Name: Investitionsausgaben großer Technologieunternehmen im Zeitverlauf
Creator: Artificial Analysis
License: https://artificialanalysis.ai/docs/legal/Terms-of-Use.pdf

Fortschritt der KI

Verfolgung der fortlaufenden Weiterentwicklung von KI und der Position jedes führenden KI-Unternehmens.

Frontier Language Model Intelligence, Over Time

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, 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 includes: AA-Briefcase, GDPval-AA v2, 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.

Investitionsausgaben großer Technologieunternehmen im Zeitverlauf

Investitionsausgaben je Quartal (in Milliarden 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. Veröffentlichungsdatum

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 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.

Führende Modelle nach KI-Labor

Höchster von jedem KI-Labor erzielter Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, 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.

Effizienz

Analyse der Entwicklung der KI-Effizienz. Dazu betrachten wir die Kosten für das Erreichen bestimmter Intelligenzniveaus und die Geschwindigkeit, mit der diese Intelligenz verfügbar ist.

Inferenzpreis von Sprachmodellen nach Intelligence-Index-Band im Zeitverlauf

Preis in USD pro 1 Mio. Tokens (Mischung der Preise für Cache-, Eingabe- und Ausgabetokens im Verhältnis 7:2:1). Die Bänder verwenden den Artificial Analysis Intelligence Index v4.3.

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, 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.

Ausgabegeschwindigkeit von Sprachmodellen nach Intelligence-Index-Band im Zeitverlauf

Ausgabetokens pro Sekunde. Die Bänder verwenden den Artificial Analysis Intelligence Index v4.3.

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, 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.

Länderanalyse

KI ist ein globales Phänomen. Wir zeigen, wo KI-Fortschritt stattfindet und wie sich die führenden Modelle verschiedener Länder vergleichen lassen. Die USA und China als zwei führende Zentren der KI-Entwicklung analysieren wir besonders eingehend.

Intelligenz von Frontier-Sprachmodellen nach Land im Zeitverlauf

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, 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 includes: AA-Briefcase, GDPval-AA v2, 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.

Offene Gewichte: Intelligenz von Frontier-Sprachmodellen nach Land im Zeitverlauf

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, 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 includes: AA-Briefcase, GDPval-AA v2, 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.

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 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.

Modelle mit offenen Gewichten

Modelle mit offenen Gewichten ermöglichen flexible Bereitstellungen und die Feinabstimmung auf bestimmte Anwendungsfälle. Wir analysieren die führenden Modelle mit offenen Gewichten und vergleichen ihre Intelligenz mit proprietären Modellen.

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 4.0, 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 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.

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 4.0, 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 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.

Modellarchitektur

Die Architektur von KI-Modellen beeinflusst ihre Leistung und Effizienz. Dieser Abschnitt untersucht Architekturtrends wie die zunehmende Verbreitung der Mixture-of-Experts-Architektur (MoE) und deren Zusammenhang mit Modellfähigkeiten.

Intelligence Index vs. Veröffentlichungsdatum nach Modellarchitektur

Artificial Analysis Intelligence Index, nur Modelle mit offenen Gewichten

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 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.

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. Gesamtparameter

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 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.

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.

Kontextlänge (Tokens), Median je Quartal

Mediane Kontextlänge (Tausend 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).

Trainingsanalyse

Unsere Analyse von Trends beim Training von KI-Modellen betrachtet sowohl die Entwicklung der Größe von Trainingsläufen als auch den Zusammenhang zwischen der Größe eines Trainingslaufs und der Intelligenz des Modells.

Trainingstokens nach Modell

Trainingstokens in Billionen

No data available

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

Intelligence Index vs. Trainingstokens

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1 · Trainingstokens in Billionen

Most attractive quadrant

No data available

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, 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.

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

KI-Trends von Artificial Analysis

State of AI (Highlights) – Jahresende 2025

Fortschritt der KI

Frontier Language Model Intelligence, Over Time

Investitionsausgaben großer Technologieunternehmen im Zeitverlauf

Intelligence Index vs. Veröffentlichungsdatum

Führende Modelle nach KI-Labor

Effizienz

Inferenzpreis von Sprachmodellen nach Intelligence-Index-Band im Zeitverlauf

Ausgabegeschwindigkeit von Sprachmodellen nach Intelligence-Index-Band im Zeitverlauf

Länderanalyse

Intelligenz von Frontier-Sprachmodellen nach Land im Zeitverlauf

Offene Gewichte: Intelligenz von Frontier-Sprachmodellen nach Land im Zeitverlauf

Leading Models by Country

Modelle mit offenen Gewichten

Progress in Open Weights vs. Proprietary Intelligence

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Modellarchitektur

Intelligence Index vs. Veröffentlichungsdatum nach Modellarchitektur

Model Size: Total and Active Parameters

Intelligence Index vs. Active Parameters

Intelligence Index vs. Gesamtparameter

Kontextlänge (Tokens), Median je Quartal

Trainingsanalyse

Trainingstokens nach Modell

Intelligence Index vs. Trainingstokens

KI-Trends von Artificial Analysis

State of AI (Highlights) – Jahresende 2025

Fortschritt der KI

Frontier Language Model Intelligence, Over Time

Artificial Analysis Intelligence Index

Investitionsausgaben großer Technologieunternehmen im Zeitverlauf

Capital Expenditure (Capex)

Capex Data Sources Note

Intelligence Index vs. Veröffentlichungsdatum

Artificial Analysis Intelligence Index

Führende Modelle nach KI-Labor

Artificial Analysis Intelligence Index

Effizienz

Inferenzpreis von Sprachmodellen nach Intelligence-Index-Band im Zeitverlauf

Artificial Analysis Intelligence Index

Ausgabegeschwindigkeit von Sprachmodellen nach Intelligence-Index-Band im Zeitverlauf

Artificial Analysis Intelligence Index

Länderanalyse

Intelligenz von Frontier-Sprachmodellen nach Land im Zeitverlauf

Artificial Analysis Intelligence Index

Offene Gewichte: Intelligenz von Frontier-Sprachmodellen nach Land im Zeitverlauf

Artificial Analysis Intelligence Index

Leading Models by Country

Artificial Analysis Intelligence Index

Modelle mit offenen Gewichten

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

Modellarchitektur

Intelligence Index vs. Veröffentlichungsdatum nach Modellarchitektur

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. Gesamtparameter

Artificial Analysis Intelligence Index

Total Parameters

Kontextlänge (Tokens), Median je Quartal

Context Window for RAG

Context Window

Trainingsanalyse

Trainingstokens nach Modell

Training Tokens

Intelligence Index vs. Trainingstokens

Artificial Analysis Intelligence Index

Training Tokens