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AssemblyAI Whisper RT

Up to 30%

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

Start Using API

What is AssemblyAI Whisper RT?

With AssemblyAI Whisper RT, LLM.API turns audio into text for product voice features. Streaming speech-to-text model by Assemblyai. The model id `whisper-rt` keeps STT alongside your other endpoints.

Providers

LLM.API routes AssemblyAI Whisper RT to the providers below, with discounted effective rates versus list price.

ProviderPricingContextCapabilities
assemblyai30% offin $0.005; out — per minute of audio——

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

Try this model

Test AssemblyAI Whisper RT right here — free to start.

AssemblyAI Whisper RT
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Code snippet

Call AssemblyAI Whisper RT 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="whisper-rt",
    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": "whisper-rt",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • 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.

  • Caption generation

    Produces base transcripts for subtitle workflows. Grounded in the model's stt role rather than generic chat claims.

  • Voice UX input

    Powers voice-driven product interfaces and IVR handoffs.

  • Meeting capture

    Fits voice notes, calls, and meeting recording pipelines. Grounded in the model's stt role rather than generic chat claims.

  • Speech transcription

    Converts spoken audio into text for captions, notes, and search. Grounded in the model's stt role rather than generic chat claims.

6 Most Valuable Use Cases

  • Compliance recording text archives with AssemblyAI Whisper RT
  • Voice command capture in mobile apps
  • Feeding voice input into LLM agents with AssemblyAI Whisper RT
  • Call-center transcription and QA
  • Clinical or field note dictation workflows with AssemblyAI Whisper RT
  • 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 Whisper RT on LLM.API?

  • Unified AI Routing

    Practical: Reach AssemblyAI Whisper RT and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Practical: Compare provider price points and keep spend visible as you scale AssemblyAI Whisper RT.

  • Reliability Layer

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

  • Observability

    Production: Trace prompts, tokens, and errors for AssemblyAI Whisper RT alongside the rest of your stack.

  • Drop-in SDKs

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

  • Model Breadth

    Swap AssemblyAI Whisper RT 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 Whisper RT)
  • You need speech-to-text for batch or streaming audio (AssemblyAI Whisper RT)
  • Voice is a primary input modality in your product (AssemblyAI Whisper RT)

Avoid if...

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

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 Whisper RT.

  • 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

  • Which providers serve AssemblyAI Whisper RT?

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

  • What modalities does AssemblyAI Whisper RT support?

    AssemblyAI Whisper RT accepts audio and produces text according to its architecture metadata on LLM.API.

  • What is the context length for AssemblyAI Whisper RT?

    Reported context for AssemblyAI Whisper RT is See provider specs. Always verify the active provider row if multiple providers are listed.

  • Can I use tools or structured outputs with AssemblyAI Whisper RT?

    Tooling support varies; for pure stt models, prefer the modalities listed rather than assuming chat tools.

  • When should I choose AssemblyAI Whisper RT?

    You need speech-to-text for batch or streaming audio — especially when you specifically need AssemblyAI Whisper RT.

  • What is AssemblyAI Whisper RT?

    Streaming speech-to-text model by Assemblyai. On LLM.API it is addressed as `whisper-rt`.

  • Where is the canonical page for AssemblyAI Whisper RT?

    https://llmapi.ai/models/openai-whisper-rt/

  • Is AssemblyAI Whisper RT a chat model?

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

  • How do I call AssemblyAI Whisper RT via API?

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

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