Idioma Iorubá — Benchmark de modelos de IA Compare o desempenho multilíngue dos LLMs

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

Os 5 melhores modelos de IA para tarefas em iorubá são Gemini 3.1 Pro Preview, Gemini 3 Pro Preview (high), Gemini 3 Flash, Claude Opus 4.6 (max) e Claude Opus 4.5. Eles alcançam as maiores pontuações de raciocínio em iorubá no Artificial Analysis Multilingual Index.

Para comparar o desempenho em todos os idiomas disponíveis, consulte a página completa do benchmark multilíngue de modelos de IA.

🇳🇬 Melhores modelos para o idioma Iorubá

Gemini 3.1 Pro Preview

89#2

Gemini 3 Pro Preview (high)

86#3

Gemini 3 Flash

85#4

Claude Opus 4.6 (max)

84#5

Claude Opus 4.5

Destaques

Inteligência

Multilingual Index: Yoruba · Higher is better

Velocidade

Output tokens per second · Higher is better

Preço

USD per 1M tokens (blended) · Lower is better

Multilingual Index

Multilingual Index: idioma Iorubá

Artificial Analysis Multilingual Index · Higher is better

Based on the Global-MMLU-Lite evaluation, assessing general reasoning performance in a single language. Results are computed exclusively within the selected language. See methodology for further details.

Multilingual Index: idioma Iorubá vs. preço

Artificial Analysis Multilingual Index · USD per 1M tokens (blended)

Most attractive quadrant

While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.

Multilingual Index: idioma Iorubá vs. velocidade de saída

Artificial Analysis Multilingual Index · Output speed: output tokens per second

Most attractive quadrant

There is a trade-off between model quality and output speed, with higher intelligence models typically having lower output speed.

Multilingual Index: idioma Iorubá vs. janela de contexto

Artificial Analysis Multilingual Index · Context window: tokens limit

Most attractive quadrant

Global-MMLU-Lite

Global-MMLU-Lite multilíngue: idioma Iorubá

Multilingual Global-MMLU-Lite · Higher is better

A multilingual version of Massive Multitask Language Understanding, evaluated across multiple languages. Tests general knowledge and reasoning ability in areas like science, humanities, mathematics and more. See methodology for further details.

Preços

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens)

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

Velocidade e latência

Output Speed

Output tokens per second · Higher is better

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Latency: Time To First Answer Token

Seconds to first answer token received · Accounts for reasoning model 'thinking' time

Time to first answer token received, in seconds, after API request sent. For reasoning models, this includes the 'thinking' time of the model before providing an answer. For models which do not support streaming, this represents time to receive the completion.

End-to-End Response Time

Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better

Seconds to receive a 500 token response. Key components:

Input time: Time to receive the first response token
Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details).
Answer time: Time to generate 500 output tokens, based on output speed

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Idioma Iorubá — Benchmark de modelos de IA Compare o desempenho multilíngue dos LLMs

🇳🇬 Melhores modelos para o idioma Iorubá

Inteligência

Velocidade

Preço

Multilingual Index

Multilingual Index: idioma Iorubá

Per-Language Reasoning Index

Multilingual Index: idioma Iorubá vs. preço

Price-Quality Variance

Multilingual Index: idioma Iorubá vs. velocidade de saída

Intelligence vs. Speed Trade-off

Multilingual Index: idioma Iorubá vs. janela de contexto

Per-Language Reasoning Index

Global-MMLU-Lite

Global-MMLU-Lite multilíngue: idioma Iorubá

Global-MMLU-Lite

Preços

Pricing: Cache Hit, Input, and Output

Cache Hit

Velocidade e latência

Output Speed

Output Speed

Model Performance Representation

Latency: Time To First Answer Token

Time to First Answer Token

End-to-End Response Time

End-to-End Response Time

Model Performance Representation