Alibaba
Released February 24, 2026

Qwen3.5-35B-A3B

Alibaba Qwen3.5-35B-A3B is a reasoning vision-language model built on Gated Delta Networks and Mixture-of-Experts, with toggleable thinking and tool use.

Inputs
Text
Image
Video
Outputs
Text

Model Overview

Capabilities, design details, and architectural traits

Qwen3.5-35B-A3B - A Reasoning Vision-Language Model With Tool Use

Qwen3.5-35B-A3B is described by the Qwen team as a reasoning vision-language model that supports tool use. It combines multimodal understanding with agentic capability in one model, built on an architecture that favors efficiency over raw size.

TraitDetail
Defining purposeA reasoning vision-language model that supports tool use, combining multimodal understanding with agentic capability in one model.
Gated Delta plus MoEBuilt on a hybrid architecture combining Gated Delta Networks with a sparse Mixture-of-Experts design, aimed at high-throughput inference with low latency.
Early fusion trainingTrained with early fusion on multimodal tokens, a unified approach to vision-language learning rather than attaching a separate vision encoder to a text only model.
Toggleable thinking modeSupports both a thinking mode for step by step reasoning and a non-thinking mode for direct responses, switchable depending on the task.

Trained With Massive-Scale Agent Reinforcement Learning

Qwen states it scaled reinforcement learning across environments involving large numbers of agents, using progressively complex task distributions aimed at robust real-world adaptability rather than a single fixed training scenario.

Benchmark Performance

Independent evaluations · Artificial Analysis

19.3%
Intelligence

Accuracy & Capability Details

GPQA - Graduate Science84.5%
Humanity's Last Exam21.0%
SciCode - Scientific Coding37.7%
Instruction Following72.5%
Long Context Reasoning72.0%
τ²-Bench - Agentic Tasks89.2%
TerminalBench - System Control26.5%

Compare Models Side-by-Side

Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderAlibabaAnthropicAnthropic
Release DateFebruary 24, 2026September 22, 2026September 28, 2026
Knowledge Cutoff--Jun 2026
Context & Limits
Context Window262K
1M
Best Context Window
1M
Best Context Window
Pricing (per 1M tokens)
Input Pricing
$0.25
Best Input Pricing
$4$2
Output Pricing
$2
Best Output Pricing
$20$10
Modalities
Inputs
textimagevideo
textimagefile
textimagefile
Outputs
text
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Benchmarks (0-100)
Intelligence Index15.1
57.6
Best Intelligence Index
56.0
Coding Index37.0--
Agentic Index11.8--
Qwen3.5-35B-A3B
Claude Opus 5.5
Claude Sonnet 5.5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

13%
Qwen3.5-35B-A3B
Humanity's Last Exam
Score: 13%
Qwen3.5-35B-A3B
61%
Claude Opus 5.5
Humanity's Last Exam
Score: 61%
Claude Opus 5.5
55%
Claude Sonnet 5.5
Humanity's Last Exam
Score: 55%
Claude Sonnet 5.5

Long Context Reasoning

Logical reasoning over long context windows.

63%
Qwen3.5-35B-A3B
Long Context Reasoning
Score: 63%
Qwen3.5-35B-A3B
85%
Claude Opus 5.5
Long Context Reasoning
Score: 85%
Claude Opus 5.5
83%
Claude Sonnet 5.5
Long Context Reasoning
Score: 83%
Claude Sonnet 5.5

SciCode Benchmark

Scientific coding and mathematical modeling.

29%
Qwen3.5-35B-A3B
SciCode Benchmark
Score: 29%
Qwen3.5-35B-A3B
67%
Claude Opus 5.5
SciCode Benchmark
Score: 67%
Claude Opus 5.5
61%
Claude Sonnet 5.5
SciCode Benchmark
Score: 61%
Claude Sonnet 5.5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

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