GPT-5.2 Pro vs Claude Opus 4.7
Benchmarks, API Token Pricing, Context Window & Speed Comparison
Related topics (12)
GPT-5.2 Pro by OpenAI and Claude Opus 4.7 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 4.7 holds a notable pricing advantage for token ingestion. On output generation, Claude Opus 4.7 is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, Claude Opus 4.7 provides an expanded memory horizon with 1,000K tokens. In latency-sensitive production environments, Claude Opus 4.7 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.
Cambia y Compara Cualquier Modelo
Select any AI models from our verified benchmark database to generate live side-by-side matrices.
GPT-5.2 Pro
Razonamiento profesionalun alto-precisión GPT-5.2 nivel para difficult razonamiento y revisión flujos de trabajo.
$17.50 / 1M
$140.00 / 1M
400K tokens
79.4%
Claude Opus 4.7
Software avanzadoun enhanced ingeniería de software modelo construido specifically para de misión crítica industrial architectures, formal verificación, y alto-stakes razonamiento.
$5.00 / 1M
$25.00 / 1M
1M tokens
79.5%
Diferencias Clave de un Vistazo
- 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%).
| Característica | 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 |
¿Quién gana en cada área?
At-a-glance decision frameworkPuntuaciones 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.
Latencia y Tiempo de Respuesta
Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.
Simulador Interactivo de Costos de Tokens
Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.
GPT-5.2 Pro · Strengths & Key Advantages
- más alto precisión en el GPT-5.2 family
- sólido en adversarial revisión y perimetral-case análisis
- mejor-en-family en adversarial y perimetral-case revisión
Considerations & Trade-offs
- muy expensive y slow
- Rarely justified outside alto-stakes decisions
Claude Opus 4.7 · Strengths & Key Advantages
- Industry-leading 79.5% SWE-bench Verified rendimiento en early 2026
- Enhanced formal verificación capacidades para de misión crítica aerospace y finance software
- Resilient multiturno error recovery en autónomo codificación agentes
Considerations & Trade-offs
- Premium salida token precios ($25/1M) requiere thoughtful costo gobernanza
- extendido razonamiento overhead during complejo dependency resolución
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 |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | 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: Respuestas Rápidas (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.
Veredicto
Verdict & Model Selection Recommendation: Choose GPT-5.2 Pro if your priority is Critical analysis, security review and high-value decisions. Its performance in demanding tasks justifies its operational token cost. Choose Claude Opus 4.7 if your workflow prioritizes Autonomous software testing suites, cybersecurity code analysis, and complex refactors. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Preguntas frecuentes
How does GPT-5.2 Pro compare to Claude Opus 4.7 in API token pricing and cost per token?+
GPT-5.2 Pro costs $17.50 per 1M input tokens and $140.00 per 1M output tokens, whereas Claude Opus 4.7 costs $5.00 input and $25.00 output. Overall, Claude Opus 4.7 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: GPT-5.2 Pro or Claude Opus 4.7?+
GPT-5.2 Pro supports a context window of 400K tokens (~300k words), while Claude Opus 4.7 supports 1,000K tokens (~750k words). Therefore, Claude Opus 4.7 can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: GPT-5.2 Pro or Claude Opus 4.7?+
GPT-5.2 Pro scores 79.4% on SWE-bench Verified while Claude Opus 4.7 scores 79.5%. For autonomous software engineering and multi-file debugging, Claude Opus 4.7 holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between GPT-5.2 Pro and Claude Opus 4.7?+
GPT-5.2 Pro features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Claude Opus 4.7 provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between GPT-5.2 Pro and Claude Opus 4.7?+
GPT-5.2 Pro generates approximately 50 tokens per second, while Claude Opus 4.7 delivers 58 tokens per second. In latency-sensitive production environments, Claude Opus 4.7 provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining GPT-5.2 Pro and Claude Opus 4.7 to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to Claude Opus 4.7 to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GPT-5.2 Pro. 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.
Related reading
- Claude Opus 4.7 vs Claude Opus 4.6: Benchmarks, Pricing & Speed ComparisonComparar
- Claude Opus 4.8 vs Claude Opus 4.7: Benchmarks, Pricing & Speed ComparisonComparar
- GPT-5.2 Pro vs GPT-5.2: Benchmarks, Pricing & Speed ComparisonComparar
- GPT-5.3 Chat vs GPT-5.2 Pro: Benchmarks, Pricing & Speed ComparisonComparar
- Muse Spark 1.1 vs Claude Opus 4.7: Benchmarks, Pricing & Speed ComparisonComparar
- Aion-3.0 vs Aion-Mini: Benchmarks, Pricing & Speed ComparisonComparar
Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.
Fuentes: GetInfoUs Independent AI Benchmarks & Official API Specs