Comparación de modelos de IA medianos con pesos abiertos (40B-150B)

Modelos de IA con pesos abiertos de entre 40B y 150B parámetros.

Consideramos que un modelo tiene pesos abiertos (también denominado comúnmente «open source») cuando sus pesos están disponibles para descargar. Esto permite alojarlo en infraestructura propia y personalizarlo, por ejemplo, mediante ajuste fino.

Para más detalles sobre nuestra metodología, consulta nuestras FAQs.

Logo de InclusionAILing 3.0 Flash y Logo de AlibabaQwen3.5 122B A10B son los modelos medianos con pesos abiertos, definidos como aquellos con 40B-150B parámetros de mayor inteligencia, seguidos por Logo de MistralMistral Medium 3.5 y Logo de AlibabaQwen3.5 122B A10B (Non-reasoning).

Aspectos destacados

Artificial Analysis Openness Index · Higher is better
Updated
Artificial Analysis Intelligence Index · Higher is better
Parámetros entrenables en miles de millones

Openness

Artificial Analysis Openness Index: Score

Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open)

Inteligencia

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.2 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1
Estimate (independent evaluation forthcoming)

Artificial Analysis Intelligence Index v4.2 includes: AA-Briefcase, GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better
See more

Agentic knowledge work, (Elo-500)/2000

Agentic real-world work tasks, (Elo-500)/2000

Agentic tool use

Agentic coding & terminal use

Coding

Reasoning & knowledge

Professional document reasoning, All-pass

Physics reasoning

Long context reasoning

Agentic SaaS workflows

Legal agentic work, criterion pass rate

Agentic business operations

Scientific reasoning

Quantitative analysis on spreadsheets & documents

Instruction following

Long-horizon agentic tasks

Kubernetes incident root-cause analysis

Visual reasoning

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

Artificial Analysis Intelligence Index v4.2 includes: AA-Briefcase, GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Tamaño

Model Size: Total and Active Parameters

Comparison between total model parameters and parameters active during inference

The total number of trainable weights and biases in the model, expressed in billions. These parameters are learned during training and determine the model's ability to process and generate responses.

The number of parameters actually executed during each inference forward pass, expressed in billions. For Mixture of Experts (MoE) models, a routing mechanism selects a subset of experts per token, resulting in fewer active than total parameters. Dense models use all parameters, so active equals total.

Intelligence Index vs. Active Parameters

Artificial Analysis Intelligence Index · Active parameters at inference time
Most attractive quadrant
Pareto line

Artificial Analysis Intelligence Index v4.2 includes: AA-Briefcase, GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

The number of parameters actually executed during each inference forward pass, expressed in billions. For Mixture of Experts (MoE) models, a routing mechanism selects a subset of experts per token, resulting in fewer active than total parameters. Dense models use all parameters, so active equals total.

Intelligence Index vs. Total Parameters

Artificial Analysis Intelligence Index · Size in parameters (billions)
Most attractive quadrant
Pareto line

Artificial Analysis Intelligence Index v4.2 includes: AA-Briefcase, GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

The total number of trainable weights and biases in the model, expressed in billions. These parameters are learned during training and determine the model's ability to process and generate responses.

Ventana de contexto

Context Window

Context window: tokens limit · Higher is better

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Más detalles

Pesos
Benchmarks de proveedores
Ling 3.0 Flash
Logo de InclusionAIInclusionAI
27
124B
5.1B activos en inferencia
262k
$0.0
322
No disponible
DeepInfraInclusionAI
Qwen3.5 122B A10B (Reasoning)
Logo de AlibabaAlibaba
25
125B
10B activos en inferencia
262k
$0.7
132
SiliconFlowDeepInfraAlibaba Cloud
+2
Mistral Medium 3.5
Logo de MistralMistral
23
128B
256k
$1.2
147
MistralSelf-hosted
Qwen3.5 122B A10B (Non-reasoning)
Logo de AlibabaAlibaba
21
125B
10B activos en inferencia
262k
$0.7
145
DeepInfraAlibaba Cloud
Nemotron 3 Super 120B A12B (Reasoning)
Logo de NVIDIANVIDIA
19
120.6B
12.7B activos en inferencia
1M
$0.3
141
CoreWeaveNebiusDeepInfra
gpt-oss-120b (high)
Logo de OpenAIOpenAI
16
117B
5.1B activos en inferencia
131k
$0.2
176
GroqCloudflareScaleway
+17
Qwen3 Coder Next
Logo de AlibabaAlibaba
14
79.7B
3B activos en inferencia
256k
$0.4
102
Amazon BedrockParasailTogether AINovita
Mistral Small 4 (Reasoning)
Logo de MistralMistral
13
119B
6.5B activos en inferencia
256k
$0.2
170
Mistral
Devstral 2
Logo de MistralMistral
13
125B
256k
-
132
Mistral
HyperNova 60B 2605 (high, based on gpt-oss-120b)
Logo de Multiverse ComputingMultiverse Computing
12
58.7B
4.8B activos en inferencia
131k
$0.1
349
Multiverse Computing
K2 Think V2
Logo de MBZUAI Institute of Foundation ModelsMBZUAI Institute of Foundation Models
11
70B
262k
-
-
-
LongCat Flash Lite
Logo de LongCatLongCat
11
68.5B
3B activos en inferencia
256k
-
-
-