GPT-5.1 Chat vs GPT-5 Pro
Benchmarks, API Token Pricing, Context Window & Speed Comparison
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GPT-5.1 Chat by OpenAI and GPT-5 Pro by OpenAI 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, GPT-5.1 Chat holds a notable pricing advantage for token ingestion. On output generation, GPT-5.1 Chat is more economical per million generated tokens. In data-heavy architectures requiring extensive repository or document analysis, GPT-5 Pro provides an expanded memory horizon with 400K tokens. In latency-sensitive production environments, GPT-5.1 Chat 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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GPT-5.1 Chat
Conversacional 5.1Un GPT-5.1 optimizado para chat para asistencia refinada, redacción y conversación de productos.
$0.00 / 1M
$0.00 / 1M
128K tokens
74%
GPT-5 Pro
GPT-5 de razonamiento máximoel alto-compute GPT-5 nivel para difficult análisis, code revisión y planning.
$15.00 / 1M
$120.00 / 1M
400K tokens
78.5%
Diferencias Clave de un Vistazo
- GPT-5.1 Chat is 1.0x cheaper for API usage (input + output tokens combined).
- GPT-5 Pro has a larger context window (400K vs 128K tokens).
- GPT-5.1 Chat is faster at 132 tok/s vs 55 tok/s.
- GPT-5 Pro leads on SWE-bench coding (78.5% vs 74.0%).
| Característica | GPT-5.1 Chat | GPT-5 Pro |
|---|---|---|
Intelligence Index Composite reasoning & knowledge score (0-100) | 60 | 62 |
Provider | OpenAI | OpenAI |
Input Price Cost per million input tokens | $0.00 / 1M | $15.00 / 1M |
Output Price Cost per million output tokens | $0.00 / 1M | $120.00 / 1M |
Blended Price Weighted 7:2:1 cache:input:output per 1M | $0.00 / 1M | $16.05 / 1M |
Context Window Maximum input + output tokens | 128K tokens~192 A4 pages of text | 400K tokens~600 A4 pages of text |
Max Output Tokens Per single request | 16K | 272K |
Throughput Speed Tokens generated per second | 132 tok/s | 55 tok/s |
SWE-bench Verified Real-world software engineering | 74% | 78.5% |
GPQA Diamond Graduate-level reasoning | 71.8% | 87.2% |
Cached Input Price Prompt caching discount per 1M tokens | $0.00 / 1M | $1.50 / 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-5.1 Chat · Strengths & Key Advantages
- Calidad conversacional mejorada respecto a GPT-5 Chat
- Bien ajustado para flujos de trabajo de redacción y productos
- Fuerte en la edición multiturno de documentos extensos
Considerations & Trade-offs
- Sin precios de API independientes: solo acceso por suscripción
- Ventana de contexto más pequeña que el nivel de API
GPT-5 Pro · Strengths & Key Advantages
- más alto precisión y profundidad en el GPT-5 family
- muy grande 272K salida económico para largo deliverables
- Excellent para reviewing grande codebases y plans
- muy sólido en largo, interdependent planning problems
Considerations & Trade-offs
- Extremely expensive un $15 / $120 por 1M tokens
- Slow responses — unsuitable para interactivo chat
Token Use & Task Economics
Estimated cost and token consumption to complete one representative agentic task.
| Metric | GPT-5.1 Chat | GPT-5 Pro |
|---|---|---|
Cost per Task Estimated USD to finish one task | $1.48 | $20.40 |
Output Tokens / Task Tokens generated per task | 52K | 72K |
Reasoning Tokens / Task Thinking tokens burned per task | 28K | 48K |
Especificaciones Técnicas
Architecture, release timeline, capabilities, and modalities.
