El carril de GPT-4.1 más pequeño y económico, orientado a clasificación, etiquetado y enrutamiento.
Technical Specifications
- Provider
- OpenAI
- Category
- lightweight
- Release Date
- 2025-04
- Batch API Discount
- 50% off async batch
- Consumer Subscription
- $20 / month
- Reasoning Effort Control
- Fixed
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- gpt-4-1-nano
- Supported SDK & API Protocol
- OpenAI Responses API & Chat Completions v1
- Lifecycle & Deprecation Status
- Active GA (Guaranteed support through 2027+)
- Production Rate Limits (RPM & TPM)
- 10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
- Long-Context Pricing Tier (>128K / >200K)
- Flat rate ($0.1/1M in) across full 1048K window
- Prompt Cache Write & TTL Policy
- Automatic prefix caching at $0.025/1M (no extra cache-write fee)
- Computer Use & Browser GUI Agent
- 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
- Web Search Grounding & Code Sandbox
- Native Web Search tool + Hosted Code Interpreter & File Search RAG
- Fine-Tuning & Distillation Support
- Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
- Weights Precision & Quantization
- Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster)
- Minimum GPU VRAM Requirement
- Zero Local VRAM Required (100% Serverless Cloud API)
- Supported Inference Engines
- Managed OpenAI Cloud API
- System Card & Safety Framework
- OpenAI Preparedness Framework Audited & System Card Published
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
GPT-4.1 nano Cost, Context, Hardware & API Integration
Pay-as-you-go API is cheaper for this volume (saves $10.25/mo vs $20 flat plan).
Break-even point: ~1,026 requests/day equals $20/month.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to GPT-4.1 nano:
Benchmark Scores & 6-Axis Capability Radar
- SWE-bench Verified
- 24%
- GPQA Diamond
- 38%
- MMLU-Pro
- 55.5%
- HumanEval
- 78%
- Humanity's Last Exam
- 4.4%
- Terminal-Bench
- 12.5%
- SciCode
- 15%
- LiveCodeBench
- 25.5%
- AIME
- 30.5%
- Long-Context Reasoning
- 48%
- Chatbot Arena Elo
- 1195pts
Strengths
- Extremadamente económico a $0.10 / $0.40 por millón de tokens
- Muy rápido, ideal para enrutamiento sensible a la latencia
- Mantiene la ventana de contexto de 1 millón de tokens
- Suficientemente bueno para barreras de seguridad y prefiltrado
Limitations & Trade-offs
- La variante de GPT-4.1 más débil por amplio margen
- No apto para razonamiento abierto o redacción extensa
Editorial Assessment
El mejor precio por token para tareas sencillas de gran volumen.
Best for: Clasificación masiva, etiquetado, barreras de seguridad y enrutamiento económico de agentes
Compare GPT-4.1 nano
Frequently Asked Questions about GPT-4.1 nano
How much does the GPT-4.1 nano API cost per 1M tokens?+
GPT-4.1 nano by OpenAI is priced at $0.1 per 1M input tokens and $0.4 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.025 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.
Should I use a $20/month subscription or the GPT-4.1 nano pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in GPT-4.1 nano's context window?+
GPT-4.1 nano features a 1.0M tokens context window, which equals approximately 785,682 English words or ~2,095 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 32,768 tokens.
Can I run GPT-4.1 nano locally on my own GPU (Open Weights)?+
No, GPT-4.1 nano is a proprietary closed-weights model hosted by OpenAI. It cannot be downloaded for local GPU execution and must be accessed via OpenAI's official API or cloud platform.
Does OpenAI train on data sent to the GPT-4.1 nano API, and is commercial use allowed?+
API payloads are excluded from model training by default. License tier: Proprietary Commercial API (OpenAI Terms). Full commercial ownership of generated outputs. Supported deployment channels include: OpenAI Platform API, Microsoft Azure OpenAI Foundry.
How does GPT-4.1 nano perform on coding and reasoning benchmarks?+
GPT-4.1 nano achieves a composite Intelligence Index of 26/100, scoring 24% on SWE-bench Verified, 38% on GPQA Diamond, 55.5% on MMLU-Pro, and 1195 pts on Chatbot Arena Elo.
What is GPT-4.1 nano best used for?+
GPT-4.1 nano is best suited for: Clasificación masiva, etiquetado, barreras de seguridad y enrutamiento económico de agentes. Assessment: El mejor precio por token para tareas sencillas de gran volumen.
OpenAI Family Lineage, Routing Tiers & Upgrade Path
Step down to a lighter sibling for high-volume routing or step up to OpenAI's flagship reasoning tier:
GPT-6 Astra
GPT-6.1 Sol
GPT-6 Sol
GPT-6 Luna
GPT-5.6 Sol
GPT-5.6 Terra
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to GPT-4.1 nano:
La unidad básica de texto que procesa un modelo de lenguaje, que normalmente equivale a 3 o 4 caracteres o aproximadamente 0,75 palabras. Por ejemplo, una frase típica se divide en varios tokens.
Un conjunto estandarizado de pruebas para evaluar y comparar objetivamente las capacidades de distintos modelos de IA en tareas como programación (SWE-bench) o matemáticas avanzadas (AIME).
La cantidad máxima de tokens que un modelo puede considerar a la vez, incluyendo tanto la entrada que lee como la salida que genera. Una ventana de 1.000.000 de tokens puede procesar unas 750.000 palabras en una sola petición.
La capacidad de un modelo de detectar la necesidad de una función externa y emitir argumentos JSON estructurados para ejecutar API, búsquedas web o consultas a bases de datos.
Un protocolo abierto desarrollado por Anthropic que permite a los agentes de IA conectarse de forma estandarizada a sistemas de archivos locales, entornos de desarrollo y servicios externos.
Una optimización donde los proveedores almacenan estados de atención previos para prefijos de prompts frecuentes, reduciendo el coste de entrada hasta en un 90% y acelerando la respuesta.
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: OpenAI official pricing & model documentation (verified October 2026)↗