大型开放权重 AI 模型比较（>150B）

参数量超过 150B 的开放权重 AI 模型。

如果模型权重可供下载，我们便将其视为开放权重模型。这样用户就可以在自己的基础设施上自行托管，并通过微调等方式定制模型。

如需了解包括方法论在内的更多详情，请参阅常见问题。

Kimi 标志Kimi K3 (max) 和 Z AI 标志GLM-5.2 (max) 是智能得分最高的大型开放权重模型，定义为参数量超过 150B 的模型，其次是 DeepSeek 标志DeepSeek V4 Flash 0731 (max) 和 Kimi 标志Kimi K3 (low)。

亮点

开放性

Artificial Analysis Openness Index · Higher is better

智能

Artificial Analysis Intelligence Index · Higher is better

总参数量

可训练参数（十亿）

开放性

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

智能

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
GDPval-AA v2

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

𝜏³-Banking

Agentic tool use

Terminal-Bench v2.1

Agentic coding & terminal use

SciCode

Coding

Humanity's Last Exam

Reasoning & knowledge

GPQA Diamond

Scientific reasoning

CritPt

Physics reasoning

AA-Omniscience Accuracy

Knowledge

AA-Omniscience Non-Hallucination Rate

1 - hallucination rate

AA-LCR

Long context reasoning

AA-Briefcase

Agentic knowledge work, Elo

AutomationBench-AA

Agentic SaaS workflows

Harvey LAB-AA

Legal agentic work, criterion pass rate

EnterpriseOps-Gym-AANew

Agentic business operations

IFBench

Instruction following

APEX-Agents-AA

Long-horizon agentic tasks

ITBench-AA

Kubernetes incident root-cause analysis

MMMU-Pro

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.

规模

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.

上下文窗口

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).

更多详情

权重
服务商基准测试
Kimi K3 (max)
Kimi 标志Kimi
57
2.8T
推理时启用 104B 个参数
1M
$2.3
37
🤗
WaferModalDatabricks
+8
查看
GLM-5.2 (max)
Z AI 标志Z AI
51
753B
推理时启用 40B 个参数
1M
$0.9
160
🤗
MakoraSiliconFlowDeepInfra
+13
查看
DeepSeek V4 Flash 0731 (Reasoning, Max Effort)
DeepSeek 标志DeepSeek
50
284B
推理时启用 13B 个参数
1M
$0.1
110
🤗
ParasailSiliconFlowDeepInfra
+3
查看
Kimi K3 (low)
Kimi 标志Kimi
47
2.8T
推理时启用 104B 个参数
1M
$2.3
36
🤗
Kimi
查看
MiniMax-M3
MiniMax 标志MiniMax
44
428B
推理时启用 23B 个参数
1M
$0.2
73
🤗
SiliconFlowParasailSelf-hosted
+7
查看
DeepSeek V4 Pro (Reasoning, Max Effort)
DeepSeek 标志DeepSeek
44
1.6T
推理时启用 49B 个参数
1M
$0.2
64
🤗
Self-hostedSiliconFlowGMI
+8
查看
DeepSeek V4 Pro (Reasoning, High Effort)
DeepSeek 标志DeepSeek
43
1.6T
推理时启用 49B 个参数
1M
$0.2
66
🤗
SiliconFlowDeepSeekMicrosoft Azure
+6
查看
MiMo-V2.5-Pro
Xiaomi 标志Xiaomi
42
1.0T
推理时启用 42B 个参数
1M
$0.2
67
🤗
DeepInfraNovitaXiaomi
+2
查看
Kimi K2.7 Code
Kimi 标志Kimi
42
1T
推理时启用 32B 个参数
256k
$0.7
42
🤗
DeepInfraParasailGMI
+6
查看
Hy3
Tencent 标志Tencent
41
299B
推理时启用 21B 个参数
256k
$0.1
65
🤗
GMIDeepInfraNovitaSiliconFlow
查看
Nex-N2-Pro
Nex AGI 标志Nex AGI
41
397B
推理时启用 17B 个参数
262k
$0.5
131
🤗
SiliconFlow
查看
Inkling (xhigh)
Thinking Machines 标志Thinking Machines
41
975B
推理时启用 41B 个参数
1M
$0.7
80
🤗
Thinking MachinesSelf-hostedDeepInfraTogether AI
查看