NEAR AI Cloud: Embeddings, Images, Audio & More
Use NEAR AI Cloud for embeddings, reranking, image generation, audio transcription, and PII detection — all inside TEEs
NEAR AI Cloud is not limited to chat completions. The NEAR AI Cloud Gateway (cloud-api.near.ai) serves specialized TEE-hosted models for embeddings, reranking, scoring, image generation, audio transcription, and privacy classification.
Gateway responses include an X-Request-Id response header. Support may ask you for that opaque value when debugging a request. It is support/debugging metadata, not W3C traceparent or distributed trace context. If you send your own X-Request-Id, use a non-sensitive UUID value; X-Request-Id values must not contain secrets or PII. X-Org-Id and X-Workspace-Id are internal tenant headers; public clients cannot set or override them.
Embeddings
Generate vector embeddings with Qwen/Qwen3-Embedding-0.6B:
curl https://cloud-api.near.ai/v1/embeddings \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "Qwen/Qwen3-Embedding-0.6B",
"input": "NEAR AI Cloud runs models inside TEEs."
}'
The response follows the OpenAI embeddings format (data[0].embedding is the vector). input also accepts an array of strings for batch embedding.
Reranking
Score documents against a query with Qwen/Qwen3-Reranker-0.6B:
curl https://cloud-api.near.ai/v1/rerank \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "Qwen/Qwen3-Reranker-0.6B",
"query": "what is the capital of France",
"documents": [
"Paris is the capital of France",
"Berlin is in Germany"
]
}'
{
"id": "rerank-b9390698eab7e1c3",
"model": "Qwen/Qwen3-Reranker-0.6B",
"results": [
{ "index": 0, "relevance_score": 0.914, "document": { "text": "Paris is the capital of France" } },
{ "index": 1, "relevance_score": 0.828, "document": { "text": "Berlin is in Germany" } }
]
}
Results are ordered by relevance_score; index refers to the position in your input documents array.
Image Generation
Generate images with black-forest-labs/FLUX.2-klein-4B (billed per image — see the Models page):
curl https://cloud-api.near.ai/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "black-forest-labs/FLUX.2-klein-4B",
"prompt": "a red circle on a white background",
"n": 1
}'
The response returns the generated image as base64 in data[0].b64_json. An /v1/images/edits endpoint is also available for image-to-image editing.
Audio Transcription
Transcribe audio with openai/whisper-large-v3 (multipart form upload, OpenAI-compatible):
curl https://cloud-api.near.ai/v1/audio/transcriptions \
-H "Authorization: Bearer YOUR_API_KEY" \
-F [email protected] \
-F model=openai/whisper-large-v3
{ "text": "Hello, this is a test recording.", "id": "trans-9a1799eb395047e7ad4aef8b" }
PII Detection & Redaction
The openai/privacy-filter model detects personally identifiable information (names, emails, phone numbers, ...) in text. It is not a chat model — it exposes dedicated privacy endpoints:
Classify returns labeled character spans with confidence scores:
curl https://cloud-api.near.ai/v1/privacy/classify \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "openai/privacy-filter",
"input": "My name is John Smith and my email is [email protected]"
}'
{
"id": "pt-9d83003f2d164dde9edcc0f7",
"model": "openai/privacy-filter",
"data": [{
"index": 0,
"spans": [
{ "category": "private_person", "start": 10, "end": 21, "text": " John Smith", "score": 0.999 },
{ "category": "private_email", "start": 37, "end": 54, "text": " [email protected]", "score": 0.999 }
]
}]
}
Redact (gateway only) returns the text with PII replaced:
curl https://cloud-api.near.ai/v1/privacy/redact \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "openai/privacy-filter",
"input": "My name is John Smith and my email is [email protected]"
}'
input accepts a string or an array of strings for both endpoints.
/v1/privacy/redact is gateway-only and is served at https://cloud-api.near.ai/v1.
Vision (Image Input)
Qwen/Qwen3-VL-30B-A3B-Instruct accepts images in standard OpenAI chat format (image_url content parts) on /v1/chat/completions. Check input_modalities in /v1/models to see which models accept images.