LLM Reference

Qwen3.5-397B-A17B

Released
2026-02-16
Last refreshed
2026-06-29
Status
Researched 43d ago
Open sourceCommercial use: permittedMultimodalCodingRAGAgentsLong contextVisionClassificationJSON / Tool use

Qwen3.5-397B-A17B is worth evaluating for coding, rag, and agents when its provider route and context window match the workload.

Use it for

  • Teams evaluating coding, rag, and agents
  • Workloads that can use a 262k context window
  • Buyers comparing 4 tracked provider routes

Do not use it for

  • Workloads where another current model has stronger sourced task evidence
Specifications
Family
Qwen3.5
Released
2026-02-16
Context
262k
Parameters
397B
Architecture
Mixture of Experts
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Weights
Available
Code
Unknown
Created by

AI research institute of Alibaba Group.

Hangzhou, Zhejiang, China
Founded 2017
Website
Pricing
Output / 1M
$2.34
Input / 1M
$0.390

Cheapest of 4 routes · Alibaba Cloud PAI-EAS

About

Alibaba's largest Qwen3.5 model, featuring a Mixture-of-Experts architecture with 397B total parameters and 17B active per token (using 512 total experts with 10 routed + 1 shared active). Supports 201 languages with a native 262K token context window extensible to 1M tokens via YaRN. Includes a thinking/reasoning mode, tool calling with MCP integration, and unified vision-language capabilities through early fusion training.

Qwen3.5-397B-A17B is an open-source model in the Qwen3.5 family. The structured metadata tracks a 262k-token context window, multimodal input, reasoning, function calling, tool use, and structured outputs. This page tracks provider routes through OpenRouter, Together AI, Alibaba Cloud PAI-EAS, and 1 more, with the cheapest tracked route listed at $0.39 input and $2.34 output per 1M tokens. Headline tracked benchmarks include Google-Proof Q&A 89.3, MMLU PRO 87.8, and Massive Multi-discipline Multimodal Understanding 85.0.

Top use-case fit: coding, agents, and build tasks

Coding

Q/$ C

2 relevant benchmarks in the decision map.

RAG

Included by capability and metadata signals in the decision map.

Agents

Q/$ C

4 relevant benchmarks in the decision map.

Provider price ladder

Compare all 4

Compare API pricing across 4 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Alibaba Cloud PAI-EAS$0.390$2.34
Serverless
OpenRouter$0.390$2.34
Serverless
Novita AI$0.600$3.60
Serverless
Together AI$0.600$3.60
Serverless

Available via routers & gateways(1)

Capabilities

VisionMultimodalReasoningFunction CallingTool UseStructured Outputs

Benchmark peer barsfor Coding

Benchmark scores(13)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionSource
Google-Proof Q&A89.3diamondArtificial Analysis
MMLU PRO87.8From official HuggingFace model card (accuracy)https://huggingface.co/Qwen/Qwen3.5-397B-A17B
Massive Multi-discipline Multimodal Understanding85.0https://huggingface.co/Qwen/Qwen3.5-397B-A17B
Instruction-Following Evaluation92.6https://huggingface.co/Qwen/Qwen3.5-397B-A17B
BFCL72.9v4https://huggingface.co/Qwen/Qwen3.5-397B-A17B
SWE-bench Verified76.2SWE-bench Verifiedhttps://benchlm.ai/benchmarks/sweVerified
AIME 202691.3AIME 2026 (accuracy)https://huggingface.co/Qwen/Qwen3.5-397B-A17B
Berkeley Function Calling Leaderboard v372.9BFCL-V4, from official model card (accuracy)https://huggingface.co/Qwen/Qwen3.5-397B-A17B
Humanity's Last Exam28.7HLE with CoT, no tools, from official model card (accuracy)https://huggingface.co/Qwen/Qwen3.5-397B-A17B
LiveCodeBench83.6LiveCodeBench v6 (pass@1)https://huggingface.co/Qwen/Qwen3.5-397B-A17B
MultiChallenge67.6Multi-Challenge leaderboard rank 2 of 28 (accuracy%)https://llm-stats.com/benchmarks/multichallenge
τ-bench86.7TAU2-Bench, from official model card (accuracy)https://huggingface.co/Qwen/Qwen3.5-397B-A17B
Terminal-Bench 2.052.5Terminal-Bench 2.0 (accuracy%)https://llm-stats.com/benchmarks/terminal-bench-2

Migration checks

No linked migration route is available for this model yet.

