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Deepgram Nova 2

Up to 30%

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

Start Using API

What is Deepgram Nova 2?

Deepgram Nova 2 is a speech-to-text model on LLM.API (`nova-2`). Speech-to-text model by Deepgram. Feed audio and receive text transcripts for captions, agents, and searchable archives.

Providers

LLM.API routes Deepgram Nova 2 to the providers below, with discounted effective rates versus list price.

ProviderPricingContextCapabilities
deepgram30% offin $0.0043; out — per minute of audio——

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

Try this model

Test Deepgram Nova 2 right here — free to start.

Deepgram Nova 2
Hi! Want to test the model?

Suggestions for your first prompt

Code snippet

Call Deepgram Nova 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="nova-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": "nova-2",
  "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. Tuned to how teams typically call Deepgram Nova 2.

  • Meeting capture

    Fits voice notes, calls, and meeting recording pipelines.

  • Speech transcription

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

  • Voice UX input

    Powers voice-driven product interfaces and IVR handoffs.

  • Caption generation

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

6 Most Valuable Use Cases

  • Podcast and video caption drafts with Deepgram Nova 2
  • Clinical or field note dictation workflows
  • Voice command capture in mobile apps with Deepgram Nova 2
  • Call-center transcription and QA
  • Meeting notes and searchable recordings with Deepgram Nova 2
  • Compliance recording text archives

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 Nova 2 on LLM.API?

  • Unified AI Routing

    Reach Deepgram Nova 2 and sibling models through one OpenAI-compatible endpoint.

  • Cost Control

    Compare provider price points and keep spend visible as you scale Deepgram Nova 2.

  • Reliability Layer

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

  • Observability

    Production: Trace prompts, tokens, and errors for Deepgram Nova 2 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 Nova 2 for chat, media, or embedding alternatives without rewriting auth.

When to Use — When NOT to Use

Use it if...

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

Avoid if...

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

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 Nova 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

  • Where is the canonical page for Deepgram Nova 2?

    https://llmapi.ai/models/amazon-nova-2/

  • Does Deepgram Nova 2 support streaming?

    Streaming depends on the active provider; check the providers table on this page for flags.

  • Is Deepgram Nova 2 a chat model?

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

  • What modalities does Deepgram Nova 2 support?

    Deepgram Nova 2 accepts audio and produces text according to its architecture metadata on LLM.API.

  • When should I choose Deepgram Nova 2?

    You need speech-to-text for batch or streaming audio — especially when you specifically need Deepgram Nova 2.

  • Which providers serve Deepgram Nova 2?

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

  • Does Deepgram Nova 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.

  • What is Deepgram Nova 2?

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

  • How is Deepgram Nova 2 priced on LLM.API?

    Listed pricing metadata shows: In $4.3 / 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 are limitations of Deepgram Nova 2?

    Like other API models, Deepgram Nova 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.

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