Celeris: inteligencia, rendimiento y precio de sus modelos

Celeris
Celeris

Análisis de los modelos de Celeris en métricas clave como calidad, precio, velocidad de salida, latencia, ventana de contexto y más. Este análisis está pensado para ayudarte a elegir el mejor modelo ofrecido por Celeris para tu caso de uso.

Más inteligente

#1
Celeris-1
Celeris-1
12

Índice de inteligencia

1 modelo en total

Más rápido

#1
Celeris-1
Celeris-1
2,035 t/s

Velocidad de salida

1 modelo en total

Menor precio

#1
Celeris-1
Celeris-1
$2.40

Precio combinado (por 1M de tokens)

1 modelo en total

Celeris actualmente ofrece Celeris-1.

Aspectos destacados

Artificial Analysis Intelligence Index · Higher is better
Output tokens per second · Higher is better
USD per 1M tokens (blended) · Lower is better

Evaluaciones de inteligencia

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR
Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

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

Agentic tool use

Agentic coding & terminal use

Coding

Reasoning & knowledge

Scientific reasoning

Physics reasoning

Long context reasoning

Agentic knowledge work, Elo

No data available

Agentic SaaS workflows

No data available

Legal agentic work, criterion pass rate

No data available

Agentic business operations

No data available

Instruction following

No data available

Long-horizon agentic tasks

No data available

Kubernetes incident root-cause analysis

No data available

Visual reasoning

No data available
Reasoning models are indicated by a lightbulb icon

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

Intelligence Index vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)
Most attractive quadrant
Reasoning models are indicated by a lightbulb icon

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

Ventana de contexto

Context Window

Context window: tokens limit · Higher is better
Reasoning models are indicated by a lightbulb icon

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Precios

Intelligence Index vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)
Most attractive quadrant
Reasoning models are indicated by a lightbulb icon

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

Resumen de rendimiento

Output Speed vs. Price

Output speed: output tokens per second · USD per 1M tokens (blended)
Most attractive quadrant
Reasoning models are indicated by a lightbulb icon

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).

Velocidad

Medida por la velocidad de salida (tokens por segundo)

Output Speed

Output tokens per second · Higher is better
Reasoning models are indicated by a lightbulb icon

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).

Latencia

Medida por el tiempo (segundos) hasta el primer token

Latency: Time To First Token

Seconds to first token received · Lower is better
Reasoning models are indicated by a lightbulb icon

Time to first token received, in seconds, after API request sent. For reasoning models which share reasoning tokens, this will be the first reasoning token. For models which do not support streaming, this represents time to receive the completion.

Tiempo de respuesta de extremo a extremo

Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

End-to-End Response Time vs. Price

End-to-end response time: end-to-end seconds to output 500 tokens · USD per 1M tokens (blended)
Most attractive quadrant

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

Análisis adicional
Logo de Celeris
Celeris-1
131k
Propietario
12
--
2,035
0.63
0.87
--

Definiciones clave

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Preguntas frecuentes

Preguntas comunes sobre Celeris

Celeris ofrece 1 modelo que monitoreamos: Celeris-1.

El modelo más inteligente disponible en Celeris es Celeris-1, con una puntuación de 12 en el Índice de Inteligencia.

El modelo más rápido en Celeris por velocidad de salida es Celeris-1, con 2,035.1 tokens por segundo.

El modelo con el menor tiempo hasta el primer token de respuesta en Celeris es Celeris-1, con 0.63s. Una menor latencia significa una respuesta inicial más rápida.

El modelo más económico en Celeris por precio combinado es Celeris-1, a $2.40 por 1M de tokens (proporción 7:2:1 de aciertos de caché/entrada/salida).

Sí, Celeris ofrece una API compatible con OpenAI, lo que facilita cambiar desde OpenAI o usar integraciones existentes del SDK de OpenAI.

Sí, los 1 modelos en Celeris admiten llamadas a funciones (uso de herramientas).

Sí, el rendimiento de un proveedor puede variar con el tiempo debido a cambios de infraestructura, balanceo de carga y actualizaciones. Medimos continuamente a todos los proveedores y mostramos las tendencias históricas de rendimiento en los gráficos "a lo largo del tiempo".

Al elegir un modelo en Celeris, considera: inteligencia (para tareas sensibles a la calidad), velocidad de salida (para tareas intensivas en rendimiento), latencia (para aplicaciones interactivas que requieren primeras respuestas rápidas), precios (para cargas de trabajo sensibles al costo) y funcionalidades como el tamaño de la ventana de contexto, el modo JSON o las llamadas a funciones.