Head-to-Head Model Comparison

GPT-5.4 vs GPT-5.4 mini

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial

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GPT-5.4Profile

GPT-5.4 miniProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT-5.4

IA Agéntica y Uso de Herramientas

GPT-5.4 de OpenAI es un modelo de IA diseñado para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, con ventana de contexto de 1.1M, velocidad de 126 tokens/s, índice de inteligencia de 78/100 y tarif

Intelligence Index78 / 100

Input Token:

$2.50 / 1M

Output Token:

$15.00 / 1M

Context Window:

1.05M tokens

SWE-bench Verified:

79.2%

OpenAI

GPT-5.4 mini

Modelo Ligero y Económico

GPT-5.4 mini de OpenAI es un modelo de IA diseñado para máxima eficiencia de costos por token y alta velocidad en producción, con ventana de contexto de 400K, velocidad de 175 tokens/s, índice de inteligencia de 59/100 y tarifa de $0.5/$4 p

Intelligence Index59 / 100

Input Token:

$0.50 / 1M

Output Token:

$4.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

68.5%

Diferencias Clave de un Vistazo

GPT-5.4 mini is 4.0x cheaper for API usage (input + output tokens combined).
GPT-5.4 has a larger context window (1M vs 400K tokens).
GPT-5.4 mini is faster at 175 tok/s vs 126 tok/s.
GPT-5.4 leads on SWE-bench coding (79.2% vs 68.5%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Característica	GPT-5.4	GPT-5.4 mini
Intelligence Index Composite reasoning & knowledge score (0-100)	78	59
Provider	OpenAI	OpenAI
Input Price Cost per million input tokens	$2.50 / 1M	$0.50 / 1M
Output Price Cost per million output tokens	$15.00 / 1M	$4.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.17 / 1M	$0.53 / 1M
Context Window Maximum input + output tokens	1.05M tokens~1,575 A4 pages of text	400K tokens~600 A4 pages of text
Max Output Tokens Per single request	128K	128K
Throughput Speed Tokens generated per second	126 tok/s	175 tok/s
SWE-bench Verified Real-world software engineering	79.2%	68.5%
GPQA Diamond Graduate-level reasoning	78.6%	72.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.25 / 1M	$0.05 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

GPT-5.4

+10.7% SWE-bench lead

Costo

GPT-5.4 mini

4.0x cheaper monthly runtime

Velocidad

GPT-5.4 mini

+39% faster generation

Contexto

GPT-5.4

1.05M tokens window

Puntuaciones de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

GPT-5.4GPT-5.4 mini

SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

79.2%vs68.5%

GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

78.6%vs72.5%

MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

88.6%vs84.8%

LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1436ptsvs1375pts

Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

15.4%vs12.2%

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

54.5%vs41.5%

SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

49.5%vs40%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

77%vs67%

AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

93.8%vs89.6%

Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

84.5%vs78%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

126 tok/s vs175 tok/s

Latencia y Tiempo de Respuesta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better

GPT-5.41.08s

GPT-5.4 mini0.76s

Est. End-to-End Response (500 tokens)TTFT + generation time

GPT-5.45.05s

GPT-5.4 mini3.62s

Simulador Interactivo de Costos de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

GPT-5.4 Monthly API Bill

$17.63 / month

$2.5/1M in · $15/1M out

GPT-5.4 mini Monthly API Bill

$4.42 / month

$0.5/1M in · $4/1M out

GPT-5.4 mini saves approximately $13.20 / month (75%) under this workload.4.0x Savings

GPT-5.4 · Strengths & Key Advantages

Ventana de contexto de 1.1M con hasta 128K tokens de salida máxima (SWE-bench Verified 79.2% · GPQA Diamond 78.6%)
Rendimiento ágil de 126 tokens/segundo con latencia inicial (TTFT) de solo 1080 ms
Economía de API competitiva ($2.5/$15 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas

Considerations & Trade-offs

Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
En volúmenes masivos de tokens, se recomienda activar el caché de prompts y Batch API para optimizar costos

