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Qwen3.5 397B A17B vs Qwen3.8 Max

Compare Qwen3.5 397B A17B and Qwen3.8 Max side-by-side. See how these vision models stack up in Image Captioning, OCR, and Open Prompt.

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QwenQwen3.5 397B A17B
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QwenQwen3.8 Max
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Qwen3.5 397B A17B vs Qwen3.8 Max Comparison Table

Evals updated August 6, 2026Pricing updated August 7, 2026

PropertyQwen3.5 397B A17BQwen3.8 Max
OrganizationQwenQwen
Categoryopenclosed
Modalitymultimodalmultimodal
Release DateFeb 2026Aug 2026
Context Window262K984K
Parameters397B2.4T total, ~95B active
LicenseApache 2.0Apache 2.0
Pricing per 1M tokens
Input $/1M$0.390$2.00
Output $/1M$2.34$6.00
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
OverallNot evaluated
84.0%
Avg cost / sample$0.0074
Avg speed / sample18.02s
By task
Object Detection
77.1%
$0.013
Counting
82.4%
$0.0046
Identification
90.6%
$0.0027
OCR
92.8%
$0.0056
Data Extraction
87.6%
$0.0029
Reasoning (low)
73.5%
$0.0047
Reasoning (high)
80.8%
$0.011

Qwen3.5 397B A17B vs Qwen3.8 Max: Overview

Qwen3.5 397B A17B

Qwen3.5-397B-A17B is a 397B-parameter (17B active) open-weight multimodal model developed by Alibaba’s Qwen team, released on 2026-02-16 under Apache-2.0. It supports text and image inputs with text outputs, combining a sparse Mixture-of-Experts architecture with Gated Delta Networks for efficient scaling. The model provides native vision-language reasoning and a large ~262K token context window, extendable to ~1M tokens.

As the first open-weight release in the Qwen3.5 family, it positions itself as a high-capacity, long-context alternative in the large vision-language space, balancing scale and efficiency via sparse activation. It is designed for advanced reasoning, coding, agent workflows, and multimodal understanding tasks.

Qwen3.8 Max

Qwen3.8 Max is the flagship tier of Alibaba's Qwen3.8 family, a sparse mixture-of-experts multimodal model with roughly 2.4 trillion total parameters of which about 95 billion activate per token, which keeps serving cost and latency well below what the total parameter count would imply. It builds on the architectural foundation established by Qwen3.5 and accepts text, images, video, and documents as input while producing text output. Reported context handling reaches close to one million tokens, with a maximum generation length of 131,072 tokens, so the model is aimed at long-horizon agentic work such as repository-scale coding, multi-step research, data analysis, and office document workflows.

For vision work the model performs image and video understanding, document and chart interpretation, text recognition inside images, and grounded visual question answering, and Alibaba reports gains concentrated in multimodal and agentic evaluation categories rather than general reasoning. Published figures include 86.6 on Terminal-Bench 2.1, 67.7 on SWE-bench Pro, 93.0 on PaperBench, 82.8 on IFBench, and 92.6 on GPQA Diamond. It is the first model in the Max tier of the Qwen line for which the team states weights will be released publicly, alongside a smaller Qwen3.8 27B checkpoint. No training or safety model card has been published.