Model catalog

Deepgram Flux

API

Deepgram Flux is a transcription model from Deepgram with a 0K-token context window. Provider list price is $0.0015 per minute; on Allocate you pay $0.0016 with the 7% transaction fee. It is a closed model served over API; the weights are not published.

Pricing

Provider listOn Allocate
Price, per minute$0.0015$0.0016

Token usage bills at the provider list price plus the 7% transaction fee. Prices checked 2026-07-08.

Price against its peers

Provider list prices per minute, Deepgram Flux against its nearest transcription peers by price.

What a real workload costs

Transcribing 1,000 minutes of audio costs 1,000 × $0.0015 = $1.50 at list, or $1.60 billed on Allocate with the 7% transaction fee included.

Deepgram Flux is served over API. Route traffic to it by name, meter every token, and swap it out in one click when a better fit ships.

Example usage

Point a route at deepgram/flux and the endpoint never changes; swap the model behind it whenever you want.

api.allocate.network
curl https://api.allocate.network/v1/chat/completions \
  -H "Authorization: Bearer $ALLOCATE_KEY" \
  -d '{
    "model": "deepgram/flux",
    "messages": [{"role": "user",
      "content": "Summarise the attached contract."}]
  }'
200 · deepgram/flux · inside your boundary

Common questions

How much does Deepgram Flux cost?

Provider list price is $0.0015 per minute. On Allocate you pay list plus the 7% transaction fee: $0.0016.

What context window does Deepgram Flux have?

448 tokens (0K). At roughly 0.75 words per token, that is about 0k words of English text per request.

Can I fine-tune Deepgram Flux?

No. Deepgram Flux is a closed model served over API; the weights are not published. If you want a model you can train and own, start from an open-weights base in the catalog and fine-tune that.

How do I call Deepgram Flux on Allocate?

Send deepgram/flux in the model field of the OpenAI-compatible endpoint at api.allocate.network/v1, or point a route name (like prod/support-agent) at it so you can swap the model later without a deploy.