Deepgram Whisper Tiny API: Endpoint & Pricing
Transcribe speech with Deepgram Whisper Tiny on LLM.API—batch or streaming audio to text with the same developer surface as your other models.
What is Deepgram Whisper Tiny?
With Deepgram Whisper Tiny, LLM.API turns audio into text for product voice features. Speech-to-text model by Deepgram. The model id `whisper-tiny` keeps STT alongside your other endpoints.
Can you self-host Deepgram Whisper Tiny?
No. We found no public weights for Deepgram Whisper Tiny 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 Tiny 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 Tiny right here — free to start.
Suggestions for your first prompt
Code snippet
Call Deepgram Whisper Tiny 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-tiny 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-tiny",
"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-tiny",
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-tiny",
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-tiny",
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-tiny",
"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-tiny · 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 Tiny in production
What the model is good at.
Streaming recognition
Supports low-latency partial transcripts when the provider offers streaming STT. Grounded in the model's stt role rather than generic chat claims.
Multilingual audio
Handles diverse accents and languages depending on the model. Grounded in the model's stt role rather than generic chat claims.
Downstream LLM prep
Feeds transcripts into summarization and action-item extractors. Grounded in the model's stt role rather than generic chat claims.
Voice UX input
Powers voice-driven product interfaces and IVR handoffs. Grounded in the model's stt role rather than generic chat claims.
Compliance archives
Creates text records of spoken interactions for audit trails. Relevant for `whisper-tiny` workloads on LLM.API.
What you get when you call Deepgram Whisper Tiny through LLM.API.
Unified AI Routing
Practical: Reach Deepgram Whisper Tiny and sibling models through one OpenAI-compatible endpoint.
One endpoint, every model.Cost Control
Production: Compare provider price points and keep spend visible as you scale Deepgram Whisper Tiny.
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 Tiny 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
Production: Swap Deepgram Whisper Tiny 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 need speech-to-text for batch or streaming audio (Deepgram Whisper Tiny)
- You will pipe transcripts into search or LLM summarization (Deepgram Whisper Tiny)
- Voice is a primary input modality in your product (Deepgram Whisper Tiny)
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 Whisper Tiny.
- 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 Tiny?
Reported context for Deepgram Whisper Tiny is See provider specs. Always verify the active provider row if multiple providers are listed.
How do I call Deepgram Whisper Tiny via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "whisper-tiny" and your LLM.API key. See the code snippet on this page.
Does Deepgram Whisper Tiny 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.
Where is the canonical page for Deepgram Whisper Tiny?
https://llmapi.ai/models/openai-whisper-tiny/
When should I choose Deepgram Whisper Tiny?
Voice is a primary input modality in your product — especially when you specifically need Deepgram Whisper Tiny.
How is Deepgram Whisper Tiny priced on LLM.API?
Listed pricing metadata shows: In $4.8 / 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.
Which providers serve Deepgram Whisper Tiny?
LLM.API currently lists: deepgram. Availability can vary by region and account.
What is Deepgram Whisper Tiny?
Speech-to-text model by Deepgram. On LLM.API it is addressed as `whisper-tiny`.
Can I use tools or structured outputs with Deepgram Whisper Tiny?
Tooling support varies; for pure stt models, prefer the modalities listed rather than assuming chat tools.
Does Deepgram Whisper Tiny support streaming?
Streaming depends on the active provider; check the providers table on this page for flags.
What are limitations of Deepgram Whisper Tiny?
Like other API models, Deepgram Whisper Tiny 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
Deepgram Whisper Large
Input$0.0048 / minuteList price per minute of audio.
$0.0048 in / — out per minute of audio, context varies — the closest current alternative to Deepgram Whisper Tiny.
Deepgram Nova 3 Multilingual
Input$0.0052 / minuteList price per minute of audio.
$0.0052 in / — out per minute of audio, context varies — the closest current alternative to Deepgram Whisper Tiny.
ElevenLabs Scribe v2
Input$0.0037 / minuteList price per minute of audio.
$0.0037 in / — out per minute of audio, context varies — the closest current alternative to Deepgram Whisper Tiny.
Get one key to every model
Swap your API key. Keep your code.