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qwen/qwen3.5-397b-a17b

Nebius AI/🇪🇺 EU/chat

Multimodal model featuring a Hybrid Mixture-of-Experts architecture, designed for state-of-the-art performance across chat, retrieval-augmented generation, vision-language understanding, video understanding, and agentic workflows.More

Which id to call

nebius/qwen/qwen3.5-397b-a17b

This exact deployment on Nebius AI, with no routing and no failover. Send it as the model field.

Input /1M

$0.60

Nebius AI

Output /1M

$3.60

6.0x input

Context

128K

tokens

Added

Feb 2026

chat

Capabilities 4/8

VisionReasoningTool callingCachingWeb searchJSON schemaComputer useImage generation

Provider rates

What qwen/qwen3.5-397b-a17b costs

Provider prices per 1M tokens, updated November 2, 2026.more

These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.

Input /1M

$0.60

Output /1M

$3.60

Cache write /1M

-

Cache read /1M

-

What a workload costs

100K input + 10K output
$0.0960
1M input + 100K output
$0.96
10M input + 1M output
$9.60

At the rates above. This endpoint does not offer prompt caching, so repeated context is billed as new input every time.

OpenAI compatible

Call it in three lines

Change the base url, use your Requesty key, set the model to nebius/qwen/qwen3.5-397b-a17b. Existing OpenAI SDK code needs no other edit.

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from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="nebius/qwen/qwen3.5-397b-a17b", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)

Reference

Specs and data terms

What the catalog reports for this deployment, and what the provider does with the traffic.

Context window128K tokens
Max output-
API typechat
AddedFeb 2026
Model id
Data retentionNone
Used for trainingNo
Served from🇪🇺 EU

Public leaderboards

Benchmark scores

Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.

No benchmarks are published for this exact variant yet.

Region-specific deployments and highspeed tiers usually share scores with their base model. Try the base model page or the Nebius AI models overview.

Same provider

More from Nebius AI

Newest first, on the same provider and the same key.

Reference

qwen/qwen3.5-397b-a17b questions

How much does qwen/qwen3.5-397b-a17b cost?

qwen/qwen3.5-397b-a17b is priced at $0.60 per million input tokens and $3.60 per million output tokens when accessed via Requesty. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.

What is the context window of qwen/qwen3.5-397b-a17b?

qwen/qwen3.5-397b-a17b has a context window of 128K tokens. That's roughly 171 words of input you can fit in a single prompt.

What can qwen/qwen3.5-397b-a17b do?

qwen/qwen3.5-397b-a17b supports vision input, tool calling, extended reasoning, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.

How do I use qwen/qwen3.5-397b-a17b with the OpenAI SDK?

Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "nebius/qwen/qwen3.5-397b-a17b". The Quickstart above shows Python, JavaScript and cURL snippets.

Can I run qwen/qwen3.5-397b-a17b through Requesty?

Yes. qwen/qwen3.5-397b-a17b runs through Requesty's OpenAI-compatible API, served from Nebius AI. You do not host the model yourself: point base_url at Requesty, set the model to "nebius/qwen/qwen3.5-397b-a17b", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

Call qwen/qwen3.5-397b-a17b through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.

All Nebius AI models