Volleyball
Volleyball IntelligenceUpgraded
Synthetic Analysis Intelligence Index
Synthetic Analysis Intelligence Index v4.3.2 integrates 10 assessments: 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
Synthetic Analysis Intelligence Index v4.3.2 consists of: 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 approach for more information, consisting of a breakdown of each examination and how we run them.
Synthetic Analysis Intelligence Index by Open Weights/ Proprietary
Synthetic Analysis Intelligence Index v4.3.2 integrates 10 examinations
: 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
Synthetic Analysis Intelligence Index v4.3.2 consists of: 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 method for additional information, consisting of a breakdown of each assessment and how we run them.
Shows whether the design weights are readily available. Designs are identified as ‘Commercial Use Restricted’ if business usage is restricted by conditions, and as’Non-commercial’if the license restricts industrial usage.
Volleyball Ability Indexes
Steps the efficiency of designs on particular abilities and markets
Intelligence Evaluations
Intelligence examinations determined separately by Artificial Analysis · Higher is much better
Agentic real-world work jobs,(Elo-500)/ 2000
Agentic coding & terminal usage
Expert file thinking, All-pass
Medical long context thinking
While design intelligence typically equates throughout usage cases, particular assessments might be more appropriate for particular usage cases.
Synthetic Analysis Intelligence Index v4.3.2 consists of: 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 approach for additional information, consisting of a breakdown of each assessment and how we run them.
AA-Briefcase v1.1 Upgraded
AA-Briefcase Elo
AA-Briefcase v1.1 is an agentic understanding work criteria established by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and discussion Elo · Higher is much better
AA-Omniscience
AA-Omniscience Index
AA-Omniscience Index (greater is much better)determines understanding dependability and hallucination. It rewards appropriate responses, punishes hallucinations, and has no charge for declining to respond to. Ratings vary from -100 to 100, where 0 methods as lots of proper as inaccurate responses, and unfavorable ratings imply more inaccurate than appropriate.
AA-Omniscience Index( greater is much better)determines understanding dependability and hallucination. It rewards proper responses, punishes hallucinations, and has no charge for declining to respond to. Ratings vary from -100 to 100, where 0 methods as lots of right as inaccurate responses, and unfavorable ratings indicate more inaccurate than proper.
AA-Omniscience Index
AA-Omniscience Index (greater is much better)determines understanding dependability and hallucination. It rewards appropriate responses, punishes hallucinations, and has no charge for declining to respond to. Ratings vary from -100 to 100, where 0 methods as lots of proper as inaccurate responses, and unfavorable ratings imply more inaccurate than appropriate.
Volleyball Openness Index
Synthetic Analysis Openness Index: Score
Openness Index examines design openness on a 0 to 100 stabilized scale(greater is more open)
Volleyball Intelligence Index Comparisons
Intelligence Index vs. Cost per Intelligence Index Task
Synthetic Analysis Intelligence Index · Weighted typical expense (USD )per Artificial Analysis Intelligence Index job
Weighted typical expense per Intelligence Index job. Each examination’s expense is determined from input, cache hit, cache compose, thinking, and address token rates, divided by job count, and weighted by its Intelligence Index weight.
Synthetic Analysis Intelligence Index v4.3.2 consists of: 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 approach for additional information, consisting of a breakdown of each assessment and how we run them.
Volleyball Token Use
Output Tokens per Intelligence Index Task
Weighted typical variety of output tokens utilized to run one job in the Artificial Analysis
The variety of tokens needed per Intelligence Index job. This is determined by increasing the output tokens per eval by the relative weights of each criteria in the Intelligence Index, then dividing by job count(omitting repeats).
[19659061]Expense
Expense per Intelligence Index Task
Weighted typical expense(USD)per Artificial Analysis Intelligence Index job, segmented by token type. Lower is much better
Weighted typical expense per Intelligence Index job. Each examination’s expense is computed from input, cache hit, cache compose, thinking, and address token costs, divided by job count, and weighted by its Intelligence Index weight.
Expense to Run Artificial Analysis Intelligence Index
Expense (USD)to run all assessments in the Artificial Analysis Intelligence Index
The expense to run the examinations in the Artificial Analysis Intelligence Index, determined utilizing the design’s input, cache hit, cache compose, thinking, and respond to token costs and the variety of tokens utilized throughout examinations(omitting repeats).
Prices: Cache Hit, Input, and Output
Cost(USD per M Tokens )
Rate per token for cached triggers( formerly processed ), generally providing a substantial discount rate compared to routine input rate, represented as USD per million tokens. The worths revealed here are the cache struck rate; cache compose and cache storage are billed independently and
differ by company– see “Cache pricing by provider” for information.
Volleyball Context Window
Context Window
Context window: tokens restrict · Higher is much better
Volleyball Context Window
Context Window
Context window: tokens restrict · Higher is much better
Bigger context windows pertain to RAG (Retrieval Augmented Generation)LLM workflows which usually include thinking and details retrieval of big quantities of information.[ [ Optimum variety of combined input & output tokens. Output tokens typically have a considerably lower limitation(differed by design). Determined by Output Speed(tokens per second ) Output tokens per 2nd · Higher is much better Tokens per 2nd gotten while the design is producing tokens (ie. after very first piece has actually been gotten from the API for designs which support streaming). Figures represent efficiency of the design’s first-party API or the typical throughout service providers where a first-party API is not readily available. Weighted typical decode time (minutes) per job; leaves out TTFT and overhead time · Lower is much better The weighted typical time (seconds) per Artificial Analysis Intelligence Index job. This is determined by dividing output tokens per job by output speed, weighted by the relative weights of each criteria in the Intelligence Index. Determined by Time (seconds) to First Token Seconds to very first response token got · Accounts for thinking design ‘believing’ time Time to very first response token gotten, in seconds, after API demand sent out. For thinking designs, this consists of the ‘thinking’ time of the design before offering a response. For designs which do not support streaming, this represents time to get the conclusion. Seconds to output 500 tokens, computed based upon time to very first token, ‘believing’ time for thinking designs, and output speed Seconds to output 500 tokens, consisting of thinking design ‘believing’ time · Lower is much better Seconds to get a 500 token action. Secret parts: Figures represent efficiency of the design’s first-party API or the typical throughout suppliers where a first-party API is not offered. Contrast in between overall design specifications and criteria active throughout reasoning The overall variety of trainable weights and predispositions in the design, revealed in billions. These criteria are found out throughout training and identify the design’s capability to procedure and produce actions. The variety of criteria in fact performed throughout each reasoning forward pass, revealed in billions. For Mixture of Experts (MoE) designs, a routing system chooses a subset of specialists per token, leading to less active than overall criteria. Thick designs utilize all specifications, so active equates to overall. 19659084]
Volleyball Speed
Output Speed
Time per Intelligence Index Task
Volleyball Latency
Latency: Time To First Answer Token
Volleyball End-to-End Response Time
End-to-End Response Time
Volleyball Design Size (Open Weights Models Only)
Design Size: Total and Active Parameters
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