Claude Opus 4.8 vs GPT-5.5 Instant
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Claude Opus 4.8 da Anthropic e GPT-5.5 Instant da OpenAI são dois modelos de IA de destaque. O Claude Opus 4.8 oferece uma janela de contexto de 1M tokens a $5.00/$25.00 por milhão de tokens, enquanto o GPT-5.5 Instant oferece 400K tokens de contexto a $0.75/$6.00 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.
Troque e Compare Qualquer Modelo
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Claude Opus 4.8
Modelo Principal de FronteiraO Claude Opus 4.8 da Anthropic é um modelo de IA projetado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, oferecendo janela de contexto de 1M, velocidade de 64 tokens/s, índice de inteligência de 67/100
$5.00 / 1M
$25.00 / 1M
1M tokens
80.8%
GPT-5.5 Instant
Modelo Leve e EconômicoO GPT-5.5 Instant da OpenAI é um modelo de IA projetado para máxima economia por token e alto desempenho em escala de produção, oferecendo janela de contexto de 400K, velocidade de 168 tokens/s, índice de inteligência de 65/100 e tarifa de
$0.75 / 1M
$6.00 / 1M
400K tokens
74.5%
Principais Diferenças em Resumo
- GPT-5.5 Instant is 4.6x cheaper for API usage (input + output tokens combined).
- Claude Opus 4.8 has a larger context window (1M vs 400K tokens).
- GPT-5.5 Instant is faster at 168 tok/s vs 64 tok/s.
- Claude Opus 4.8 leads on SWE-bench coding (80.8% vs 74.5%).
| Feature | Claude Opus 4.8 | GPT-5.5 Instant |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 67 | 65 |
Provider | Anthropic | OpenAI |
Input Price Cost per million input tokens | $5.00 / 1M | $0.75 / 1M |
Output Price Cost per million output tokens | $25.00 / 1M | $6.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $3.85 / 1M | $0.80 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 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 | 64 tok/s | 168 tok/s |
SWE-bench Verified Real-world software engineering | 80.8% | 74.5% |
GPQA Diamond Graduate-level reasoning | 78.9% | 75% |
Cached Input Price Prompt caching discount per 1M tokens | $0.50 / 1M | $0.07 / 1M |
Quem vence em cada categoria?
At-a-glance decision frameworkPontuações de Benchmarks Verificadas
Official evaluation metrics verified by independent third-party research labs.
Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.
Challenging questions created by domain experts to test complex PhD-level reasoning.
Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.
Crowdsourced human preference evaluation based on blind, head-to-head model battles.
Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.
Autonomous multi-step tasks executed inside a real command-line terminal environment.
Research-grade coding problems drawn from real scientific and numerical workloads.
Contamination-free competitive programming problems collected continuously over time.
American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.
Accuracy when reasoning over very large inputs that fill the model context window.
Tokens emitted per second during active generation streaming.
Latência e Tempo de Resposta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interativo de Custo de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
Claude Opus 4.8 · Strengths & Key Advantages
- Janela de contexto de 1M com limite máximo de saída de 128K tokens (SWE-bench Verified 80.8% · GPQA Diamond 78.9%)
- Taxa de transferência rápida de 64 tokens/segundo com latência inicial (TTFT) de 1650 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
GPT-5.5 Instant · Strengths & Key Advantages
- Janela de contexto de 400K com limite máximo de saída de 128K tokens (SWE-bench Verified 74.5% · GPQA Diamond 75%)
- Taxa de transferência rápida de 168 tokens/segundo com latência inicial (TTFT) de 780 ms
- Economia de API competitiva ($0.75/$6 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
- Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude Opus 4.8 | GPT-5.5 Instant |
|---|---|---|
Cost per Task Estimated USD to finish one task | $5.49 | $0.95 |
Output Tokens / Task Tokens generated per task | 72K | 52K |
Reasoning Tokens / Task Thinking tokens burned per task | 37K | 26K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude Opus 4.8 | GPT-5.5 Instant |
|---|---|---|
| Official API Model ID (SDK) | claude-opus-4-8-20260501 | gpt-5-5-instant |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2026-05 | 2026-05 |
| Knowledge Cutoff | March 2026 | December 2025 |
| Architecture | Frontier Hybrid Cognitive Architecture | Low-latency compact reasoning model |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 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) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Flat rate ($0.75/1M in) across full 400K window |
| Prompt Cache Policy & TTL | $0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL | Automatic prefix caching at $0.075/1M (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 Citations + Code Execution Tool + MCP Connectors | Native Web Search tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt Distillation | 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 | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated | 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 |
Claude Opus 4.8 vs GPT-5.5 Instant: Respostas Rápidas (FAQ)
Which is more intelligent, Claude Opus 4.8 or GPT-5.5 Instant?
Claude Opus 4.8 is more intelligent. It scores 67 compared with 65 on the composite Intelligence Index.
Which model is faster?
GPT-5.5 Instant is faster, generating 168 tokens per second compared with 64 tokens per second.
Which model is cheaper to run?
GPT-5.5 Instant is cheaper at $0.80 per 1M tokens blended, compared with $3.85 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-5.5 Instant has lower latency, with a time to first token of 0.78s compared with 1.65s.
Which model has a larger context window?
Claude Opus 4.8 has a larger context window, supporting 1M tokens compared with 400K tokens.
Veredito
Tanto Claude Opus 4.8 (Indicado para raciocínio corporativo de fronteira, programação avançada e cargas de produção, arquiteturas RAG corporativas e integração escalável via API.) quanto GPT-5.5 Instant (Indicado para máxima economia por token e alto desempenho em escala de produção, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Claude Opus 4.8 lidera em inteligência geral e programação, GPT-5.5 Instant oferece geração mais rápida e GPT-5.5 Instant apresenta o melhor custo-benefício em produção.
Perguntas Frequentes (FAQ)
Qual é melhor para programação e raciocínio, Claude Opus 4.8 ou GPT-5.5 Instant?+
Nas avaliações de inteligência e código, Claude Opus 4.8 leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.
Qual modelo tem a API mais barata, Claude Opus 4.8 ou GPT-5.5 Instant?+
O Claude Opus 4.8 custa $5.00 / $25.00 por 1M de tokens (entrada/saída) e o GPT-5.5 Instant custa $0.75 / $6.00. No custo combinado, GPT-5.5 Instant é mais econômico.
Qual modelo possui maior janela de contexto e velocidade?+
O Claude Opus 4.8 suporta 1M tokens de contexto contra 400K tokens do GPT-5.5 Instant, enquanto GPT-5.5 Instant entrega maior velocidade de geração.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
Related reading
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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 Anthropic e OpenAI e benchmarks independentes (2026).