Alibaba
Released February 24, 2026

Qwen3.5 27B

Qwen3.5 27B by Alibaba: dense open-weight model with early fusion vision-language, Gated DeltaNet hybrid architecture, 262K context, 201-language support.

Inputs
Text
Image
Video
Outputs
Text

Model Overview

Capabilities, design details, and architectural traits

Qwen3.5 27B - Dense Multimodal Foundation with Early Fusion

Qwen3.5 27B is the dense open-weight variant in the Qwen3.5 series. Unlike its MoE siblings (35B-A3B, 122B-A10B, 397B-A17B), every parameter is active during inference. It includes a built-in vision encoder, making it a natively multimodal causal model rather than a language-only backbone with a separately attached vision module.

TraitDetail
Unified vision-language via early fusionText, image, and video tokens are interleaved and trained jointly from pretraining, not via post-hoc adapters - the official model card explicitly states this achieves cross-generational parity with Qwen3
Multi-Token Prediction (MTP)Trained with multi-step MTP, documented in the model card as a distinct training objective
Asynchronous RL at million-agent scaleReinforcement learning training used asynchronous frameworks supporting massive-scale agent scaffolds across progressively complex task distributions
201 languagesDocumented multilingual coverage across 201 languages and dialects - notably broader than the 119 documented for Qwen3
Context window262,144 tokens natively, extensible to 1,010,000 via YaRN
LicenseApache 2.0 open-weight

Benchmark Performance

Independent evaluations · Artificial Analysis

22.9%
Intelligence

Accuracy & Capability Details

GPQA - Graduate Science85.8%
Humanity's Last Exam23.9%
SciCode - Scientific Coding39.5%
Instruction Following75.6%
Long Context Reasoning77.7%
τ²-Bench - Agentic Tasks93.9%
TerminalBench - System Control32.6%

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
$0.30
Best Input Pricing
$4$2
Output Pricing
$2.40
Best Output Pricing
$20$10
Modalities
Inputs
textimagevideo
textimagefile
textimagefile
Outputs
text
text
text
Benchmarks (0-100)
Intelligence Index19.4
57.6
Best Intelligence Index
56.0
Coding Index---
Agentic Index---
Qwen3.5 27B
Claude Opus 5.5
Claude Sonnet 5.5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

14%
Qwen3.5 27B
Humanity's Last Exam
Score: 14%
Qwen3.5 27B
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.

64%
Qwen3.5 27B
Long Context Reasoning
Score: 64%
Qwen3.5 27B
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.

37%
Qwen3.5 27B
SciCode Benchmark
Score: 37%
Qwen3.5 27B
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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