Comparação de modelos grandes de IA de pesos abertos (>150B)

Modelos de IA de pesos abertos com mais de 150B parâmetros.

Os modelos são considerados de pesos abertos (também chamados frequentemente de código aberto) quando seus pesos estão disponíveis para download. Isso permite a auto-hospedagem em sua própria infraestrutura e a personalização do modelo, por exemplo, por meio de ajuste fino.

Para mais detalhes sobre nossa metodologia, consulte as perguntas frequentes.

Logo: KimiKimi K3 (max) e Logo: Z AIGLM-5.2 (max) são os modelos com maior inteligência entre os modelos grandes de pesos abertos, definidos como aqueles com >150B parâmetros, seguidos por Logo: DeepSeekDeepSeek V4 Flash 0731 (max) e Logo: KimiKimi K3 (low).

Destaques

Artificial Analysis Openness Index · Higher is better
Artificial Analysis Intelligence Index · Higher is better
Parâmetros treináveis em bilhões

Abertura

Artificial Analysis Openness Index: Score

Openness Index assesses model openness on a 0 to 100 normalized scale (higher is more open)
Reasoning models are indicated by a lightbulb icon

Inteligência

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR
Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. 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

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

Agentic tool use

Agentic coding & terminal use

Coding

Reasoning & knowledge

Scientific reasoning

Physics reasoning

Long context reasoning

Agentic knowledge work, Elo

Agentic SaaS workflows

Legal agentic work, criterion pass rate

Agentic business operations

Instruction following

Long-horizon agentic tasks

Kubernetes incident root-cause analysis

Visual reasoning

Reasoning models are indicated by a lightbulb icon

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

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

Tamanho

Model Size: Total and Active Parameters

Comparison between total model parameters and parameters active during inference
Reasoning models are indicated by a lightbulb icon

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
Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. 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
Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. 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.

Janela de contexto

Context Window

Context window: tokens limit · Higher is better
Reasoning models are indicated by a lightbulb icon

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).

Mais detalhes

Pesos
Benchmarks de provedores
Kimi K3 (max)
Logo: KimiKimi
57
2.8T
104B ativos durante a inferência
1M
$2.3
37
Together AIKimiSelf-hosted
+8
GLM-5.2 (max)
Logo: Z AIZ AI
51
753B
40B ativos durante a inferência
1M
$0.9
150
ParasailSiliconFlowSelf-hosted
+13
DeepSeek V4 Flash 0731 (Reasoning, Max Effort)
Logo: DeepSeekDeepSeek
50
284B
13B ativos durante a inferência
1M
$0.1
104
DeepSeekDeepInfraParasail
+3
Kimi K3 (low)
Logo: KimiKimi
47
2.8T
104B ativos durante a inferência
1M
$2.3
37
Kimi
MiniMax-M3
Logo: MiniMaxMiniMax
44
428B
23B ativos durante a inferência
1M
$0.2
73
NebiusSiliconFlowSelf-hosted
+7
DeepSeek V4 Pro (Reasoning, Max Effort)
Logo: DeepSeekDeepSeek
44
1.6T
49B ativos durante a inferência
1M
$0.2
64
Microsoft AzureMakoraDeepSeek
+8
DeepSeek V4 Pro (Reasoning, High Effort)
Logo: DeepSeekDeepSeek
43
1.6T
49B ativos durante a inferência
1M
$0.2
66
DeepInfraNovitaFireworks
+6
MiMo-V2.5-Pro
Logo: XiaomiXiaomi
42
1.0T
42B ativos durante a inferência
1M
$0.2
68
DeepInfraGMINovita
+2
Kimi K2.7 Code
Logo: KimiKimi
42
1T
32B ativos durante a inferência
256k
$0.7
43
NebiusGMINovita
+6
Hy3
Logo: TencentTencent
41
299B
21B ativos durante a inferência
256k
$0.1
65
GMIDeepInfraNovitaSiliconFlow
Nex-N2-Pro
Logo: Nex AGINex AGI
41
397B
17B ativos durante a inferência
262k
$0.5
129
SiliconFlow
Inkling (xhigh)
Logo: Thinking MachinesThinking Machines
41
975B
41B ativos durante a inferência
1M
$0.7
80
Together AIThinking MachinesSelf-hostedDeepInfra