Nano GPT logo
NanoGPT
Provider logo

Qwen3.5 397B A17B Thinking

qwen/qwen3.5-397b-a17b-thinking
BackTry Model
Provider logo

Qwen3.5 397B A17B Thinking

qwen/qwen3.5-397b-a17b-thinking
BackTry Model

Qwen 3.5's open-source 397B MoE model (17B active params) with hybrid linear attention and extended reasoning. Supports text, image, and video input with a 256K context window.

Added Feb 16, 2026

Model weights

Context Window

258.0K

Max Output

65.5K

Avg output tokens (7d)

2.4K tokens

84%

Input Price (Auto)

$0.63/1M

Output Price (Auto)

$3.78/1M

Cache Read (Auto)

$0.31/1M

Capabilities

Benchmarks

Performance metrics and benchmarks

Sourced from Artificial Analysis.

Intelligence Index

33.7

Better than 82% of models compared

Coding Index

48.2

Better than 67% of models compared

Agentic Index

19.8

Better than 55% of models compared

Reasoning

GPQA Diamond

Graduate-level scientific reasoning

89.3%

Better than 94% of models compared

HLE

Humanity's Last Exam

27.3%

Better than 91% of models compared

IFBench

Instruction-following benchmark

78.8%

Better than 97% of models compared

T²-Bench Telecom

Conversational AI agents in dual-control scenarios

95.6%

Better than 95% of models compared

AA-LCR

Long context reasoning evaluation

65.7%

Better than 86% of models compared

GDPval-AA

Economically valuable tasks

23.2%

CritPt

Research-level physics reasoning

1.7%

Coding

SciCode

Python programming for scientific computing

42.0%

Better than 84% of models compared

Terminal-Bench Hard

Agentic coding and terminal use

40.9%

Better than 89% of models compared

Knowledge

AA-Omniscience Accuracy

Proportion of correctly answered questions

30.8%

AA-Omniscience Hallucination Rate

Rate of incorrect answers among non-correct responses

88.9%

Last updated Jun 28, 2026

Artificial Analysis

Providers

Choose explicit providers for this model. Auto routing remains available as the default option.

Loading provider options…

Compare Qwen3.5 397B A17B Thinking with similar models from the same provider or model family.

Qwen3.5 397B A17B

qwen/qwen3.5-397b-a17b

Qwen 3.5's open-source 397B MoE model (17B active params) with hybrid linear attention. Supports text, image, and video input with a 256K context window.

Qwen3.6 35B A3B Thinking

Qwen/Qwen3.6-35B-A3B:thinking

Qwen3.6 35B A3B is a native vision-language MoE model with hybrid attention. Compared to Qwen3.5 35B A3B, Alibaba reports stronger agentic coding, mathematical and code reasoning, and better spatial understanding (including object localization and detection).

Qwen3.6 35B A3B

Qwen/Qwen3.6-35B-A3B

Qwen3.6 35B A3B is a native vision-language MoE model with hybrid attention. Compared to Qwen3.5 35B A3B, Alibaba reports stronger agentic coding, mathematical and code reasoning, and better spatial understanding (including object localization and detection).

Qwen 3 Coder 480B

qwen/qwen3-coder

Qwen 3 Coder 480B, a 480 billion total parameter model with 35B active, and 160 total experts with 8 active. Performs similar to Claude 4 Sonnet in coding benchmarks, but does so at a much lower price.

Qwen3.5 9B

qwen/qwen3.5-9b

Qwen3.5 9B is a multimodal foundation model from the Qwen 3.5 family, built for efficient reasoning, coding, and visual understanding in a compact 9B architecture.

Qwen3.5 Plus

qwen/qwen3.5-plus

Qwen 3.5 Plus is a commercial model with hybrid linear attention and sparse MoE architecture. Supports text, image, and video input with a 1M context window.