| Característica | GPT-5.1 Chat | GPT-5 Pro |
|---|---|---|
| Official API Model ID (SDK) | gpt-5-1-chat | gpt-5-pro |
| API Protocol | OpenAI Responses API & Chat Completions v1 | OpenAI Responses API & Chat Completions v1 |
| Release Date | 2025-11 | 2025-10 |
| Knowledge Cutoff | October 2024 | September 2024 |
| Architecture | Chat-tuned unified reasoning model | Maximum-compute unified reasoning model |
| Parameters | Confidential | Confidential |
| Enterprise Rate Limits (RPM / TPM) | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM | 10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM |
| Long-Context Tier (>128K/200K) | Free across full context window (only KV-cache VRAM scales) | Flat rate ($15/1M in) across full 400K window |
| Prompt Cache Policy & TTL | Automatic prefix KV-caching in vLLM / SGLang (0 cost) | Automatic prefix caching at $1.5/1M (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 | 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 tool + Hosted Code Interpreter & File Search RAG |
| Official Fine-Tuning Support | Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT) | 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 | OpenAI Preparedness Framework Audited & System Card Published | 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 |
GPT-5.1 Chat vs GPT-5 Pro: Respuestas Rápidas (FAQ)
Which is more intelligent, GPT-5.1 Chat or GPT-5 Pro?
GPT-5 Pro is more intelligent. It scores 62 compared with 60 on the composite Intelligence Index.
Which model is faster?
GPT-5.1 Chat is faster, generating 132 tokens per second compared with 55 tokens per second.
Which model is cheaper to run?
GPT-5.1 Chat is cheaper at $0.00 per 1M tokens blended, compared with $16.05 (7:2:1 cache:input:output ratio).
Which model has lower latency?
GPT-5.1 Chat has lower latency, with a time to first token of 1.18s compared with 4.20s.
Which model has a larger context window?
GPT-5 Pro has a larger context window, supporting 400K tokens compared with 128K tokens.
Veredicto
Verdict & Model Selection Recommendation: Choose GPT-5.1 Chat if your priority is Interactive ChatGPT experiences. Its performance in demanding tasks justifies its operational token cost. Choose GPT-5 Pro if your workflow prioritizes High-value, low-volume analysis and code review. For large-scale batch processing or customer-facing conversational interfaces, its balance of speed and economics delivers superior ROI.
Preguntas frecuentes
How does GPT-5.1 Chat compare to GPT-5 Pro in API token pricing and cost per token?+
GPT-5.1 Chat costs $0.00 per 1M input tokens and $0.00 per 1M output tokens, whereas GPT-5 Pro costs $15.00 input and $120.00 output. Overall, GPT-5.1 Chat 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-5.1 Chat or GPT-5 Pro?+
GPT-5.1 Chat supports a context window of 128K tokens (~96k words), while GPT-5 Pro supports 400K tokens (~300k words). Therefore, GPT-5 Pro can process more textual data and document context in a single prompt.
Which AI model is better for software engineering and coding: GPT-5.1 Chat or GPT-5 Pro?+
GPT-5.1 Chat scores 74% on SWE-bench Verified while GPT-5 Pro scores 78.5%. For autonomous software engineering and multi-file debugging, GPT-5 Pro holds the verified benchmark lead.
What is the difference in reasoning capability and extended thinking between GPT-5.1 Chat and GPT-5 Pro?+
GPT-5.1 Chat features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, GPT-5 Pro provides chain-of-thought reasoning depth for complex math and science.
How does inference speed (tokens per second) compare between GPT-5.1 Chat and GPT-5 Pro?+
GPT-5.1 Chat generates approximately 132 tokens per second, while GPT-5 Pro delivers 55 tokens per second. In latency-sensitive production environments, GPT-5.1 Chat provides faster time-to-first-token (TTFT) and higher streaming response velocity.
Can you implement a tiered LLM routing setup combining GPT-5.1 Chat and GPT-5 Pro to optimize costs?+
Yes! High-efficiency architectures route high-frequency routine classification and conversational tasks to GPT-5.1 Chat to save operational costs, and dynamically escalate complex architectural queries or reasoning tasks to GPT-5 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.
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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