Deepgram Whisper Large API: Endpoint & Pricing
Transcribe speech with Deepgram Whisper Large on LLM.API—batch or streaming audio to text with the same developer surface as your other models.
What is Deepgram Whisper Large?
With Deepgram Whisper Large, LLM.API turns audio into text for product voice features. Speech-to-text model by Deepgram. The model id `whisper-large` keeps STT alongside your other endpoints.
Can you self-host Deepgram Whisper Large?
No. We found no public weights for Deepgram Whisper Large on Hugging Face, so there is nothing to download, quantize or serve on your own GPUs: no VRAM budget, no vLLM or GGUF build to plan for. The only way to run it is over an API.
Skip the deploy — use LLM.API as your endpoint
No GPUs, no quantization trade-offs. Same model, OpenAI-compatible, with custom volume discounts on request.
Providers
LLM.API routes Deepgram Whisper Large to the providers below, with discounted effective rates versus list price.
List price by provider
InputOutputProvider list prices; the LLM.API discount applies on top.
| Provider | Pricing | Context | Capabilities |
|---|---|---|---|
| in $0; out — per minute of audio | — | — |
Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 11 Oct 2026.
Try this model
Test Deepgram Whisper Large right here — free to start.
Suggestions for your first prompt
Code snippet
Call Deepgram Whisper Large through the OpenAI-compatible API — STT via LLM.API (see docs for audio endpoints).
Switching from OpenAI? Change 2 lines.
- base_url="https://api.openai.com/v1"
- api_key="YOUR_OPENAI_KEY"
+ base_url="https://api.llmapi.ai/v1"
+ api_key="YOUR_LLMAPI_KEY"Everything else stays the same — SDK, message format, tools, streaming. Set model to whisper-large and the call runs unchanged.
curl https://api.llmapi.ai/v1/chat/completions \
-H "Authorization: Bearer $LLMAPI_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "whisper-large",
"messages": [
{"role": "user", "content": "Give me three crisp launch checklist items."}
]
}'from openai import OpenAI
client = OpenAI(
api_key="YOUR_LLMAPI_KEY",
base_url="https://api.llmapi.ai/v1",
)
resp = client.chat.completions.create(
model="whisper-large",
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)import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.LLMAPI_KEY,
baseURL: "https://api.llmapi.ai/v1",
});
const resp = await client.chat.completions.create({
model: "whisper-large",
messages: [
{ role: "user", content: "Give me three crisp launch checklist items." },
],
});
console.log(resp.choices[0].message.content);stream = client.chat.completions.create(
model="whisper-large",
messages=[{"role": "user", "content": "Write a haiku about latency."}],
stream=True,
)
for chunk in stream:
delta = chunk.choices[0].delta.content
if delta:
print(delta, end="", flush=True){
"model": "whisper-large",
"messages": [
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."}
]
}ENDPOINTS
Supported endpoints & features
Base URL https://api.llmapi.ai/v1 · model ID whisper-large · OpenAI-compatible.
POST /v1/chat/completionsChat Completions — supported
| Feature | Status | How to set it |
|---|---|---|
| Function calling (tools) | Not supported | tools, tool_choice |
| Parallel tool calls | Not supported | parallel_tool_calls |
| JSON mode | Not supported | response_format: {"type": "json_object"} |
| Structured outputs | Not supported | response_format: {"type": "json_schema", …} |
| Streaming | Not supported | stream: true |
| Vision (image input) | Not supported | image_url content parts |
| Web search | Not supported | web_search |
ERRORS
Errors & fallback routing
| Code | What it means | What to do |
|---|---|---|
401 | Missing or invalid API key. | Send Authorization: Bearer YOUR_LLMAPI_KEY and check the key is active. |
429 | Rate limited, or the upstream provider is throttling the request. | Back off and retry with jitter; the gateway also retries the request on another provider where one is available. |
5xx | Upstream provider error or timeout. | Retry; fallback routing sends the retry to the next healthy provider for this model. |
When a provider fails or throttles, the request is routed to the next provider serving this model — the ones listed in the providers table above.
Deepgram Whisper Large in production
What the model is good at.
Speech transcription
Converts spoken audio into text for captions, notes, and search. 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.
Multilingual audio
Handles diverse accents and languages depending on the model.
Compliance archives
Creates text records of spoken interactions for audit trails. Tuned to how teams typically call Deepgram Whisper Large.
Voice UX input
Powers voice-driven product interfaces and IVR handoffs.
What you get when you call Deepgram Whisper Large through LLM.API.
Unified AI Routing
Reach Deepgram Whisper Large and sibling models through one OpenAI-compatible endpoint.
One endpoint, every model.Cost Control
Compare provider price points and keep spend visible as you scale Deepgram Whisper Large.
More performance, less spend.Reliability Layer
Practical: Retry and route across configured providers when a single upstream blips.
Never go dark on users.Observability
Production: Trace prompts, tokens, and errors for Deepgram Whisper Large alongside the rest of your stack.
See every token, everywhere.Drop-in SDKs
Practical: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Think tasks, not models.Model Breadth
Swap Deepgram Whisper Large for chat, media, or embedding alternatives without rewriting auth.
Scale from 1 to millions.
When to Use — When NOT to Use
Use it if...
- You will pipe transcripts into search or LLM summarization (Deepgram Whisper Large)
- You need speech-to-text for batch or streaming audio (Deepgram Whisper Large)
- Voice is a primary input modality in your product (Deepgram Whisper Large)
Avoid if...
- You require guaranteed perfect transcripts for every accent without evaluation
- You need text-to-speech or chat generation instead of transcription
- 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 Deepgram Whisper Large.
- 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
What is the context length for Deepgram Whisper Large?
Reported context for Deepgram Whisper Large is See provider specs. Always verify the active provider row if multiple providers are listed.
Is Deepgram Whisper Large a chat model?
No—Deepgram Whisper Large is categorized as a stt model. Use the matching API surface rather than assuming chat completions.
Where is the canonical page for Deepgram Whisper Large?
https://llmapi.ai/models/openai-whisper-large/
Does Deepgram Whisper Large 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 Whisper Large support?
Deepgram Whisper Large accepts audio and produces text according to its architecture metadata on LLM.API.
What is Deepgram Whisper Large?
Speech-to-text model by Deepgram. On LLM.API it is addressed as `whisper-large`.
How do I call Deepgram Whisper Large via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "whisper-large" and your LLM.API key. See the code snippet on this page.
Which providers serve Deepgram Whisper Large?
LLM.API currently lists: deepgram. Availability can vary by region and account.
COMPARE
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