Head-to-Head Model Comparison

GPT-5.2 vs GPT-5.2 Chat

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale

Cambia e Confronta Qualsiasi Modello

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GPT-5.2Profile

GPT-5.2 ChatProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT-5.2

Modello Ammiraglia di Frontiera

GPT-5.2 di OpenAI è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 400K, velocità di 128 token/s, indice di intelligenza di 65/100 e

Intelligence Index65 / 100

Input Token:

$1.75 / 1M

Output Token:

$14.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

76.5%

OpenAI

GPT-5.2 Chat

Modello Ammiraglia di Frontiera

GPT-5.2 Chat di OpenAI è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 128K, velocità di 135 token/s, indice di intelligenza di 63/1

Intelligence Index63 / 100

Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

75.4%

Differenze Chiave a Colpo d’Occhio

GPT-5.2 Chat is 1.0x cheaper for API usage (input + output tokens combined).
GPT-5.2 has a larger context window (400K vs 128K tokens).
GPT-5.2 Chat is faster at 135 tok/s vs 128 tok/s.
GPT-5.2 leads on SWE-bench coding (76.5% vs 75.4%).

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

Feature	GPT-5.2	GPT-5.2 Chat
Intelligence Index Composite reasoning & knowledge score (0-100)	65	63
Provider	OpenAI	OpenAI
Input Price Cost per million input tokens	$1.75 / 1M	$0.00 / 1M
Output Price Cost per million output tokens	$14.00 / 1M	$0.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$1.87 / 1M	$0.00 / 1M
Context Window Maximum input + output tokens	400K tokens~600 A4 pages of text	128K tokens~192 A4 pages of text
Max Output Tokens Per single request	128K	16K
Throughput Speed Tokens generated per second	128 tok/s	135 tok/s
SWE-bench Verified Real-world software engineering	76.5%	75.4%
GPQA Diamond Graduate-level reasoning	77.8%	76.5%
Cached Input Price Prompt caching discount per 1M tokens	$0.17 / 1M	$0.00 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

GPT-5.2

+1.1% SWE-bench lead

Cost

GPT-5.2 Chat

1.0x cheaper monthly runtime

Speed

GPT-5.2 Chat

+5% faster generation

Context

GPT-5.2

400K tokens window

Punteggi Benchmark Verificati

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

GPT-5.2GPT-5.2 Chat

SWE-bench Verified (Autonomous Coding)

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

76.5%vs75.4%

GPQA Diamond (Doctorate-Level Science & Math)

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

77.8%vs76.5%

MMLU-Pro (Multi-task Language Understanding)

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

87.2%vs86.6%

LMSYS Chatbot Arena Elo

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

1388ptsvs1382pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

13.6%vs13%

Terminal-Bench (Agentic Coding & Terminal Use)

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

50%vs48.5%

SciCode (Scientific Computing)

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

46.5%vs45%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

74.8%vs73%

AIME (Advanced Math Competition)

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

93.4%vs92.6%

Long-Context Reasoning

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

81.5%vs80.5%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

128 tok/s vs135 tok/s

Latenza e Tempo di Risposta

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-5.21.12s

GPT-5.2 Chat1.10s

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

GPT-5.25.03s

GPT-5.2 Chat4.80s

Simulatore Interattivo dei Costi Token

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 Monthly API Bill

$15.49 / month

$1.75/1M in · $14/1M out

GPT-5.2 Chat Monthly API Bill

$0.00 / month

$0/1M in · $0/1M out

GPT-5.2 Chat saves approximately $15.49 / month (100%) under this workload.1.0x Savings

GPT-5.2 · Strengths & Key Advantages

Finestra di contesto da 400K con capacità massima di output fino a 128K token (SWE-bench Verified 76.5% · GPQA Diamond 77.8%)
Throughput elevato di 128 token/secondo con latenza al primo token (TTFT) di soli 1120 ms
Economia API competitiva ($1.75/$14 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

GPT-5.2 Chat · Strengths & Key Advantages

Finestra di contesto da 128K con capacità massima di output fino a 16K token (SWE-bench Verified 75.4% · GPQA Diamond 76.5%)
Throughput elevato di 135 token/secondo con latenza al primo token (TTFT) di soli 1100 ms
Economia API competitiva (accesso gratuito a pesi aperti) con supporto per prompt caching, tool calling e output JSON strutturati

Considerations & Trade-offs

Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
Nelle dimostrazioni scientifiche più estreme, i modelli di ragionamento pesante dedicati offrono maggiore profondità

Token Use & Task Economics

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

Metric	GPT-5.2	GPT-5.2 Chat
Cost per Task Estimated USD to finish one task	$2.05	$1.90
Output Tokens / Task Tokens generated per task	57K	54K
Reasoning Tokens / Task Thinking tokens burned per task	31K	29K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	GPT-5.2	GPT-5.2 Chat
Official API Model ID (SDK)	gpt-5-2	gpt-5-2-chat
API Protocol	OpenAI Responses API & Chat Completions v1	OpenAI Responses API & Chat Completions v1
Release Date	2025-12	2025-12
Knowledge Cutoff	August 2025	August 2025
Architecture	Unified reasoning model (Instant / Thinking / Pro modes)	Chat-tuned unified reasoning model
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)	Flat rate ($1.75/1M in) across full 400K window	Free across full context window (only KV-cache VRAM scales)
Prompt Cache Policy & TTL	Automatic prefix caching at $0.175/1M (no extra cache-write fee)	Automatic prefix KV-caching in vLLM / SGLang (0 cost)
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
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 vs GPT-5.2 Chat: Risposte Rapide (FAQ)

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

GPT-5.2 is more intelligent. It scores 65 compared with 63 on the composite Intelligence Index.

Which model is faster?

GPT-5.2 Chat is faster, generating 135 tokens per second compared with 128 tokens per second.

Which model is cheaper to run?

GPT-5.2 Chat is cheaper at $0.00 per 1M tokens blended, compared with $1.87 (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 1.12s.

Which model has a larger context window?

GPT-5.2 has a larger context window, supporting 400K tokens compared with 128K tokens.

Verdetto

Sia GPT-5.2 (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) sia GPT-5.2 Chat (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: GPT-5.2 guida nei benchmark di ragionamento e programmazione, GPT-5.2 Chat garantisce una generazione più rapida e GPT-5.2 Chat offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, GPT-5.2 o GPT-5.2 Chat?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale GPT-5.2. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra GPT-5.2 e GPT-5.2 Chat?+

GPT-5.2 costa $1.75 / $14.00 per milione di token di input/output, mentre GPT-5.2 Chat costa $0.00 / $0.00. Nel costo combinato, GPT-5.2 Chat risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

GPT-5.2 supporta 400K token di contesto contro 128K token di GPT-5.2 Chat, mentre GPT-5.2 Chat offre una velocità di generazione superiore.

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 vs GPT-5.2 Chat

Cambia e Confronta Qualsiasi Modello

GPT-5.2

GPT-5.2 Chat

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

GPT-5.2 · Strengths & Key Advantages

Considerations & Trade-offs

GPT-5.2 Chat · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

GPT-5.2 vs GPT-5.2 Chat: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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