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Qwen3.5 122B A10B (Non-reasoning)

AlibabaQwenOpen WeightApache 2.0 · Uso Comercial

Descripción

Qwen3.5-122B-A10B is a multimodal Mixture-of-Experts model with 122 billion total parameters and 10 billion activated parameters. It combines strong reasoning, coding, long-context, and visual understanding performance with production-friendly efficiency and a native 262K context window.

Fecha de lanzamiento
2026-02-24
Parámetros
122.0B
Longitud del contexto
262K
Modalidades
audio, image, text, video

Radar de capacidades

17
general
43
coding
83
reasoning
62
science
60
agents
80
multimodal

Rankings

Dominio#PosiciónPuntuaciónFuente
Capacidad agéntica47
49.0
LS
Ranking de codificación263
55.0
AA
Ranking general245
48.0
AA
Ranking multimodal43
59.0
LS
Ciencia226
55.0
AA

Puntuaciones de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Agents

t2-bench79.5%Aut.
VITA-Bench33.6%Aut.
DeepPlanning24.1%Aut.

Chat

IFEvalGoogle Research (2023)93.4%Aut.
Multi-Challenge61.5%Aut.

Code

FullStackBench en62.6%Aut.
FullStackBench zh58.7%Aut.

General

C-Eval91.9%Aut.
MAXIFE87.9%Aut.
Include82.8%Aut.
AndroidWorld_SR66.4%Aut.
NOVA-6358.6%Aut.

Healthcare

MedXpertQA67.3%Aut.
PMC-VQA63.3%Aut.

Instruction Following

IFBench76.1%Aut.

Language

MMLU-Redux94.0%Aut.
MMMLU86.7%Aut.
MMLU-Pro86.7%Aut.
MMLU-ProX82.2%Aut.
WMT24++78.3%Aut.

Long Context

LongBench v260.2%Aut.

Math

HMMT 202591.4%Aut.
HMMT2590.3%Aut.
MathVista-Mini87.4%Aut.
MathVision86.2%Aut.
DynaMath85.9%Aut.
CodeForces0.85 / 3000Aut.
PolyMATH68.9%Aut.

Multimodal

VideoMME w/o sub.83.9%Aut.
MMMU83.9%Aut.
VideoMMMU82.0%Aut.
OSWorld-Verified58.0%Aut.
TIR-Bench53.2%Aut.

Reasoning

Global PIQA88.4%Aut.
GPQANYU + Cohere + Anthropic (2023)86.6%Aut.
LiveCodeBench v678.9%Aut.
CharXiv-R77.2%Aut.
SWE-Bench Verified72.0%Aut.
BrowseComp-zh69.9%Aut.
SuperGPQA67.1%Aut.
AA-LCR66.9%Aut.
BrowseCompOpenAI (2025)63.8%Aut.
Terminal-Bench 2.0Stanford × Laude Institute (2026)49.4%Aut.
Humanity's Last Exam47.5%Aut.
Seal-044.1%Aut.
OJBench39.5%Aut.

Search

WideSearch60.5%Aut.

Tool Calling

BFCL-V472.2%Aut.

Video

MLVU87.3%Aut.

Vision

CountBench0.97 / 100Aut.
VLMsAreBlind96.7%Aut.
AI2D93.3%Aut.
V*93.2%Aut.
MMBench-V1.192.8%Aut.
OCRBench92.1%Aut.
RefCOCO-avg0.91 / 100Aut.
OmniDocBench 1.589.8%Aut.
VideoMME w sub.87.3%Aut.
RealWorldQA85.1%Aut.
EmbSpatialBench0.84 / 100Aut.
MMStar82.9%Aut.
CC-OCR81.8%Aut.
SlakeVQA81.6%Aut.
LingoQA80.8%Aut.
MMMU-Pro76.9%Aut.
MVBench76.6%Aut.
MMVU74.7%Aut.
LVBench74.4%Aut.
ScreenSpot Pro70.4%Aut.
RefSpatialBench0.69 / 100Aut.
Hallusion Bench67.6%Aut.
ERQA62.0%Aut.
SimpleVQA0.62 / 100Aut.
MMLongBench-Doc0.59 / 100Aut.
ODinW44.5%Aut.
BabyVision40.2%Aut.
SUNRGBD0.36 / 100Aut.
ZEROBench-Sub0.36 / 100Aut.
Nuscene15.4%Aut.
Hypersim0.13 / 100Aut.
ZEROBench0.09 / 100Aut.

Índices de evaluación AA

(Artificial Analysis)
Tau2(Sierra + U Toronto + Vector Institute (2025))
84.5
Gpqa(NYU + Cohere + Anthropic (2023))
82.7
Lcr(Artificial Analysis)
61.3
Ifbench(Google Research (2023))
50.8
Terminalbench V2 1
47.2
Coding Index(Artificial Analysis)
43.3
Terminalbench Hard(Stanford × Laude Institute (2026))
29.5
Intelligence Index(Artificial Analysis)
17.7
Hle(Center for AI Safety + Scale AI (2025))
15.9
Tau Banking
10.3

Puntuaciones por categoría LLM Stats

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

Precios

Precio de entrada$0.4 / 1M tokens
Precio de salida$3.2 / 1M tokens
Precio mixto (3:1)$1.1 / 1M tokens

Velocidad

Tokens/seg146.1
Retraso del primer token1.00s
Tiempo hasta la respuesta1.00s

Ranking de Precios por Proveedor

Ranking de Precios por Proveedor

2 proveedores

Más barato: DeepInfraMás caro: Alibaba
ProveedorEntradaSalida
1DeepInfraMás barato
$0
$0
2AlibabaPRINCIPAL
$0.4
$3.2

Comparar precios entre diferentes proveedores de API para este modelo.

Fuentes externas

LLM StatsArtificial Analysis