오픈 웨이트 모델 비교

오픈 웨이트 AI 모델을 품질, 성능, 추론 속도, 컨텍스트 창, 파라미터 수, 라이선스 세부 정보 등 주요 성능 지표로 비교하고 분석합니다.

웨이트를 다운로드할 수 있는 모델을 오픈 웨이트 모델(흔히 오픈 소스라고도 함)로 간주합니다. 자체 인프라에서 호스팅할 수 있으며 미세 조정 등을 통해 모델을 맞춤 설정할 수 있습니다.

방법론에 관한 자세한 내용은 FAQ에서 확인하세요.

Kimi 로고Kimi K3 (max)과 Alibaba 로고Qwen3.8 2.4T A95B은 오픈 웨이트 모델 중 지능이 가장 높으며 DeepSeek 로고DeepSeek V4 Pro 0813 (max)과 Z AI 로고GLM-5.2 (max)이 뒤를 잇습니다.

주요 내용

개방성

Artificial Analysis Openness Index · Higher is better

지능

Artificial Analysis Intelligence Index · Higher is better

총 파라미터 수

학습 가능한 파라미터 수(단위: 십억 개)

개방성

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

오픈 웨이트 모델의 발전

Progress in Open Weights vs. Proprietary Intelligence

Artificial Analysis Intelligence Index v4.1.1 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 v4.1.1 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.

Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use.

연구소별 오픈 웨이트 언어 모델 지능 추이

Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1.1 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.

크기별 오픈 웨이트 모델 지능 추이

Artificial Analysis Intelligence Index v4.1.1 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 v4.1.1 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.

  • Tiny: Less than or equal to 4B parameters. These are usually the smallest models in terms of resource demand.
  • Small: Less than 40B parameters.
  • Medium: Between 40B-150B parameters.
  • Large: Over 150B parameters.

지능

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.1.1 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 v4.1.1 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
See more
GDPval-AA v2

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

𝜏³-BankingUpdated

Agentic tool use

Terminal-Bench v2.1

Agentic coding & terminal use

SciCode

Coding

Humanity's Last ExamUpdated

Reasoning & knowledge

GPQA Diamond

Scientific reasoning

CritPt

Physics reasoning

AA-Omniscience AccuracyUpdated

Knowledge

AA-Omniscience Non-Hallucination RateUpdated

1 - hallucination rate

AA-LCRUpdated

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-AA

Agentic business operations

AA-AnalystAgentNew

Quantitative analysis on spreadsheets & documents

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 v4.1.1 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.

크기

모델 크기별 Intelligence Index

Artificial Analysis Intelligence Index v4.1.1 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 v4.1.1 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.

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 v4.1.1 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 v4.1.1 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.

컨텍스트 창

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).

상세 정보

웨이트
제공업체 벤치마크
Kimi K3 (max)
Kimi 로고Kimi
60
2.8T
추론 시 104B 활성
1M
$2.3
38
🤗
KimiFireworksFireworks
+12
보기
Qwen3.8 2.4T A95B
Alibaba 로고Alibaba
58
2.4T
추론 시 95B 활성
984k
$1.2
24
🤗
FireworksTogether AIDeepInfra
+3
보기
DeepSeek V4 Pro 0813 (Reasoning, Max Effort)
DeepSeek 로고DeepSeek
53
1.6T
추론 시 49B 활성
1M
$0.7
69
🤗
DeepSeekGMISiliconFlow
+5
보기
Qwen3.8 27B (xhigh)
Alibaba 로고Alibaba
52
27B
256k
$0.4
54
🤗
DeepInfraSelf-hostedAlibaba Cloud
+2
보기
Motif 3
Motif Technologies 로고Motif Technologies
47
314B
추론 시 13.2B 활성
262k
-
-
제공되지 않음
-
보기
MiniMax-M3
MiniMax 로고MiniMax
45
428B
추론 시 23B 활성
1M
$0.2
137
🤗
ParasailCoreWeaveTogether AI
+9
보기
Inkling (xhigh)
Thinking Machines 로고Thinking Machines
42
975B
추론 시 41B 활성
1M
$0.7
50
🤗
Self-hostedDeepInfraBaseten
+2
보기
Nemotron 3 Ultra 550B A55B (Reasoning)
NVIDIA 로고NVIDIA
38
550B
추론 시 55B 활성
262k
$0.5
188
🤗
CoreWeaveGMITogether AI
+6
보기
Solar Open2 250B
Upstage 로고Upstage
37
250B
추론 시 15B 활성
1M
-
-
🤗
-
보기
Muse Glimmer (high)
Meta 로고Meta
35
30B
131k
$0.2
109
🤗
Together AIDeepInfra
보기
A.X-K2
SK Telecom 로고SK Telecom
35
692B
추론 시 33B 활성
262k
-
-
🤗
-
보기
K-EXAONE 2.0 0803
LG AI Research 로고LG AI Research
31
750B
추론 시 37B 활성
262k
-
-
제공되지 않음
-
보기
Mistral Medium 3.5
Mistral 로고Mistral
30
128B
256k
$1.2
145
🤗
MistralSelf-hosted
보기
Nemotron 3 Super 120B A12B (Reasoning)
NVIDIA 로고NVIDIA
26
120.6B
추론 시 12.7B 활성
1M
$0.3
142
🤗
CoreWeaveNebiusDeepInfra
보기
gpt-oss-120b (high)
OpenAI 로고OpenAI
24
117B
추론 시 5.1B 활성
131k
$0.2
175
🤗
GroqCloudflareScaleway
+16
보기
Nemotron 3.5 Lightning
NVIDIA 로고NVIDIA
24
31.6B
추론 시 3.6B 활성
1M
$0.1
309
제공되지 않음
DeepInfraNebiusCoreWeave
+3
보기
Command A+
Cohere 로고Cohere
23
218B
추론 시 25B 활성
192k
-
264
🤗
Cohere
보기