Comparison of Open Source Models

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

Comparison and analysis of open source AI models across key performance metrics including quality, performance, inference speed, context window, parameter count & licensing details.

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 relating to our methodology, see our FAQs.

MiMo-V2.6-Pro and

GLM-5.3 (max) are the highest intelligence open source models, followed by

Kimi K3 (max) &

GLM-5.3-Flash.

Openness

Artificial Analysis Openness Index · Higher is better

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)

Open Source Progress

Progress in Open Weights vs. Proprietary Intelligence

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

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.

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.

Open Source Language Models Intelligence By Lab Over Time

Open Source Models Intelligence By Size Over Time

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.

Intelligence

Artificial Analysis Intelligence Index

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

AA-Briefcase v1.1Updated

Agentic knowledge work, (Elo-500)/2000

GDPval-AA v2.1Updated

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

AutomationBench-AA

Agentic SaaS workflows

Terminal-Bench 4.0

Agentic coding & terminal use

SciCodeUnder review

Coding

Humanity's Last Exam

Reasoning & knowledge

GDP.pdf

Professional document reasoning, All-pass

CritPtUnder review

Physics reasoning

AA-Omniscience Accuracy

Knowledge

AA-Omniscience Non-Hallucination Rate

1 - hallucination rate

AA-LCR v1.1

Long context reasoning

Harvey LAB-AA

Legal agentic work, criterion pass rate

EnterpriseOps-Gym-AA

Agentic business operations

Terminal-Bench-Science 0.1New

Agentic scientific research workflows in a terminal

AA-AnalystAgent

Quantitative analysis on spreadsheets & documents

ITBench-AA

Kubernetes incident root-cause analysis

MMMU-Pro

Visual reasoning

MLCR-AA

Medical long context reasoning

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

Size

Intelligence Index By Model Size

Model Size: Total and Active Parameters

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. Active Parameters

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

Most attractive quadrant

Pareto line

Intelligence Index vs. Total Parameters

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.

Context Window

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).

Further details

							Weights		Provider Benchmarks
MiMo-V2.6-Pro	Xiaomi	46	1.0T 42B active at inference time	1M	$0.2	40	🤗	+2	View
GLM-5.3 (Max)	Z AI	45	753B 40B active at inference time	1M	$0.9	79	🤗	+23	View
Kimi K3 (Max)	Kimi	44	2.8T 104B active at inference time	1M	$2.3	42	🤗	+18	View
GLM 5.3 Flash	Z AI	42	320B 18B active at inference time	1M	$0.1	51	🤗	+21	View
DeepSeek V4.1 Flash (Max)	DeepSeek	39	552B 16B active at inference time	1M	$0.2	216	🤗	+20	View
Qwen3.8 27B (Xhigh)	Alibaba	34	27B	256k	$0.5	47	🤗	+9	View
K2 Horizon 375B A23B	Institute of Foundation Models	31	375B 23B active at inference time	524k	-	118	🤗		View
MiniMax-M3	MiniMax	29	428B 23B active at inference time	1M	$0.2	94	🤗	+12	View
Inkling (Xhigh)	Thinking Machines	25	975B 41B active at inference time	1M	$0.7	151	🤗	+4	View
Nemotron 3 Ultra 550B A55B (Reasoning)	NVIDIA	23	550B 55B active at inference time	262k	$0.5	155	🤗	+5	View
Muse Glimmer (High)	Meta	17	30B	131k	$0.2	91	🤗		View

Comparison of Open Source Models

Openness

Intelligence

Total Parameters

Openness

Artificial Analysis Openness Index: Score

Open Source Progress

Progress in Open Weights vs. Proprietary Intelligence

Artificial Analysis Intelligence Index

Open Weights

Open Source Language Models Intelligence By Lab Over Time

Artificial Analysis Intelligence Index

Open Source Models Intelligence By Size Over Time

Artificial Analysis Intelligence Index

Model Size Classifications

Intelligence

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index

Intelligence Evaluations

Intelligence Evaluation Relevance

Artificial Analysis Intelligence Index

Size

Intelligence Index By Model Size

Artificial Analysis Intelligence Index

Model Size: Total and Active Parameters

Total Parameters

Active Parameters at Inference Time

Intelligence Index vs. Active Parameters

Artificial Analysis Intelligence Index

Active Parameters at Inference Time

Intelligence Index vs. Total Parameters

Artificial Analysis Intelligence Index

Total Parameters

Context Window

Context Window

Context Window for RAG

Context Window

Further details