Compare Qwen3.5-397B-A17B with other models

Show all 53 popular comparisonssorted by 7-day search impressions
Qwen3.5-397B-A17B vs Claude Haiku 4.534Qwen3.5-397B-A17B vs GLM-5 Turbo30Qwen3.5-397B-A17B vs Llama 3 8B Instruct30Qwen3.5-397B-A17B vs GPT-4o29Qwen3.5-397B-A17B vs Claude 3.7 Sonnet27Qwen3.5-397B-A17B vs Mistral Medium 3.526Qwen3.5-397B-A17B vs DeepSeek V3.125Qwen3.5-397B-A17B vs Grok 424Qwen3.5-397B-A17B vs Mistral Large 221Qwen3.5-397B-A17B vs Qwen2.5-72B-Instruct20Qwen3.5-397B-A17B vs Llama 3 70B Instruct20Qwen3.5-397B-A17B vs GLM-4V 9B18Qwen3.5-397B-A17B vs Llama 3.2 11B Vision16Qwen3.5-397B-A17B vs Qwen2-VL-72B-Instruct15Qwen3.5-397B-A17B vs Gemma 7B Instruct15Qwen3.5-397B-A17B vs Grok 4.315Qwen3.5-397B-A17B vs Claude Opus 4.513Qwen3.5-397B-A17B vs o313Qwen3.5-397B-A17B vs DeepSeek V312Qwen3.5-397B-A17B vs Phi-3 Mini 4k12Qwen3.5-397B-A17B vs Llama 3.1 70B Instruct12Qwen3.5-397B-A17B vs Qwen3.5-Flash12Qwen3.5-397B-A17B vs Gemini 3 Pro12Qwen3.5-397B-A17B vs GPT-5.3-Codex-Spark12Qwen3.5-397B-A17B vs DeepSeek R111Qwen3.5-397B-A17B vs GPT-5.211Qwen3.5-397B-A17B vs GPT-5.510Qwen3.5-397B-A17B vs Phi 3.5 Vision Instruct9Qwen3.5-397B-A17B vs Gemini 2.5 Flash9Qwen3.5-397B-A17B vs DeepSeek R1 05288Qwen3.5-397B-A17B vs GPT Realtime 27Qwen3.5-397B-A17B vs gpt-realtime-1.57Qwen3.5-397B-A17B vs Gemini 3.1 Flash-Lite7Qwen3.5-397B-A17B vs Qwen3.5-35B-A3B6Qwen3.5-397B-A17B vs GPT-5.5-Cyber6Qwen3.5-397B-A17B vs Llama 3.2 1B Instruct6Qwen3.5-397B-A17B vs GPT-5.5 Instant6Qwen3.5-397B-A17B vs Llama 3.2 90B Vision5Qwen3.5-397B-A17B vs GPT Realtime Translate4Qwen3.5-397B-A17B vs Claude Mythos Preview4Qwen3.5-397B-A17B vs Llama 2 13B Chat4Qwen3.5-397B-A17B vs Trinity-Large-Thinking3Qwen3.5-397B-A17B vs o3 Mini3Qwen3.5-397B-A17B vs Mistral Medium 3 Instruct3Qwen3.5-397B-A17B vs GPT-5.4 Pro3Qwen3.5-397B-A17B vs Gemini 2.5 Pro3Qwen3.5-397B-A17B vs Grok-33Qwen3.5-397B-A17B vs gpt-realtime3Qwen3.5-397B-A17B vs Mistral Large 2 (2407)2Qwen3.5-397B-A17B vs Mistral Medium 31Qwen3.5-397B-A17B vs Phi-3 Silica1Qwen3.5-397B-A17B vs DeepSeek R1 Lite1Qwen3.5-397B-A17B vs Mixtral 8x7B0

Frequently asked questions

What is the context window of Qwen3.5-397B-A17B?

Qwen3.5-397B-A17B has a context window of 262k tokens.

How much does Qwen3.5-397B-A17B cost?

Qwen3.5-397B-A17B pricing ranges from $0.39/1M to $0.6/1M input tokens depending on the provider.

When was Qwen3.5-397B-A17B released?

Qwen3.5-397B-A17B was released on 2026-02-16.

Which providers offer Qwen3.5-397B-A17B?

Qwen3.5-397B-A17B is available from 4 providers: OpenRouter, Together AI, Alibaba Cloud PAI-EAS, Novita AI.

What benchmarks has Qwen3.5-397B-A17B been tested on?

Qwen3.5-397B-A17B has been evaluated on 13 benchmarks, including Google-Proof Q&A, MMLU PRO, Massive Multi-discipline Multimodal Understanding, Instruction-Following Evaluation, BFCL.