GPT-5.4 mini · Strengths & Key Advantages

Ventana de contexto de 400K con hasta 128K tokens de salida máxima (SWE-bench Verified 68.5% · GPQA Diamond 72.5%)
Rendimiento ágil de 175 tokens/segundo con latencia inicial (TTFT) de solo 760 ms
Economía de API competitiva ($0.5/$4 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas

Considerations & Trade-offs

Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
En demostraciones científicas extremas, los modelos de razonamiento pesado de gama alta ofrecen mayor profundidad

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metric	GPT-5.4	GPT-5.4 mini
Cost per Task Estimated USD to finish one task	$2.10	$0.62
Output Tokens / Task Tokens generated per task	62K	52K
Reasoning Tokens / Task Thinking tokens burned per task	34K	27K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	GPT-5.4	GPT-5.4 mini
Official API Model ID (SDK)	gpt-5-4	gpt-5-4-mini
API Protocol	OpenAI Responses API & Chat Completions v1	OpenAI Responses API & Chat Completions v1
Release Date	2026-03	2026-03
Knowledge Cutoff	August 2025	August 2025
Architecture	Agent-ready unified reasoning model	Compact agent-ready reasoning model
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($2.5/1M in) across full 1050K window	Flat rate ($0.5/1M in) across full 400K window
Prompt Cache Policy & TTL	Automatic prefix caching at $0.25/1M (no extra cache-write fee)	Automatic prefix caching at $0.05/1M (no extra cache-write fee)
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool Calling	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Native Web Search tool + Hosted Code Interpreter & File Search RAG	Native Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
Quantization & Min GPU VRAM	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	OpenAI Preparedness Framework Audited & System Card Published	OpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text, vision	text, vision
Output Modalities	text	text

GPT-5.4 vs GPT-5.4 mini: Respuestas Rápidas (FAQ)

Which is more intelligent, GPT-5.4 or GPT-5.4 mini?

GPT-5.4 is more intelligent. It scores 78 compared with 59 on the composite Intelligence Index.

Which model is faster?

GPT-5.4 mini is faster, generating 175 tokens per second compared with 126 tokens per second.

Which model is cheaper to run?

GPT-5.4 mini is cheaper at $0.53 per 1M tokens blended, compared with $2.17 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-5.4 mini has lower latency, with a time to first token of 0.76s compared with 1.08s.

Which model has a larger context window?

GPT-5.4 has a larger context window, supporting 1.05M tokens compared with 400K tokens.

Veredicto

Tanto GPT-5.4 (Ideal para flujos de trabajo agénticos autónomos, llamada a herramientas y automatización compleja, sistemas RAG empresariales y automatización mediante API.) como GPT-5.4 mini (Ideal para máxima eficiencia de costos por token y alta velocidad en producción, sistemas RAG empresariales y automatización mediante API.) destacan en producción: GPT-5.4 lidera en inteligencia general y programación, GPT-5.4 mini ofrece mayor velocidad de generación de tokens y GPT-5.4 mini resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, GPT-5.4 o GPT-5.4 mini?+

En las pruebas de inteligencia compuesta y resolución de código, GPT-5.4 obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de GPT-5.4 frente a GPT-5.4 mini?+

GPT-5.4 cuesta $2.50 / $15.00 por millón de tokens de entrada/salida, mientras que GPT-5.4 mini cuesta $0.50 / $4.00. En costo combinado, GPT-5.4 mini es la opción más económica.

¿Qué modelo tiene mayor ventana de contexto y menor latencia?+

GPT-5.4 cuenta con 1.05M tokens de contexto frente a 400K tokens de GPT-5.4 mini. En velocidad de inferencia, GPT-5.4 mini ofrece un rendimiento superior.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

GPT-5.4 vs GPT-5.4 mini

Cambia y Compara Cualquier Modelo

GPT-5.4

GPT-5.4 mini

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

GPT-5.4 · Strengths & Key Advantages

Considerations & Trade-offs

GPT-5.4 mini · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

GPT-5.4 vs GPT-5.4 mini: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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