to AssemblyAI Universal-2.

  • Head-to-head tests of the leading APIs land within a point or two of each other; the choice usually comes down to language coverage, streaming latency and batch pricing.
  • Voice-agent developers report streaming latency and endpointing quality matter more in production than headline word-error rates.
  • Whisper-family models remain the default open baseline, with hosted providers winning on real-time features and diarization.

SOURCES

Frequently Asked Questions

  • What modalities does AssemblyAI Universal-2 support?

    AssemblyAI Universal-2 accepts audio and produces text according to its architecture metadata on LLM.API.

  • Does AssemblyAI Universal-2 translate speech?

    Primary behavior is transcription to text. Translation—if needed—should be a separate step with a chat model unless the provider explicitly offers it.

  • Where is the canonical page for AssemblyAI Universal-2?

    https://llmapi.ai/models/universal-2/

  • How do I call AssemblyAI Universal-2 via API?

    Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "universal-2" and your LLM.API key. See the code snippet on this page.

  • Which providers serve AssemblyAI Universal-2?

    LLM.API currently lists: assemblyai. Availability can vary by region and account.

  • What is AssemblyAI Universal-2?

    Speech-to-text model by Assemblyai. On LLM.API it is addressed as `universal-2`.

  • Is AssemblyAI Universal-2 a chat model?

    No—AssemblyAI Universal-2 is categorized as a stt model. Use the matching API surface rather than assuming chat completions.

  • What are limitations of AssemblyAI Universal-2?

    Like other API models, AssemblyAI Universal-2 can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.

  • What is the context length for AssemblyAI Universal-2?

    Reported context for AssemblyAI Universal-2 is See provider specs. Always verify the active provider row if multiple providers are listed.

  • When should I choose AssemblyAI Universal-2?

    You will pipe transcripts into search or LLM summarization — especially when you specifically need AssemblyAI Universal-2.

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