Comparisons of Large Open Source AI Models (>150B)

Open source AI models with over 150B parameters.

Models are considered open source (also commonly referred to as open weights) where their weights are accessible to download. This allows self-hosting on your own infrastructure and enables customizing the model such as through fine-tuning.

For more details including relating to our methodology, see our FAQs.

Z AI logoGLM-5.2 (max) and MiniMax logoMiniMax-M3 are the highest intelligence Large open source models, defined as those with >150B parameters, followed by DeepSeek logoDeepSeek V4 Pro (max) & Kimi logoKimi K2.6.

Highlights

Openness

Artificial Analysis Openness Index · Higher is better
Updated

Intelligence

Artificial Analysis Intelligence Index · Higher is better

Total Parameters

Trainable parameters in billions

Openness

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

Intelligence

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
Estimate (independent evaluation forthcoming)
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-BriefcaseNew

Agentic knowledge work, Elo

AutomationBench-AANew

Agentic SaaS workflows

Harvey LAB-AANew

Legal agentic work, task all-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.

Size

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 vs. Active Parameters

Artificial Analysis Intelligence Index · Active parameters at inference time
Most attractive quadrant
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 vs. Total Parameters

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

Context Window

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).

Further details

Weights
Provider Benchmarks
GLM-5.2 (max)
Z AI logoZ AI
51
753B
40B active at inference time
1M
$0.9
178
🤗
CoreWeaveWaferFriendliAI
+13
View
MiniMax-M3
MiniMax logoMiniMax
44
428B
23B active at inference time
1M
$0.2
85
🤗
ParasailSiliconFlowTogether AI
+3
View
DeepSeek V4 Pro (Reasoning, Max Effort)
DeepSeek logoDeepSeek
44
1.6T
49B active at inference time
1M
$0.2
61
🤗
GMIFireworksDeepSeek
+8
View
Kimi K2.6
Kimi logoKimi
44
1T
32B active at inference time
256k
$0.7
48
🤗
NovitaDatabricksGMI
+12
View
MiMo-V2.5-Pro
Xiaomi logoXiaomi
42
1.0T
42B active at inference time
1M
$0.2
61
🤗
NovitaGMIDeepInfraXiaomi
View
Kimi K2.7 Code
Kimi logoKimi
42
1T
32B active at inference time
256k
$0.7
49
🤗
DatabricksMakoraCrusoe
+8
View
Hy3
Tencent logoTencent
41
299B
21B active at inference time
256k
-
48
🤗
Novita
View
Nex-N2-Pro
Nex AGI logoNex AGI
41
397B
17B active at inference time
262k
$0.5
139
🤗
SiliconFlow
View
DeepSeek V4 Pro (Reasoning, High Effort)
DeepSeek logoDeepSeek
41
1.6T
49B active at inference time
1M
$0.2
56
🤗
BasetenDeepInfraTogether AI
+7
View
Inkling (xhigh)
Thinking Machines logoThinking Machines
41
975B
41B active at inference time
1M
$1.1
73
🤗
Thinking Machines
View
DeepSeek V4 Flash (Reasoning, Max Effort)
DeepSeek logoDeepSeek
40
284B
13B active at inference time
1M
$0.1
110
🤗
ParasailMakoraSiliconFlow
+4
View
GLM-5.1 (Reasoning)
Z AI logoZ AI
40
744B
40B active at inference time
200k
$0.9
64
🤗
DeepInfraWaferSiliconFlow
+7
View