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

Name: Openness
Creator: Artificial Analysis
License: https://artificialanalysis.ai/docs/legal/Terms-of-Use.pdf

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.

Nemotron 3.5 Super VL y

Ling-3.0-flash-VL son los modelos medianos con pesos abiertos, definidos como aquellos con 40B-150B parámetros de mayor inteligencia, seguidos por

Ling-3.0-flash-Fin y

Nemotron 3.5 Bolt 74B-A9B.

Openness

Artificial Analysis Openness Index · Higher is better

Inteligencia

Artificial Analysis Intelligence Index · Higher is better

Parámetros totales

Parámetros entrenables en miles de millones

Openness

Artificial Analysis Openness Index: puntuación

El Openness Index mide la apertura de los modelos en una escala normalizada de 0 a 100 (cuanto más alta, mayor apertura)

Inteligencia

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3.2 incorporates 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

Estimate (independent evaluation forthcoming)

Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, 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.

Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

AA-Briefcase v1.1Updated

Agentic knowledge work, (Elo-500)/2000

AA-Omniscience Accuracy

Knowledge

AA-Omniscience Non-Hallucination Rate

1 - hallucination rate

AutomationBench-AA

Agentic SaaS workflows

GDPval-AA v2.1Updated

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

Humanity's Last Exam

Reasoning & knowledge

GDP.pdf

Professional document reasoning, All-pass

Terminal-Bench 4.0

Agentic coding & terminal use

AA-LCR v1.1

Long context reasoning

SciCodeUnder review

Coding

CritPtUnder review

Physics reasoning

Terminal-Bench-Science 0.1New

Agentic scientific research workflows in a terminal

No data available

FrontierCode 1.1New

Agentic software engineering in open-source repositories

No data available

AA-AnalystAgent

Quantitative analysis on spreadsheets & documents

Harvey LAB-AA v1.1Updated

Legal agentic work, Hallucination-Gated All-Pass Rate

No data available

EnterpriseOps-Gym-AA

Agentic business operations

ITBench-AA

Kubernetes incident root-cause analysis

MLCR-AA

Medical long context reasoning

MMMU-Pro

Visual reasoning

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

Tamaño

Tamaño del modelo: parámetros totales y activos

Comparison between total model parameters and parameters active during inference (billions)

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. parámetros activos

Artificial Analysis Intelligence Index · Active parameters at inference time (billions)

Most attractive quadrant

Pareto line

Intelligence Index vs. parámetros totales

Artificial Analysis Intelligence Index · Size in parameters (billions)

Most attractive quadrant

Pareto line

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: 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
Nemotron 3.5 Super VL	NVIDIA	26	120B 12B activos en inferencia	1M	$0.1	251	🤗	+3	Ver
Ling-3.0-flash-VL	InclusionAI	25	124B 5.5B activos en inferencia	262k	-	-	🤗	-	Ver
Ling-3.0-flash-Fin	InclusionAI	23	124B 5.1B activos en inferencia	262k	$0.0	226	🤗		Ver
Nemotron 3.5 Bolt 74B-A9B	NVIDIA	21	74B 9B activos en inferencia	262k	-	-	No disponible	-	Ver
Qwen3.5 122B A10B (Non-reasoning)	Alibaba	18	125B 10B activos en inferencia	262k	$0.7	140	🤗		Ver
Qwen3.5 122B A10B (Reasoning)	Alibaba	16	125B 10B activos en inferencia	262k	$0.7	131	🤗		Ver
Mistral Medium 3.5	Mistral	14	128B	256k	$1.2	165	🤗		Ver
HyperNova 60B 2605 (High, Based on gpt-oss-120b)	Multiverse Computing	12	58.7B 4.8B activos en inferencia	131k	-	-	🤗	-	Ver
gpt-oss-120b (High)	OpenAI	12	117B 5.1B activos en inferencia	131k	$0.2	213	🤗	+15	Ver
K2 Think V2	Institute of Foundation Models	11	70B	262k	-	-	🤗	-	Ver
LongCat Flash Lite	LongCat	11	68.5B 3B activos en inferencia	256k	-	-	🤗	-	Ver
Mistral Small 4 (Reasoning)	Mistral	11	119B 6.5B activos en inferencia	256k	$0.1	177	🤗		Ver

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

Openness

Inteligencia

Parámetros totales

Openness

Artificial Analysis Openness Index: puntuación

Inteligencia

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index

Evaluations

Intelligence Evaluation Relevance

Artificial Analysis Intelligence Index

Tamaño

Tamaño del modelo: parámetros totales y activos

Total Parameters

Active Parameters at Inference Time

Intelligence Index vs. parámetros activos

Artificial Analysis Intelligence Index

Active Parameters at Inference Time

Intelligence Index vs. parámetros totales

Artificial Analysis Intelligence Index

Total Parameters

Ventana de contexto

Ventana de contexto

Context Window for RAG

Context Window

Más detalles