Bonus: Top up now and we'll double your first deposit — get x2 credits instantly.
Get Started
Sign Up
Sign Up

Deepgram Base Phone Call

Up to 30%

Deepgram Base Phone Call brings speech-to-text speech-to-text to LLM.API for voice notes, calls, and caption pipelines.

Start Using API

What is Deepgram Base Phone Call?

Deepgram Base Phone Call is a speech-to-text model on LLM.API (`base-phonecall`). Speech-to-text model by Deepgram. Feed audio and receive text transcripts for captions, agents, and searchable archives.

Providers

LLM.API routes Deepgram Base Phone Call to the providers below, with discounted effective rates versus list price.

ProviderPricingContextCapabilities
deepgram30% offin $0.0125; out — per minute of audio——

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

Try this model

Test Deepgram Base Phone Call right here — free to start.

Deepgram Base Phone Call
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Deepgram Base Phone Call 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="base-phonecall",
    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": "base-phonecall",
  "messages": [
    {"role": "system", "content": "You are a precise product assistant."},
    {"role": "user", "content": "Give me three crisp launch checklist items."}
  ]
}

5 Core Capabilities

  • Multilingual audio

    Handles diverse accents and languages depending on the model. Grounded in the model's stt role rather than generic chat claims.

  • Voice UX input

    Powers voice-driven product interfaces and IVR handoffs.

  • Streaming recognition

    Supports low-latency partial transcripts when the provider offers streaming STT. Reflects speech-to-text positioning for this endpoint.

  • Meeting capture

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

  • Caption generation

    Produces base transcripts for subtitle workflows. Tuned to how teams typically call Deepgram Base Phone Call.

6 Most Valuable Use Cases

  • Voice command capture in mobile apps with Deepgram Base Phone Call
  • Compliance recording text archives
  • Meeting notes and searchable recordings with Deepgram Base Phone Call
  • Podcast and video caption drafts
  • Feeding voice input into LLM agents with Deepgram Base Phone Call
  • Clinical or field note dictation workflows

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 Deepgram Base Phone Call on LLM.API?

  • Unified AI Routing

    Practical: Reach Deepgram Base Phone Call and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Practical: Compare provider price points and keep spend visible as you scale Deepgram Base Phone Call.

  • Reliability Layer

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

  • Observability

    Trace prompts, tokens, and errors for Deepgram Base Phone Call 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 Deepgram Base Phone Call 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 (Deepgram Base Phone Call)
  • Voice is a primary input modality in your product (Deepgram Base Phone Call)
  • You need speech-to-text for batch or streaming audio (Deepgram Base Phone Call)

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 Deepgram Base Phone Call.

  • 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

  • Can I use tools or structured outputs with Deepgram Base Phone Call?

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

  • How do I call Deepgram Base Phone Call via API?

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

  • How is Deepgram Base Phone Call priced on LLM.API?

    Listed pricing metadata shows: In $12.5 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.

  • What is Deepgram Base Phone Call?

    Speech-to-text model by Deepgram. On LLM.API it is addressed as `base-phonecall`.

  • When should I choose Deepgram Base Phone Call?

    You will pipe transcripts into search or LLM summarization — especially when you specifically need Deepgram Base Phone Call.

  • Where is the canonical page for Deepgram Base Phone Call?

    https://llmapi.ai/models/base-phonecall/

  • Which providers serve Deepgram Base Phone Call?

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

  • Is Deepgram Base Phone Call a chat model?

    No—Deepgram Base Phone Call is categorized as a stt model. Use the matching API surface rather than assuming chat completions.

  • Does Deepgram Base Phone Call 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.

  • What modalities does Deepgram Base Phone Call support?

    Deepgram Base Phone Call accepts audio and produces text according to its architecture metadata on LLM.API.

  • What is the context length for Deepgram Base Phone Call?

    Reported context for Deepgram Base Phone Call is See provider specs. Always verify the active provider row if multiple providers are listed.

  • What are limitations of Deepgram Base Phone Call?

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

COMPARE

Competitive Models

Get one key to every model

Swap your API key. Keep your code.

Start for free Talk to sales