Claude Opus 5 vs Claude Opus 5.5
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
Claude Opus 5 by Anthropic and Claude Opus 5.5 by Anthropic represent two of the frontier AI models analyzed in our comprehensive 2026 AI benchmark and LLM comparison. In this head-to-head evaluation, we examine API token pricing, context window specifications, inference speed (tokens per second), and empirical reasoning performance. From a pure economic perspective, Claude Opus 5.5 holds a notable pricing advantage for token ingestion. On output generation, Claude Opus 5.5 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, both models provide an identical memory horizon with 1,000K tokens. In latency-sensitive production environments, Claude Opus 5.5 leads in tokens-per-second throughput, making it ideal for real-time conversational agents and high-concurrency workflows. Below is the complete empirical head-to-head breakdown across cost, speed, context, and capability matrices.
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Claude Opus 5
Modelo de Raciocínio ProfundoO Claude Opus 5 da Anthropic é um modelo de inteligência artificial com janela de contexto de 1M tokens e preço de API de $5/1M na entrada e $25/1M na saída, projetado para programação, raciocínio e automação empresarial.
$5.00 / 1M
$25.00 / 1M
1M tokens
83.1%
Claude Opus 5.5
Modelo de Raciocínio ProfundoO Claude Opus 5.5 da Anthropic é um modelo de inteligência artificial com janela de contexto de 1M tokens e preço de API de $4.0/1M na entrada e $20.0/1M na saída, projetado para programação, raciocínio e automação empresarial.
$4.00 / 1M
$20.00 / 1M
1M tokens
84.6%
Principais Diferenças em Resumo
- Claude Opus 5.5 is 1.3x cheaper for API usage (input + output tokens combined).
- Claude Opus 5.5 is faster at 78 tok/s vs 68 tok/s.
- Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 83.1%).
| Feature | Claude Opus 5 | Claude Opus 5.5 |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 75 | 94 |
Provider | Anthropic | Anthropic |
Input Price Cost per million input tokens | $5.00 / 1M | $4.00 / 1M |
Output Price Cost per million output tokens | $25.00 / 1M | $20.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $3.85 / 1M | $3.08 / 1M |
Context Window Maximum input + output tokens | 1M tokens~1,500 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 | 68 tok/s | 78 tok/s |
SWE-bench Verified Real-world software engineering | 83.1% | 84.6% |
GPQA Diamond Graduate-level reasoning | 80.5% | 82.3% |
Cached Input Price Prompt caching discount per 1M tokens | $0.50 / 1M | $0.40 / 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 5 · Strengths & Key Advantages
- Arquitetura Thinking-First Autonomous Foundation Architecture avançada da Anthropic com contexto de 1M tokens
- Excelente relação custo-benefício ($5/1M entrada, $25/1M saída) e baixa latência
- Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
- Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
- Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos
Claude Opus 5.5 · Strengths & Key Advantages
- Arquitetura Extended Autonomous Hybrid Reasoning Transformer avançada da Anthropic com contexto de 1M tokens
- Excelente relação custo-benefício ($4.0/1M entrada, $20.0/1M saída) e baixa latência
- Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
- Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
- Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | Claude Opus 5 | Claude Opus 5.5 |
|---|---|---|
Cost per Task Estimated USD to finish one task | $5.49 | $3.85 |
Output Tokens / Task Tokens generated per task | 72K | 68K |
Reasoning Tokens / Task Thinking tokens burned per task | 37K | 42K |
Especificações Técnicas
Architecture, release timeline, capabilities, and modalities.
| Feature | Claude Opus 5 | Claude Opus 5.5 |
|---|---|---|
| Official API Model ID (SDK) | claude-opus-5-20260701 | claude-opus-5-5-20260901 |
| API Protocol | Anthropic Messages API + AWS Bedrock + Vertex AI | Anthropic Messages API + AWS Bedrock + Vertex AI |
| Release Date | 2026-07 | 2026-09 |
| Knowledge Cutoff | March 2026 | June 2026 |
| Architecture | Thinking-First Autonomous Foundation Architecture | Extended Autonomous Hybrid Reasoning Transformer |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM | 4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM |
| Long-Context Tier (>128K/200K) | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens | Standard rate up to 200K tokens; 2x input/output tier above 200K tokens |
| Prompt Cache Policy & TTL | $0.5/1M cached read (90% off); 5-min default & 1-hour extended TTL | $0.4/1M 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 Citations + Code Execution Tool + MCP Connectors | Native Web Search Citations + Code Execution Tool + MCP Connectors |
| Official Fine-Tuning Support | Custom Model Tuning via Amazon Bedrock & Prompt Distillation | 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 | Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated | 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 |
Claude Opus 5 vs Claude Opus 5.5: Respostas Rápidas (FAQ)
Which is more intelligent, Claude Opus 5 or Claude Opus 5.5?
Claude Opus 5.5 is more intelligent. It scores 94 compared with 75 on the composite Intelligence Index.
Which model is faster?
Claude Opus 5.5 is faster, generating 78 tokens per second compared with 68 tokens per second.
Which model is cheaper to run?
Claude Opus 5.5 is cheaper at $3.08 per 1M tokens blended, compared with $3.85 (7:2:1 cache:input:output ratio).
Which model has lower latency?
Claude Opus 5.5 has lower latency, with a time to first token of 1.40s compared with 1.50s.
Veredito
Verdict & Model Selection Recommendation: Choose Claude Opus 5 if your priority is Complex software refactoring swarms, mission-critical scientific synthesis, and enterprise agent deployments. Its performance in demanding tasks justifies its operational token cost. Choose Claude Opus 5.5 if your workflow prioritizes Large-scale software development agents, enterprise codebases, and mission-critical scientific synthesis. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Perguntas Frequentes (FAQ)
How does Claude Opus 5 compare to Claude Opus 5.5 in API token pricing and cost per token?+
Claude Opus 5 costs $5.00 per 1M input tokens and $25.00 per 1M output tokens, whereas Claude Opus 5.5 costs $4.00 input and $20.00 output. Overall, Claude Opus 5.5 is the more cost-effective model for high-volume API pipelines. Both models support prompt caching discounts of up to 90% for repeated prompt prefixes.
Which model has a larger context window: Claude Opus 5 or Claude Opus 5.5?+
Both Claude Opus 5 and Claude Opus 5.5 offer an identical context window of 1,000K tokens (~750k words). Both architectures provide equal capacity for large document ingestion, multi-file codebases, and extended multi-turn conversation histories.
Which AI model is better for software engineering and coding: Claude Opus 5 or Claude Opus 5.5?+
Claude Opus 5 scores 83.1% on SWE-bench Verified while Claude Opus 5.5 scores 84.6%. For autonomous software engineering and multi-file debugging, Claude Opus 5.5 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between Claude Opus 5 and Claude Opus 5.5?+
Claude Opus 5 features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Opus 5.5 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between Claude Opus 5 and Claude Opus 5.5?+
Claude Opus 5 generates approximately 68 tokens per second, while Claude Opus 5.5 delivers 78 tokens per second. In latency-sensitive production environments, Claude Opus 5.5 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining Claude Opus 5 and Claude Opus 5.5 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Claude Opus 5.5 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to Claude Opus 5. This tiered routing pattern cuts overall API bills by up to 70%.
Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.
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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: GetInfoUs Independent AI Benchmarks & Official API Specs