Head-to-Head Model Comparison

GPT-5.2 Pro vs Claude Opus 4.7

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

Cambia e Confronta Qualsiasi Modello

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

GPT-5.2 ProProfile

Claude Opus 4.7Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

OpenAI

GPT-5.2 Pro

Motore di Ragionamento Profondo

GPT-5.2 Pro di OpenAI è un modello di IA progettato per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, con finestra di contesto da 400K, velocità di 50 token/s, indice di intelligenza di 69/100 e tariffa di

Intelligence Index69 / 100

Input Token:

$17.50 / 1M

Output Token:

$140.00 / 1M

Context Window:

400K tokens

SWE-bench Verified:

79.4%

Anthropic

Claude Opus 4.7

Modello Ammiraglia di Frontiera

Claude Opus 4.7 di Anthropic 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 1M, velocità di 58 token/s, indice di intelligenza di 6

Intelligence Index66 / 100

Input Token:

$5.00 / 1M

Output Token:

$25.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

79.5%

Differenze Chiave a Colpo d’Occhio

Claude Opus 4.7 is 5.0x cheaper for API usage (input + output tokens combined).
Claude Opus 4.7 has a larger context window (1M vs 400K tokens).
Claude Opus 4.7 is faster at 58 tok/s vs 50 tok/s.
Claude Opus 4.7 leads on SWE-bench coding (79.5% vs 79.4%).

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

Feature	GPT-5.2 Pro	Claude Opus 4.7
Intelligence Index Composite reasoning & knowledge score (0-100)	69	66
Provider	OpenAI	Anthropic
Input Price Cost per million input tokens	$17.50 / 1M	$5.00 / 1M
Output Price Cost per million output tokens	$140.00 / 1M	$25.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$18.73 / 1M	$3.85 / 1M
Context Window Maximum input + output tokens	400K tokens~600 A4 pages of text	1M tokens~1,500 A4 pages of text
Max Output Tokens Per single request	128K	128K
Throughput Speed Tokens generated per second	50 tok/s	58 tok/s
SWE-bench Verified Real-world software engineering	79.4%	79.5%
GPQA Diamond Graduate-level reasoning	79%	77.8%
Cached Input Price Prompt caching discount per 1M tokens	$1.75 / 1M	$0.50 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Claude Opus 4.7

+0.1% SWE-bench lead

Cost

Claude Opus 4.7

5.0x cheaper monthly runtime

Speed

Claude Opus 4.7

+16% faster generation

Context

Claude Opus 4.7

1M tokens window

Punteggi Benchmark Verificati

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

GPT-5.2 ProClaude Opus 4.7

SWE-bench Verified (Autonomous Coding)

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

79.4%vs79.5%

GPQA Diamond (Doctorate-Level Science & Math)

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

79%vs77.8%

MMLU-Pro (Multi-task Language Understanding)

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

88.6%vs89%

LMSYS Chatbot Arena Elo

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

1410ptsvs1405pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

14.8%vsN/A

Terminal-Bench (Agentic Coding & Terminal Use)

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

55%vs52.8%

SciCode (Scientific Computing)

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

50%vsN/A

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

77.6%vsN/A

AIME (Advanced Math Competition)

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

94%vsN/A

Long-Context Reasoning

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

83.5%vsN/A

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

50 tok/s vs58 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-5.2 Pro4.40s

Claude Opus 4.71.85s

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

GPT-5.2 Pro14.40s

Claude Opus 4.710.47s

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 Pro Monthly API Bill

$154.88 / month

$17.5/1M in · $140/1M out

Claude Opus 4.7 Monthly API Bill

$30.75 / month

$5/1M in · $25/1M out

Claude Opus 4.7 saves approximately $124.13 / month (80%) under this workload.5.0x Savings

GPT-5.2 Pro · Strengths & Key Advantages

Finestra di contesto da 400K con capacità massima di output fino a 128K token (SWE-bench Verified 79.4% · GPQA Diamond 79%)
Throughput elevato di 50 token/secondo con latenza al primo token (TTFT) di soli 4400 ms
Economia API competitiva ($17.5/$140 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
Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Claude Opus 4.7 · Strengths & Key Advantages

Finestra di contesto da 1M con capacità massima di output fino a 128K token (SWE-bench Verified 79.5% · GPQA Diamond 77.8%)
Throughput elevato di 58 token/secondo con latenza al primo token (TTFT) di soli 1850 ms
Economia API competitiva ($5/$25 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
Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Token Use & Task Economics

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

Metric	GPT-5.2 Pro	Claude Opus 4.7
Cost per Task Estimated USD to finish one task	$23.24	$5.49
Output Tokens / Task Tokens generated per task	70K	72K
Reasoning Tokens / Task Thinking tokens burned per task	46K	37K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	GPT-5.2 Pro	Claude Opus 4.7
Official API Model ID (SDK)	gpt-5-2-pro	claude-opus-4-7-20260401
API Protocol	OpenAI Responses API & Chat Completions v1	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2025-12	2026-04
Knowledge Cutoff	August 2025	February 2026
Architecture	Maximum-compute unified reasoning model	Adaptive Enterprise Reasoning Transformer
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($17.5/1M in) across full 400K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Automatic prefix caching at $1.75/1M (no extra cache-write fee)	$0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL
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 Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	Custom Model Tuning via Amazon Bedrock & Prompt Distillation
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	Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
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 Pro vs Claude Opus 4.7: Risposte Rapide (FAQ)

Which is more intelligent, GPT-5.2 Pro or Claude Opus 4.7?

GPT-5.2 Pro is more intelligent. It scores 69 compared with 66 on the composite Intelligence Index.

Which model is faster?

Claude Opus 4.7 is faster, generating 58 tokens per second compared with 50 tokens per second.

Which model is cheaper to run?

Claude Opus 4.7 is cheaper at $3.85 per 1M tokens blended, compared with $18.73 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude Opus 4.7 has lower latency, with a time to first token of 1.85s compared with 4.40s.

Which model has a larger context window?

Claude Opus 4.7 has a larger context window, supporting 1M tokens compared with 400K tokens.

Verdetto

Sia GPT-5.2 Pro (Ideale per il ragionamento logico profondo, la matematica avanzata e l’analisi scientifica, sistemi RAG aziendali e integrazioni API scalabili.) sia Claude Opus 4.7 (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 Pro guida nei benchmark di ragionamento e programmazione, Claude Opus 4.7 garantisce una generazione più rapida e Claude Opus 4.7 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, GPT-5.2 Pro o Claude Opus 4.7?+

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

Qual è la differenza di prezzo API tra GPT-5.2 Pro e Claude Opus 4.7?+

GPT-5.2 Pro costa $17.50 / $140.00 per milione di token di input/output, mentre Claude Opus 4.7 costa $5.00 / $25.00. Nel costo combinato, Claude Opus 4.7 risulta più economico.

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

GPT-5.2 Pro supporta 400K token di contesto contro 1M token di Claude Opus 4.7, mentre Claude Opus 4.7 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 Pro vs Claude Opus 4.7

Cambia e Confronta Qualsiasi Modello

GPT-5.2 Pro

Claude Opus 4.7

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

GPT-5.2 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Claude Opus 4.7 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

GPT-5.2 Pro vs Claude Opus 4.7: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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