Qwen3.5-397B-A17B delivers frontier-level multimodal intelligence with only 17B active parameters per token — making it the most efficient way for developers to access excellent capabilities for vision-language tasks and agentic workflows. On Novita AI, you get OpenAI-compatible API access at $0.60/$3.60 per 1M tokens, with 99.5% uptime SLA and no infrastructure management.
Quick Answer: Qwen3.5-397B-A17B is ideal for production multimodal applications requiring vision-language understanding, agent workflows, and multilingual support. With Novita’s serverless API, you’re running in under 2 minutes with zero GPU provisioning.
Model Architecture of Qwen3.5-397B-A17B
Qwen3.5-397B-A17B combines several breakthrough architectural innovations into a native multimodal foundation model that processes text, images, and video through unified early-fusion training.
| Component | Specification |
|---|---|
| Total Parameters | 403B |
| Active Parameters | 17B per token |
| MoE Architecture | 512 experts, 10 routed + 1 shared active |
| Attention Mechanism | Gated DeltaNet + Global Attention |
| Context Window | 262,144 tokens (native) |
| Multimodal Support | Text, Image, Video |
| Languages | 201 languages/dialects |
The model uses a 60-layer structure with 15 blocks, each containing 3 Gated DeltaNet + MoE layers followed by 1 Gated Attention + MoE layer. Gated DeltaNet layers handle 64 linear attention heads for values and 16 for query-key pairs, dramatically reducing the quadratic complexity of traditional attention. Traditional gated attention (32 heads for queries, 2 for key-values) appears only once every four blocks, optimizing decoding throughput. This design achieves 8.6x speedup at 32K context and 19x speedup at 256K context compared to Qwen3-Max, making it practical for real-time applications requiring long-context processing.
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Benchmarks of Qwen3.5-397B-A17B
| Benchmark | Score | Relative Position | What It Suggests |
|---|---|---|---|
| MultiChallenge | 67.6 | above GPT 5.2 & Gemini 3 Pro | Strong multi-step task coordination |
| NOVA-63 | 59.1 | Top tier | Robust cross-lingual reasoning |
| PolyMATH | 73.3 | Only below Gemini 3 Pro | Strong cross-language symbolic reasoning |
| WMT24++ | 78.9 | Top tier | Reliable semantic alignment |
| MMLU-ProX | 84.7 | Top tier | Stable cross-language factual reasoning |
| BrowseComp | 69.0 / 78.6 | Top tier | Retrieval + synthesis strength |
| SecCodeBench | 68.3 | Only below GPT 5.2 | Code safety reasoning |
| LongBench v2 | 63.2 | 3rd | Long-context integration stability |
Qwen3.5’s strongest relative advantages appear in complex task integration and multilingual reasoning, where it reaches or leads the top tier, including outperforming GPT5.2 and Gemini-3 Pro on MultiChallenge and NOVA-63. It remains consistently competitive in multilingual knowledge, translation, browsing-based synthesis, and secure coding. Overall, it fits a profile of a cross-lingual, multi-step coordination model with broad generalization rather than single-domain peak dominance.
Strengths of Qwen3.5-397B-A17B
1. Multimodal & Vision-Language Applications
The model outperforms GPT-4 and Gemini 3 Pro on instruction following and visual reasoning tasks. Ideal for document understanding, visual QA systems, video analysis pipelines, and multimodal RAG applications.
2. Agentic Workflows & Tool Use
Competitive with top models in agentic tool use tasks. The model’s instruction-following accuracy makes it well-suited for autonomous agent systems, API orchestration, and complex multi-step workflows.
3. High-Throughput Inference
With faster decoding than Qwen3-Max, the model handles high-concurrency production workloads efficiently. Perfect for customer-facing chatbots, real-time video analysis, and batch processing pipelines.
4. Multilingual Global Deployment
Native support for 201 languages with strong WMT24++ scores makes this the go-to choice for international applications requiring multilingual understanding and translation.
Running Qwen3.5-397B-A17B on Novita AI
Novita AI provides serverless OpenAI-compatible API access with zero infrastructure management. You’re running production workloads in under 2 minutes.
Novita is listed as one of the top providers on Hugging Face.
