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OpenAI

GPT-4.1 nano

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
Le 4.1 le plus économiqueOfficial Source Verified ↗
26
Intelligence Index

La voie GPT-4.1 la plus petite et la plus abordable, conçue pour la classification, le balisage et le routage.

Input / Output
$0.1 / $0.4
per 1M tokens
Context
1.0M tokens
window
Speed
220
tok/s
Latency
0.22s
TTFT

Technical Specifications

Provider
OpenAI
Category
lightweight
Release Date
2025-04
Knowledge Cutoff
June 2024
Architecture
Dense multimodal transformer (nano)
Parameters
Confidential
Context Window
1.0M tokens
Max Output
33K tokens
Cached Input Price
$0.025 / 1M tokens
Batch API Discount
50% off async batch
Consumer Subscription
$20 / month
Reasoning Mode
No (Standard)
Reasoning Effort Control
Fixed
Tool Calling
Yes
Structured Outputs
Yes
Open Weights
No (Proprietary Cloud)
Input Modalities
text, vision
Output Modalities
text
Official Documentation
Visit Official Docs ↗

Data Privacy, Licensing & Deployment Governance

API Data Training Policy
API payloads are excluded from model training by default
Model License & Commercial Rights
Proprietary Commercial API (OpenAI Terms)
Deployment & Cloud Availability
OpenAI Platform API, Microsoft Azure OpenAI Foundry
Output Ownership
Full commercial ownership of generated outputs

Official Provider Release Intelligence, API Quotas & Agentic Specs

Compare Multi-Models Side-by-Side →
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
Engineering & Pricing Workbench

GPT-4.1 nano Cost, Context, Hardware & API Integration

500 / day
4,000 tok
1,000 tok
Conversation Depth (History Re-billing):1 Turn (Single-Shot)
50%
Estimated Monthly API Cost (30 Days)
$9.75$12.00
Monthly Savings: $2.25 (Caching/Batch)
Daily Cost:
$0.33
Cost per Request:
$0.00065
Effective Input / 1M:
$0.063
Effective Output / 1M:
$0.400
Subscription ($20/mo) vs API

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

GPT-4.1 nano (Active)
$9.75
/ month
Gemini 2.5 Flash
$18.00
/ month
DeepSeek V3
$32.70
/ month
GPT-4o
$300.00
/ month
Claude 3.7 Sonnet
$405.00
/ month

Live Prompt Paste Tokenizer & Cost Counter

Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.

Chars / Words
175 / 24
OpenAI o200k
~46 tok
Claude BPE
~49 tok
Llama / DeepSeek
~51 tok

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:

Cascaded Monthly Bill:$15.94/mo
This model is already priced at or below the fast router baseline.

Benchmark Scores & 6-Axis Capability Radar

Benchmark Encyclopedia
Coding (35)Reasoning (44)Knowledge (56)Speed (100)Context (100)Cost Value (94)
GPT-4.1 nano2026 Frontier Median
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

  • Extrêmement abordable à 0,10 $ / 0,40 $ par million de tokens
  • Très rapide, idéal pour le routage sensible à la latence
  • Conserve la fenêtre de contexte d'un million de tokens
  • Suffisamment performant pour les garde-fous et le préfiltrage de sécurité

Limitations & Trade-offs

  • La variante GPT-4.1 la plus faible par une large marge
  • Non adapté au raisonnement ouvert ou à la rédaction longue

Editorial Assessment

Meilleur prix par token pour les tâches simples à fort volume.

Best for: Classification en masse, balisage, garde-fous et routage économique d'agents

Compare GPT-4.1 nano

GPT-4.1 nano vs GPT-4o miniGPT-4.1 nano vs Amazon Nova MicroGPT-4.1 nano vs Gemini 4 ArgonGPT-4.1 nano vs Claude Opus 5.5GPT-4.1 nano vs Llama 5GPT-4.1 nano vs Kimi K3

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: Classification en masse, balisage, garde-fous et routage économique d'agents. Assessment: Meilleur prix par token pour les tâches simples à fort volume.

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:

Higher-Intelligence Upgrade2026-09

GPT-6 Astra

$10 / $50 · 272K tokensIQ 96
Higher-Intelligence Upgrade2026-09

GPT-6.1 Sol

$2 / $10 · 1M tokensIQ 94
Higher-Intelligence Upgrade2026-09

GPT-6 Sol

$2 / $10 · 1M tokensIQ 93
Higher-Intelligence Upgrade2026-09

GPT-6 Luna

$0.1 / $0.5 · 272K tokensIQ 67
Higher-Intelligence Upgrade2026-07

GPT-5.6 Sol

$4 / $20 · 1.1M tokensIQ 89
Higher-Intelligence Upgrade2026-07

GPT-5.6 Terra

$2 / $10 · 1.1M tokensIQ 85

AI Glossary & Architecture Concepts

View full glossary →

Key machine learning concepts and benchmarks relevant to GPT-4.1 nano:

Jeton (Token)

L'unité textuelle de base traitée par un modèle linguistique, représentant généralement 3 à 4 caractères ou environ 0,75 mot. Par exemple, une phrase courante est découpée en plusieurs jetons.

Benchmark (Banc d’essai)

Une suite de tests standardisés permettant d'évaluer et de comparer objectivement les performances des modèles d'IA sur des tâches ciblées (code avec SWE-bench, mathématiques avec AIME, etc.).

Fenêtre de contexte

Le nombre maximal de jetons qu'un modèle peut traiter simultanément (entrée et sortie comprises). Une fenêtre de 1 000 000 jetons permet d'analyser environ 750 000 mots en une seule requête.

Appel d'outils (Tool Calling)

La capacité d'un LLM à déterminer quand une action externe est requise et à générer des arguments structurés pour invoquer des API, calculatrices ou bases de données avant de poursuivre.

Protocole de contexte de modèle (MCP)

Un standard ouvert créé par Anthropic permettant aux agents d'IA de se connecter de façon uniforme aux systèmes de fichiers locaux, aux environnements de développement et aux API tierces.

Entrée en cache (Cached Input)

Une optimisation tarifaire et technique conservant les états d'attention des préfixes de prompts récurrents, réduisant les coûts d'entrée de 50 à 90 % tout en abaissant la latence.

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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: OpenAI official pricing & model documentation (verified October 2026)↗