Embedding API · served now

Qwen3 Embedding API — EU-hosted embeddings

A European embedding model API: Qwen3 Embedding behind the OpenAI-compatible /v1/embeddings endpoint, served from hardware AxForge owns in Sweden — with zero prompt retention.

eu-se-1 · Stockholm api.axforge.ai/v1 1024-dim · 32,768 ctx
Get an API key Talk to an engineer Launch pricing. Keys are allocated from the waiting list.

Specifications

What is served

ModelQwen3 Embedding — text embedding model, Qwen3 family
API model nameqwen3-embed
Vector dimensions1024
Context window32,768 tokens
EndpointPOST /v1/embeddings
HardwareNVIDIA DGX Spark (GB10, 128 GB unified memory) — owned and operated by AxForge
Regioneu-se-1 · Stockholm, Sweden — pinned with x-axforge-region, echoed on the response
Pricing€0.015 / 1M tokens (launch pricing)

For quality benchmarks, see the official model card — we publish only numbers we measured ourselves.

Quickstart

OpenAI-compatible — point your SDK at us

curl
$ export OPENAI_BASE_URL=https://api.axforge.ai/v1
$ curl -sS "$OPENAI_BASE_URL/embeddings" \
    -H "Authorization: Bearer $AXFORGE_API_KEY" \
    -H "x-axforge-region: eu-se-1" \
    -H "Content-Type: application/json" \
    -d '{"model":"qwen3-embed",
         "input":["Zero-retention embeddings, computed in Stockholm."]}'
Python
# pip install openai
from openai import OpenAI

client = OpenAI(
    base_url="https://api.axforge.ai/v1",
    api_key="YOUR_AXFORGE_KEY",
    default_headers={"x-axforge-region": "eu-se-1"},
)
r = client.embeddings.create(
    model="qwen3-embed",
    input=["first chunk", "second chunk"],
)
print(len(r.data[0].embedding))  # 1024

Data & privacy

Zero prompt retention

Prompts and completions are processed in memory in Sweden — not written to disk, not logged, not retained, and never used to train anything. That includes every document you send for embedding. We keep only request metadata (token counts, timestamps, status) for billing and operations. The full policy is at axforge.ai/privacy.

FAQ

Qwen3 Embedding API — common questions

Is the embeddings API OpenAI-compatible?

Yes. It is the standard /v1/embeddings shape, so the official OpenAI SDKs work by changing base_url to https://api.axforge.ai/v1. The model name is qwen3-embed.

What vectors does Qwen3 Embedding return?

1024-dimensional vectors, with a 32,768-token context window per input.

Where is the embedding model hosted?

In Stockholm, Sweden (region eu-se-1), on hardware AxForge owns and operates. TLS terminates in the EU. Spain (eu-es-1) is live for the platform; more EU regions are in deployment.

Can I embed GDPR-sensitive documents?

Yes — that is exactly what it is built for. The service is GDPR compliant: EU region, EU-owned hardware, and zero prompt retention — inputs are processed in memory and never persisted or used for training. See the privacy policy.

What does the embeddings API cost?

Launch pricing is €0.015 per million input tokens. For committed volume, talk to an engineer.

Can I build RAG entirely inside the EU with this?

Yes. Pair qwen3-embed for retrieval with Qwen3.8 27B for generation — same API, same key, same EU region.

Ready to build on EU inference?

Get an API key Talk to an engineer

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