Nvidia Nemotron 3.5 Asr

Nvidia Nemotron 3.5 Asr

Playground

NVIDIA Nemotron 3.5 ASR is a fast AI speech-to-text model that transcribes multilingual audio into text with automatic language detection. Ready-to-use REST inference API for audio transcription, podcast processing, video subtitles, meeting notes, voice analytics, content localization, and professional ASR workflows with simple integration, no coldstarts, and affordable pricing.

Features

NVIDIA Nemotron 3.5 ASR

NVIDIA Nemotron 3.5 ASR is a multilingual speech-to-text model that transcribes uploaded audio into text with automatic language detection. It is designed for audio transcription, podcast processing, subtitle preparation, meeting notes, voice analytics, localization workflows, and other production-ready ASR use cases.

Why Choose This?

• Multilingual speech recognition
  Transcribe spoken audio into text across multiple languages.

• Automatic language detection
  Leave language on auto when you want the model to detect the spoken language automatically.

• Simple transcription workflow
  Upload one audio file, optionally choose a language, and generate the transcript.

• Useful for content and productivity workflows
  Suitable for podcasts, subtitles, interviews, lectures, meetings, and other spoken-content pipelines.

• Production-ready API
  Easy to integrate into transcription, indexing, search, and accessibility workflows.

Parameters

How to Use

1. Upload your audio — provide the audio clip you want to transcribe.
2. Choose language (optional) — leave it as auto for automatic detection, or select a fixed language if needed.
3. Submit — run the model and get the transcription result.

Example Output

{ “output”: “Ah, the garden is blooming again just like life with a little patience and care, everything finds its time to shine.” }

Pricing

Pricing is billed per started minute of input audio.

Billing Rules

• Pricing is $0.008 per started minute
• Audio duration is billed in started 60-second units
• Audio shorter than 60 seconds is billed as 1 minute
• language does not affect pricing

Best Use Cases

• Audio transcription — Convert speech recordings into text.
• Podcast processing — Generate transcripts for episodes and clips.
• Subtitle preparation — Extract spoken content before caption formatting.
• Meeting notes — Turn recorded discussions into readable text.
• Voice analytics — Prepare transcripts for search, tagging, or downstream analysis.

Pro Tips

• Use clean audio for better transcription accuracy.
• Leave language as auto when the spoken language is clear and consistent.
• Set a specific language when automatic detection may be ambiguous.
• Short clips are useful for fast testing before processing longer recordings.
• Review the output before publishing if the audio contains names, jargon, or strong accents.

Notes

• audio is required.
• language is optional.
• Pricing is based on input audio duration and billed per started minute.
• Better audio quality generally improves transcription quality.

Related Models

• Other NVIDIA speech and multimodal workflows — Useful when you need text, audio, video, or vision processing beyond ASR.
• Text-to-speech workflows — Useful when you need voice generation instead of transcription.
• Subtitle and caption workflows — Useful when you need styled subtitle output rather than plain transcript text.

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/nvidia/nemotron-3.5-asr" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "language": "auto"
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"