Dedicated model · deployable on request

Qwen3.6 35B A3B — dedicated hosting in Europe

Name: Qwen3.6 35B A3B dedicated hosting
Brand: AxForge

A mixture-of-experts Qwen with roughly 3B active parameters per token, validated on AxForge hardware and deployed on a dedicated DGX Spark for your traffic only. Not on the shared API today.

On request eu-se-1 · Stockholm 86.3 t/s · community @ 4k

Talk to an engineer Qwen3.8 27B — served now Monthly rental. Pricing on request.

Specifications

The model

Model	Qwen3.6 35B A3B — mixture-of-experts, latest Qwen generation
Served model name	qwen3.6-35b-a3b-nvfp4
Architecture	MoE — 35B total, roughly 3B active parameters per token
Context window	65,536 tokens
Quantization	NVFP4
Availability	Deployable on request — not on the shared API today
Hardware	NVIDIA DGX Spark (GB10, 128 GB unified memory) — owned and operated by AxForge
Region	eu-se-1 · Stockholm, Sweden
Pricing	On request — talk to an engineer

Performance

Community benchmark — labelled, not ours

Metric	Value	Condition
Decode speed (community)	86.3 tokens/s	SparkBench PBM @ 4k context, single GB10, NVFP4 + MTP

Community measurement from SparkBench — MoE with ~3B active parameters per token is a natural fit for GB10. We haven't published our own tuned numbers yet. More on the GB10 page; for quality benchmarks, see the official model card.

Deployment

What "deployable on request" means

System	A dedicated NVIDIA DGX Spark (GB10, 128 GB unified memory), reserved for you
Commercial model	Monthly rental
Endpoint	OpenAI-compatible /v1 on your own machine — only your traffic
Location	Hosted in the EU (eu-se-1 · Stockholm, Sweden)
Data handling	Zero prompt retention, same policy as the shared API

The model is validated on AxForge hardware and brought hot on your system. After deployment — and only then — your endpoint speaks the OpenAI API:

Post-deployment sketch — not the shared API

# After your dedicated node is live. This does not work on api.axforge.ai today.
from openai import OpenAI

client = OpenAI(base_url="https://<your-endpoint>/v1", api_key="<your-key>")
r = client.chat.completions.create(
    model="qwen3.6-35b-a3b-nvfp4",
    messages=[{"role": "user", "content": "Hello from your own machine"}],
)

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. We keep only request metadata (token counts, timestamps, status) for billing and operations. The full policy is at axforge.ai/privacy.

FAQ

Qwen3.6 35B A3B hosting — common questions

Is Qwen3.6 35B A3B on the shared AxForge API?

No. It is not on the shared API today. It is deployable on request: validated on AxForge hardware and brought hot on a dedicated DGX Spark for your traffic only. The shared API serves Qwen3.8 27B.

What does A3B mean?

Qwen3.6 35B A3B is a mixture-of-experts model: 35B total parameters, roughly 3B active per token. That is why its single-stream decode is faster than a dense model of similar size.

How fast is Qwen3.6 35B A3B on your hardware?

On the community SparkBench leaderboard (PBM methodology, 4k context, single GB10), this model with NVFP4 + MTP measures 86.3 tokens/s single-stream. We haven't published our own tuned numbers yet.

What does a dedicated Qwen deployment look like?

A dedicated NVIDIA DGX Spark (GB10, 128 GB unified memory) rented monthly, running Qwen3.6 35B A3B behind an OpenAI-compatible endpoint on your own machine, hosted in the EU with zero prompt retention.

What does dedicated Qwen hosting in the EU cost?

Pricing on request — talk to an engineer and we will quote the monthly rental.

Which Qwen model can I use through the API today?

Qwen3.8 27B is served now on the shared API at €0.29 per 1M input tokens and €1.77 per 1M output tokens (launch pricing).