Head-to-Head Model Comparison

GPT-5.2 Chat vs GPT-5.1

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-5.2 ChatProfile

GPT-5.1Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT-5.2 Chat

Modelo Insignia de Frontera

GPT-5.2 Chat de OpenAI es un modelo de IA diseñado para razonamiento empresarial de frontera, programación avanzada y flujos de producción, con ventana de contexto de 128K, velocidad de 135 tokens/s, índice de inteligencia de 63/100 y tarif

Intelligence Index63 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

75.4%

OpenAI

GPT-5.1

Modelo Insignia de Frontera

GPT-5.1 de OpenAI es un modelo de IA diseñado para razonamiento empresarial de frontera, programación avanzada y flujos de producción, con ventana de contexto de 400K, velocidad de 130 tokens/s, índice de inteligencia de 60/100 y tarifa de

Intelligence Index60 / 100

Input Token:

$1.25 / 1M

Output Token:

$10.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

74.9%

Diferencias Clave de un Vistazo

GPT-5.2 Chat is 1.0x cheaper for API usage (input + output tokens combined).
GPT-5.1 has a larger context window (400K vs 128K tokens).
GPT-5.2 Chat is faster at 135 tok/s vs 130 tok/s.
GPT-5.2 Chat leads on SWE-bench coding (75.4% vs 74.9%).

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

Característica	GPT-5.2 Chat	GPT-5.1
Intelligence Index Composite reasoning & knowledge score (0-100)	63	60
Provider	OpenAI	OpenAI
Input Price Cost per million input tokens	$0.00 / 1M	$1.25 / 1M
Output Price Cost per million output tokens	$0.00 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$0.00 / 1M	$1.34 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	400K tokens~600 A4 pages of text
Max Output Tokens Per single request	16K	128K
Throughput Speed Tokens generated per second	135 tok/s	130 tok/s
SWE-bench Verified Real-world software engineering	75.4%	74.9%
GPQA Diamond Graduate-level reasoning	76.5%	72.1%
Cached Input Price Prompt caching discount per 1M tokens	$0.00 / 1M	$0.13 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

GPT-5.2 Chat

+0.5% SWE-bench lead

Costo

GPT-5.2 Chat

1.0x cheaper monthly runtime

Velocidad

GPT-5.2 Chat

+4% faster generation

Contexto

GPT-5.1

400K tokens window

Puntuaciones de Benchmarks Verificadas

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

GPT-5.2 ChatGPT-5.1

SWE-bench Verified (Autonomous Coding)

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

75.4%vs74.9%

GPQA Diamond (Doctorate-Level Science & Math)

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

76.5%vs72.1%

MMLU-Pro (Multi-task Language Understanding)

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

86.6%vs86.1%

LMSYS Chatbot Arena Elo

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

1382ptsvs1368pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

13%vs12.1%

Terminal-Bench (Agentic Coding & Terminal Use)

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

48.5%vs46.7%

SciCode (Scientific Computing)

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

45%vs43.2%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

73%vs71.8%

AIME (Advanced Math Competition)

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

92.6%vs91.2%

Long-Context Reasoning

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

80.5%vs77.9%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

135 tok/s vs130 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-5.2 Chat1.10s

GPT-5.11.20s

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

GPT-5.2 Chat4.80s

GPT-5.15.05s

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-5.2 Chat Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

GPT-5.1 Monthly API Bill

$11.06 / month

$1.25/1M in · $10/1M out

GPT-5.2 Chat saves approximately $11.06 / month (100%) under this workload.1.0x Savings

GPT-5.2 Chat · Strengths & Key Advantages

Ventana de contexto de 128K con hasta 16K tokens de salida máxima (SWE-bench Verified 75.4% · GPQA Diamond 76.5%)
Rendimiento ágil de 135 tokens/segundo con latencia inicial (TTFT) de solo 1100 ms
Economía de API competitiva (acceso gratuito de pesos abiertos) 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

GPT-5.1 · Strengths & Key Advantages

Ventana de contexto de 400K con hasta 128K tokens de salida máxima (SWE-bench Verified 74.9% · GPQA Diamond 72.1%)
Rendimiento ágil de 130 tokens/segundo con latencia inicial (TTFT) de solo 1200 ms
Economía de API competitiva ($1.25/$10 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-5.2 Chat	GPT-5.1
Cost per Task Estimated USD to finish one task	$1.90	$1.45
Output Tokens / Task Tokens generated per task	54K	52K
Reasoning Tokens / Task Thinking tokens burned per task	29K	28K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	GPT-5.2 Chat	GPT-5.1
Official API Model ID (SDK)	gpt-5-2-chat	gpt-5-1
API Protocol	OpenAI Responses API & Chat Completions v1	OpenAI Responses API & Chat Completions v1
Release Date	2025-12	2025-11
Knowledge Cutoff	August 2025	October 2024
Architecture	Chat-tuned unified reasoning model	Unified Reasoning (Instant & Thinking)
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Free across full context window (only KV-cache VRAM scales)	Flat rate ($1.25/1M in) across full 400K window
Prompt Cache Policy & TTL	Automatic prefix KV-caching in vLLM / SGLang (0 cost)	Automatic prefix caching at $0.125/1M (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	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-5.2 Chat vs GPT-5.1: Respuestas Rápidas (FAQ)

Which is more intelligent, GPT-5.2 Chat or GPT-5.1?

GPT-5.2 Chat is more intelligent. It scores 63 compared with 60 on the composite Intelligence Index.

Which model is faster?

GPT-5.2 Chat is faster, generating 135 tokens per second compared with 130 tokens per second.

Which model is cheaper to run?

GPT-5.2 Chat is cheaper at $0.00 per 1M tokens blended, compared with $1.34 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-5.2 Chat has lower latency, with a time to first token of 1.10s compared with 1.20s.

Which model has a larger context window?

GPT-5.1 has a larger context window, supporting 400K tokens compared with 128K tokens.

Veredicto

Tanto GPT-5.2 Chat (Ideal para razonamiento empresarial de frontera, programación avanzada y flujos de producción, sistemas RAG empresariales y automatización mediante API.) como GPT-5.1 (Ideal para razonamiento empresarial de frontera, programación avanzada y flujos de producción, sistemas RAG empresariales y automatización mediante API.) destacan en producción: GPT-5.2 Chat lidera en inteligencia general y programación, GPT-5.2 Chat ofrece mayor velocidad de generación de tokens y GPT-5.2 Chat resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, GPT-5.2 Chat o GPT-5.1?+

En las pruebas de inteligencia compuesta y resolución de código, GPT-5.2 Chat obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de GPT-5.2 Chat frente a GPT-5.1?+

GPT-5.2 Chat cuesta $0.00 / $0.00 por millón de tokens de entrada/salida, mientras que GPT-5.1 cuesta $1.25 / $10.00. En costo combinado, GPT-5.2 Chat es la opción más económica.

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

GPT-5.2 Chat cuenta con 128K tokens de contexto frente a 400K tokens de GPT-5.1. En velocidad de inferencia, GPT-5.2 Chat 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-5.2 Chat vs GPT-5.1

Cambia y Compara Cualquier Modelo

GPT-5.2 Chat

GPT-5.1

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

GPT-5.2 Chat · Strengths & Key Advantages

Considerations & Trade-offs

GPT-5.1 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

GPT-5.2 Chat vs GPT-5.1: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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