Head-to-Head Model Comparison

GPT-5.2 Chat vs Claude Opus 4.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
GPT-5.2 Chat vs Claude Opus 4.5: Benchmarks, Pricing & Speed Comparison

GPT-5.2 Chat da OpenAI e Claude Opus 4.5 da Anthropic são dois modelos de IA de destaque. O GPT-5.2 Chat oferece uma janela de contexto de 128K tokens a $0.00/$0.00 por milhão de tokens, enquanto o Claude Opus 4.5 oferece 200K tokens de contexto a $5.00/$25.00 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.

Comparação Direta (VS)

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OpenAI

GPT-5.2 Chat

Modelo Principal de Fronteira

O GPT-5.2 Chat da OpenAI é um modelo de IA projetado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, oferecendo janela de contexto de 128K, velocidade de 135 tokens/s, índice de inteligência de 63/100 e

Intelligence Index63 / 100
Input Token:

$0.00 / 1M

Output Token:

$0.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

75.4%

Anthropic

Claude Opus 4.5

Modelo Principal de Fronteira

O Claude Opus 4.5 da Anthropic é um modelo de IA projetado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, oferecendo janela de contexto de 200K, velocidade de 62 tokens/s, índice de inteligência de 63/1

Intelligence Index63 / 100
Input Token:

$5.00 / 1M

Output Token:

$25.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

77.2%

Principais Diferenças em Resumo

  • GPT-5.2 Chat is 1.0x cheaper for API usage (input + output tokens combined).
  • Claude Opus 4.5 has a larger context window (200K vs 128K tokens).
  • GPT-5.2 Chat is faster at 135 tok/s vs 62 tok/s.
  • Claude Opus 4.5 leads on SWE-bench coding (77.2% vs 75.4%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGPT-5.2 ChatClaude Opus 4.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
6363
Provider
OpenAIAnthropic
Input Price
Cost per million input tokens
$0.00 / 1M$5.00 / 1M
Output Price
Cost per million output tokens
$0.00 / 1M$25.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.00 / 1M$3.85 / 1M
Context Window
Maximum input + output tokens
128K tokens~192 A4 pages of text200K tokens~300 A4 pages of text
Max Output Tokens
Per single request
16K64K
Throughput Speed
Tokens generated per second
135 tok/s62 tok/s
SWE-bench Verified
Real-world software engineering
75.4%77.2%
GPQA Diamond
Graduate-level reasoning
76.5%74.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.00 / 1M$0.50 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding
Claude Opus 4.5
+1.8% SWE-bench lead
Cost
GPT-5.2 Chat
1.0x cheaper monthly runtime
Speed
GPT-5.2 Chat
+118% faster generation
Context
Claude Opus 4.5
200K tokens window

Pontuações de Benchmarks Verificadas

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

GPT-5.2 ChatClaude Opus 4.5
SWE-bench Verified (Autonomous Coding)

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

75.4%vs77.2%
GPQA Diamond (Doctorate-Level Science & Math)

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

76.5%vs74.8%
MMLU-Pro (Multi-task Language Understanding)

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

86.6%vs87.3%
LMSYS Chatbot Arena Elo

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

1382ptsvs1376pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

13%vs13.7%
Terminal-Bench (Agentic Coding & Terminal Use)

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

48.5%vs49.2%
SciCode (Scientific Computing)

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

45%vs45.6%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

73%vs74.1%
AIME (Advanced Math Competition)

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

92.6%vs88.5%
Long-Context Reasoning

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

80.5%vs79.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

135 tok/s vs62 tok/s

Latência e Tempo de Resposta

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
Claude Opus 4.52.10s
Est. End-to-End Response (500 tokens)TTFT + generation time
GPT-5.2 Chat4.80s
Claude Opus 4.510.16s

Simulador Interativo de Custo de Tokens

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

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
GPT-5.2 Chat Monthly API Bill
$0.00 / month
$0/1M in · $0/1M out
Claude Opus 4.5 Monthly API Bill
$30.75 / month
$5/1M in · $25/1M out
GPT-5.2 Chat saves approximately $30.75 / month (100%) under this workload.1.0x Savings

GPT-5.2 Chat · Strengths & Key Advantages

  • Janela de contexto de 128K com limite máximo de saída de 16K tokens (SWE-bench Verified 75.4% · GPQA Diamond 76.5%)
  • Taxa de transferência rápida de 135 tokens/segundo com latência inicial (TTFT) de 1100 ms
  • Economia de API competitiva (acesso gratuito de pesos abertos) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
  • Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
  • Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Claude Opus 4.5 · Strengths & Key Advantages

  • Janela de contexto de 200K com limite máximo de saída de 64K tokens (SWE-bench Verified 77.2% · GPQA Diamond 74.8%)
  • Taxa de transferência rápida de 62 tokens/segundo com latência inicial (TTFT) de 2100 ms
  • Economia de API competitiva ($5/$25 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas
Considerations & Trade-offs
  • Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
  • Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos

Token Use & Task Economics

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

MetricGPT-5.2 ChatClaude Opus 4.5
Cost per Task
Estimated USD to finish one task
$1.90$5.86
Output Tokens / Task
Tokens generated per task
54K73K
Reasoning Tokens / Task
Thinking tokens burned per task
29K43K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureGPT-5.2 ChatClaude Opus 4.5
Official API Model ID (SDK)gpt-5-2-chatclaude-opus-4-5-20251101
API ProtocolOpenAI Responses API & Chat Completions v1Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2025-122025-11
Knowledge CutoffAugust 2025March 2025
ArchitectureChat-tuned unified reasoning modelHybrid Reasoning
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Free across full context window (only KV-cache VRAM scales)Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLAutomatic prefix KV-caching in vLLM / SGLang (0 cost)$0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI AgentSupported (Screen coordinate grounding, browser & desktop GUI action loops)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function callingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxNative Web Search tool + Hosted Code Interpreter & File Search RAGNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token BillingText 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 VRAMCloud-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 ClassificationOpenAI Preparedness Framework Audited & System Card PublishedAnthropic 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 TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

GPT-5.2 Chat vs Claude Opus 4.5: Respostas Rápidas (FAQ)

Which model is faster?

GPT-5.2 Chat is faster, generating 135 tokens per second compared with 62 tokens per second.

Which model is cheaper to run?

GPT-5.2 Chat is cheaper at $0.00 per 1M tokens blended, compared with $3.85 (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 2.10s.

Which model has a larger context window?

Claude Opus 4.5 has a larger context window, supporting 200K tokens compared with 128K tokens.

Veredito

Tanto GPT-5.2 Chat (Indicado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, arquiteturas RAG corporativas e integração escalável via API.) quanto Claude Opus 4.5 (Indicado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: GPT-5.2 Chat lidera em inteligência geral e programação, GPT-5.2 Chat oferece geração mais rápida e GPT-5.2 Chat apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, GPT-5.2 Chat ou Claude Opus 4.5?+

Nas avaliações de inteligência e código, GPT-5.2 Chat leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, GPT-5.2 Chat ou Claude Opus 4.5?+

O GPT-5.2 Chat custa $0.00 / $0.00 por 1M de tokens (entrada/saída) e o Claude Opus 4.5 custa $5.00 / $25.00. No custo combinado, GPT-5.2 Chat é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O GPT-5.2 Chat suporta 128K tokens de contexto contra 200K tokens do Claude Opus 4.5, enquanto GPT-5.2 Chat entrega maior velocidade de geração.

AI Terminology & Guide
Explore Glossary →

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

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fontes oficiais: Documentação oficial de API da OpenAI e Anthropic e benchmarks independentes (2026).