Pricing & Cost Analysis
| Tier | Input Cost | Output Cost | Best For |
|---|---|---|---|
| Novita AI | $0.60 / 1M tokens | $3.60 / 1M tokens | Production inference, high uptime SLA |
Cost Example: Processing 10,000 multimodal queries (avg 1K input + 500 output tokens each) = $24 total ($6 input + $18 output). With the model’s 50 tokens/second throughput, expect 10 seconds per query on average.
Step 1: Log In and Access the Model Library
Log in to your account and click on the Model Library button.
Step 2: Choose Your Model
Browse through the available options and select the model that suits your needs.
Step 3: Start Your Free Trial
Begin your free trial to explore the capabilities of the selected model.
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Step 4: Get Your API Key
To authenticate with the API, we will provide you with a new API key. Entering the “Settings“ page, you can copy the API key as indicated in the image.
Step 5: Install the API
After installation, import the necessary libraries into your development environment. Initialize the API with your API key to start interacting with Novita AI LLM. This is an example of using chat completions API for python users.
from openai import OpenAI
client = OpenAI(
api_key="<Your API Key>",
base_url="https://api.novita.ai/openai"
)
response = client.chat.completions.create(
model="qwen/qwen3.5-397b-a17b",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello, how are you?"}
],
max_tokens=64000,
temperature=0.7
)
print(response.choices[0].message.content)Easily connect Novita AI with partner platforms like Claude Code, Trae, Continue, Codex, OpenCode, AnythingLLM, LangChain, Dify, Langflow, and OpenClaw using API integrations and step-by-step setup guides.
Multimodal Inputs (Image & Video) of Qwen3.5-397B-A17B
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Why Choose Novita AI for Qwen3.5-397B-A17B
| Advantage | Details |
|---|---|
| Cost-Effective | $0.60/$3.60 per 1M tokens with transparent pay-as-you-go billing, no minimum commitment |
| Zero Infrastructure Management | Serverless API handles auto-scaling, load balancing, GPU provisioning — you write code, Novita handles ops |
| OpenAI-Compatible | Drop-in replacement — change base URL, keep existing code. Same SDK, same API format |
| Production-Grade Reliability | 99.5% uptime SLA, redundant GPU clusters, enterprise-grade infrastructure |
| Global Compliance | SOC 2 compliant, data encryption in transit and at rest, no training on customer data |
| Fast Model Updates | New models added within days of release — always access to latest AI capabilities |
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Performance Optimization Tips
1. Context Window Management
Stick to the native 262K context window for optimal speed. YaRN RoPE scaling to 1M tokens adds latency overhead — only use for tasks explicitly requiring ultra-long context.
2. Handle Verbosity
Given the model’s high verbosity, always set `max_tokens` limits. For concise outputs, add explicit instructions: “Answer in 3 bullet points” or use temperature < 0.5.
3. Batch Processing
Leverage Novita’s serverless auto-scaling for batch workloads. Process multiple requests concurrently — the platform handles load balancing across GPU clusters automatically.
4. Multimodal Preprocessing
For image/video inputs, ensure URLs are publicly accessible or use base64 encoding. Compress large videos before API calls to reduce transfer time.
5. Error Handling & Retries
Implement exponential backoff for rate limits. Novita provides 99.5% uptime SLA, but always handle transient errors gracefully in production code.
Bottom Line: For developers building multimodal applications, agentic workflows, or multilingual systems, Qwen3.5-397B-A17B on Novita AI offers the best balance of capability, speed, and cost. Start with the OpenAI-compatible API — you’re running in 2 minutes with production-ready infrastructure.
Frequently Asked Questions
Is Qwen3.5-397B-A17B suitable for long-context tasks?
Yes. Qwen3.5-397B-A17B supports a 262K native context window, allowing it to handle long documents, retrieval pipelines, and complex multi-step tasks efficiently.
How do I run Qwen3.5-397B-A17B on Novita AI?
You can deploy Qwen3.5-397B-A17B on Novita AI through an OpenAI-compatible API by generating an API key, selecting the model in the platform, and calling it using standard chat completions code.
What is Qwen3.5-397B-A17B best used for?
Qwen3.5-397B-A17B is designed for multimodal applications such as document understanding, visual reasoning, multilingual tasks, and agentic workflows that require strong instruction following.
Novita AI is an AI & agent cloud platform helping developers and startups build, deploy, and scale models and agentic applications with high performance, reliability, and cost efficiency.
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