Name: Capital Expenditure by Major Tech Companies, Over Time
Creator: Artificial Analysis
License: https://artificialanalysis.ai/docs/legal/Terms-of-Use.pdf

AI Progress

Tracking the continued advancement of AI, and the position of each of the leading AI companies.

Frontier Language Model Intelligence, Over Time

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Capital Expenditure by Major Tech Companies, Over Time

Capital expenditure by quarter (in billions of USD)

Represents major investments by tech companies in infrastructure, including AI hardware (like GPUs and data centers). Capex is a strong indicator of a company's commitment to AI development, as training and running frontier models requires significant computing resources.

Note: Capex data is sourced from publicly available financial reports, news articles, and primarily from the SEC.

Intelligence Index vs. Release Date

Artificial Analysis Intelligence Index · Release date

Most attractive region

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Leading Models by AI Lab

Highest Artificial Analysis Intelligence Index achieved by each AI lab

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Efficiency

Analysis of how efficiency of AI is developing. This includes considering how the cost of achieving levels of intelligence and the speed at which this intelligence is accessible are trending.

Language Model Inference Price, by Intelligence Index Band, Over Time

Price in USD per 1M tokens (7:2:1 blend of cache, input, and output token prices). Bands use Artificial Analysis Intelligence Index v4.3.

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Language Model Output Speed, by Intelligence Index Band, Over Time

Output tokens per second. Bands use Artificial Analysis Intelligence Index v4.3.

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Country Analysis

AI is a global phenomenon. We share perspectives on where AI progress is happening and how the leading models from countries compare. We deep-dive on the US and China as the two leading hubs for AI development.

Frontier Language Model Intelligence By Country, Over Time

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Open Weights: Frontier Language Model Intelligence By Country, Over Time

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Leading Models by Country

Artificial Analysis Intelligence Index · Leading models

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Open Source Models

Open weights models offer flexibility in deployment and the ability to fine-tune the models for specific use cases. We analyze the leading open weights models and how intelligence compares to proprietary models.

Progress in Open Weights vs. Proprietary Intelligence

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

Model Architecture

The architecture of AI models influences their performance and efficiency. This section examines architectural trends in models, such as the rise in popularity of the Mixture of Experts (MoE) architecture, and how these relate to model capabilities.

Intelligence Index vs. Release Date by Model Architecture

Artificial Analysis Intelligence Index, open weights models only

Most attractive region

A model where only a subset of parameters ("experts") are active per input. Routing mechanisms select a few experts per forward pass, reducing computation while allowing the model to scale to many more parameters overall.

A model where all parameters are active for every input. Every forward pass involves the full network, making it computationally intensive but straightforward to train and deploy.

Model Size: Total and Active Parameters

Comparison between total model parameters and parameters active during inference

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

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

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

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

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 Length (Tokens), Median By Quarter

Median context length (thousand tokens)

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).

Training Analysis

Our analysis of trends in the training of AI models includes consideration of both trends in the size of training runs as well as the relationship between the size of the training run and the intelligence of the model.

Training Tokens By Model

Training tokens in trillions

No data available

The number of tokens used to train the model, represented in trillions.

Intelligence Index vs. Training Tokens

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1 · Training tokens in trillions

Most attractive quadrant

No data available

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench v4.0, 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.

The number of tokens used to train the model, represented in trillions.

Artificial Analysis AI Trends

State of AI (Highlights) - 2025 Year End

AI Progress

Frontier Language Model Intelligence, Over Time

Capital Expenditure by Major Tech Companies, Over Time

Intelligence Index vs. Release Date

Leading Models by AI Lab

Efficiency

Language Model Inference Price, by Intelligence Index Band, Over Time

Language Model Output Speed, by Intelligence Index Band, Over Time

Country Analysis

Frontier Language Model Intelligence By Country, Over Time

Open Weights: Frontier Language Model Intelligence By Country, Over Time

Leading Models by Country

Open Source Models

Progress in Open Weights vs. Proprietary Intelligence

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Model Architecture

Intelligence Index vs. Release Date by Model Architecture

Model Size: Total and Active Parameters

Intelligence Index vs. Active Parameters

Intelligence Index vs. Total Parameters

Context Length (Tokens), Median By Quarter

Training Analysis

Training Tokens By Model

Intelligence Index vs. Training Tokens

Artificial Analysis AI Trends

State of AI (Highlights) - 2025 Year End

AI Progress

Frontier Language Model Intelligence, Over Time

Artificial Analysis Intelligence Index

Capital Expenditure by Major Tech Companies, Over Time

Capital Expenditure (Capex)

Capex Data Sources Note

Intelligence Index vs. Release Date

Artificial Analysis Intelligence Index

Leading Models by AI Lab

Artificial Analysis Intelligence Index

Efficiency

Language Model Inference Price, by Intelligence Index Band, Over Time

Artificial Analysis Intelligence Index

Language Model Output Speed, by Intelligence Index Band, Over Time

Artificial Analysis Intelligence Index

Country Analysis

Frontier Language Model Intelligence By Country, Over Time

Artificial Analysis Intelligence Index

Open Weights: Frontier Language Model Intelligence By Country, Over Time

Artificial Analysis Intelligence Index

Leading Models by Country

Artificial Analysis Intelligence Index

Open Source Models

Progress in Open Weights vs. Proprietary Intelligence

Artificial Analysis Intelligence Index

Open Weights

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index

Open Weights

Model Architecture

Intelligence Index vs. Release Date by Model Architecture

MoE Models

Dense Models

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 Length (Tokens), Median By Quarter

Context Window for RAG

Context Window

Training Analysis

Training Tokens By Model

Training Tokens

Intelligence Index vs. Training Tokens

Artificial Analysis Intelligence Index

Training Tokens