Saltar al contenido principal
AITier

Qwen3.5 27B (Reasoning)

AlibabaQwenOpen WeightApache 2.0 · Uso Comercial

Descripción

Qwen3.5-27B is a multimodal dense foundation model with 27 billion parameters. It combines strong reasoning, coding, multilingual, long-context, and visual understanding performance in a production-friendly open-weight package with a native 262K context window.

Fecha de lanzamiento
2026-02-24
Parámetros
27.0B
Longitud del contexto
262K
Modalidades
audio, image, text, video

Radar de capacidades

23
general
60
coding
86
reasoning
67
science
60
agents
80
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica57
48.0
LS
Ranking de codificación183
69.0
AA
Ranking general117
64.0
AA
Ranking multimodal74
53.0
LS
Ciencia163
63.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

t2-bench79.0%Aut.
VITA-Bench41.9%Aut.
DeepPlanning22.6%Aut.

Chat

IFEvalGoogle Research (2023)95.0%Aut.
Multi-Challenge60.8%Aut.

Code

FullStackBench en60.1%Aut.
FullStackBench zh57.4%Aut.

General

C-Eval90.5%Aut.
MAXIFE88.0%Aut.
Include81.6%Aut.
AndroidWorld_SR64.2%Aut.
NOVA-6358.1%Aut.

Healthcare

MedXpertQA62.4%Aut.
PMC-VQA62.4%Aut.

Instruction Following

IFBench76.5%Aut.

Language

MMLU-Redux93.2%Aut.
MMLU-Pro86.1%Aut.
MMMLU85.9%Aut.
MMLU-ProX82.2%Aut.
WMT24++77.6%Aut.

Long Context

LongBench v260.6%Aut.

Math

HMMT 202592.0%Aut.
HMMT2589.8%Aut.
MathVista-Mini87.8%Aut.
DynaMath87.7%Aut.
MathVision86.0%Aut.
CodeForces0.81 / 3000Aut.
PolyMATH71.2%Aut.

Multimodal

VideoMME w/o sub.82.8%Aut.
VideoMMMU82.3%Aut.
MMMU82.3%Aut.
TIR-Bench59.8%Aut.
OSWorld-Verified56.2%Aut.

Reasoning

Global PIQA87.5%Aut.
GPQANYU + Cohere + Anthropic (2023)85.5%Aut.
LiveCodeBench v680.7%Aut.
CharXiv-R79.5%Aut.
SWE-Bench Verified72.4%Aut.
AA-LCR66.1%Aut.
SuperGPQA65.6%Aut.
BrowseComp-zh62.1%Aut.
BrowseCompOpenAI (2025)61.0%Aut.
Humanity's Last Exam48.5%Aut.
Seal-047.2%Aut.
Terminal-Bench 2.0Stanford × Laude Institute (2026)41.6%Aut.
OJBench40.1%Aut.

Search

WideSearch61.1%Aut.

Tool Calling

BFCL-V468.5%Aut.

Video

MLVU85.9%Aut.

Vision

CountBench0.98 / 100Aut.
VLMsAreBlind96.9%Aut.
V*93.7%Aut.
AI2D92.9%Aut.
MMBench-V1.192.6%Aut.
RefCOCO-avg0.91 / 100Aut.
OCRBench89.4%Aut.
OmniDocBench 1.588.9%Aut.
VideoMME w sub.87.0%Aut.
EmbSpatialBench0.84 / 100Aut.
RealWorldQA83.7%Aut.
LingoQA82.0%Aut.
CC-OCR81.0%Aut.
MMStar81.0%Aut.
SlakeVQA80.0%Aut.
MMMU-Pro75.0%Aut.
MVBench74.6%Aut.
LVBench73.6%Aut.
MMVU73.3%Aut.
ScreenSpot Pro70.3%Aut.
Hallusion Bench70.0%Aut.
RefSpatialBench0.68 / 100Aut.
ERQA60.5%Aut.
MMLongBench-Doc0.60 / 100Aut.
SimpleVQA0.56 / 100Aut.
BabyVision44.6%Aut.
ODinW41.1%Aut.
ZEROBench-Sub0.36 / 100Aut.
SUNRGBD0.35 / 100Aut.
Nuscene15.2%Aut.
Hypersim0.13 / 100Aut.
ZEROBench0.10 / 100Aut.

Índices de evaluación AA

(Artificial Analysis)
Tau2(Sierra + U Toronto + Vector Institute (2025))
93.9
Gpqa(NYU + Cohere + Anthropic (2023))
85.8
Lcr(Artificial Analysis)
77.7
Ifbench(Google Research (2023))
75.6
Terminalbench Hard(Stanford × Laude Institute (2026))
32.6
Hle(Center for AI Safety + Scale AI (2025))
23.9
Intelligence Index(Artificial Analysis)
22.9

Puntuaciones por categoría LLM Stats

(LLM Stats (zeroeval))
Instruction Following
90
Biology
90
Chat
80
Image To Text
80
Language
80
Legal
80
Math
80
Physics
80
Structured Output
80
Embodied
80
Finance
80
Grounding
80
Chemistry
80
Text-to-image
80
Video
80
Long Context
70
Multimodal
70
Reasoning
70
Spatial Reasoning
70
Frontend Development
70
General
70
Healthcare
70
Economics
70
Vision
70
Search
60
Agents
60
Code
60
Communication
60
Tool Calling
60
Spatial
20
3d
20

Precios

Precio de entrada$0.3 / 1M tokens
Precio de salida$2.4 / 1M tokens
Precio mixto (3:1)$0.825 / 1M tokens

Velocidad

Tokens/seg0.0
Retraso del primer token0.00s
Tiempo hasta la respuesta0.00s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

4 proveedores

Más barato: DeepInfraMás caro: Alibaba
ProveedorEntradaSalida
1DeepInfraMás barato
$0
$0
2Novita
$0
$0
3EmpirioLabs AI
$0.086
$0.688
4AlibabaPRINCIPAL
$0.3
$2.4

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas

LLM StatsArtificial Analysis