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OpenAI: GPT-4.1 (batch)

openai/gpt-4.1:batch

Comparer

GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and GPT-4.5 across coding (54.6% SWE-bench Verified), instruction compliance (87.4% IFEval), and multimodal understanding benchmarks. It is tuned for precise code diffs, agent reliability, and high recall in large document contexts, making it ideal for agents, IDE tooling, and enterprise knowledge retrieval.

Modalités
Prix en entrée / sortie
1 $US / 4 $USpar 1M
Contexte
1,0M
Publié
14 avr. 2025
Date limite des connaissances
juin 2024
Comparer
FournisseursTarificationPerformancesDisponibilitéÉvaluations comparativesApplicationsActivitéDocumentationFAQExplorer

Fournisseurs

Différentes entreprises hébergent le même modèle. OpenRouter achemine votre requête vers l’une d’elles selon le mode de routage choisi — Balanced (prix + vitesse), Nitro (le plus rapide) ou Floor (le moins cher).

Tarification

Le prix moyen que les clients paient réellement pour ce modèle, à côté des prix affichés par les fournisseurs. Grâce à la mise en cache et aux remises, le prix réellement payé est souvent bien inférieur au prix affiché.

Performances

Le débit est la vitesse à laquelle le modèle écrit (jetons par seconde — plus il est élevé, mieux c’est). La latence est le temps total d’aller-retour (plus il est faible, mieux c’est). Le TTFT est le délai avant le premier jeton — le temps avant de voir quelque chose apparaître (plus il est faible, mieux c’est).

Disponibilité

La disponibilité correspond au pourcentage des 3 derniers jours pendant lequel au moins un fournisseur répondait aux requêtes. La disponibilité du service correspond au pourcentage de temps pendant lequel l’inférence a été assurée avec succès. OpenRouter surveille en continu les fournisseurs et utilise le meilleur fournisseur suivant lorsque l’un d’eux renvoie une erreur.

Évaluations comparatives

Scores aux évaluations standardisées et réponses de ce modèle aux prompts communs des tests de référence. Des pourcentages plus élevés sont meilleurs — et chaque rang indique la position de ce modèle parmi les modèles évalués sur cette source.

Résumé des scores aux tests de performance pour OpenAI: GPT-4.1 (batch) (Artificial Analysis, Design Arena et Vals AI)
SourceTest de performanceScore
Artificial AnalysisGPT-4.1 GPQA Diamond66.6%
Artificial AnalysisGPT-4.1 HLE4.2%
Artificial AnalysisGPT-4.1 IFBench43.0%
Artificial AnalysisGPT-4.1 τ²-Bench Telecom47.1%
Artificial AnalysisGPT-4.1 AA-LCR68.3%
Artificial AnalysisGPT-4.1 CritPt0.0%
Artificial AnalysisGPT-4.1 LiveCodeBench45.7%
Artificial AnalysisGPT-4.1 Terminal-Bench Hard13.6%
Artificial AnalysisGPT-4.1 MMLU-Pro80.6%
Artificial AnalysisGPT-4.1 AIME 202534.7%
Artificial AnalysisGPT-4.1 AIME43.7%
Artificial AnalysisGPT-4.1 MATH-50091.3%
Design ArenaGPT-4.1 Models Arena 3D Elo847
Design ArenaGPT-4.1 Models Arena Code Categories Elo1024
Design ArenaGPT-4.1 Models Arena Data Visualization Elo1104
Design ArenaGPT-4.1 Models Arena Game Development Elo1078
Design ArenaGPT-4.1 Models Arena UI Component Elo995
Design ArenaGPT-4.1 Models Arena Website Elo1037
Vals AIGPT 4.1 AIME39.6%
Vals AIGPT 4.1 CaseLaw v269.9%
Vals AIGPT 4.1 CorpFin v263.1%
Vals AIGPT 4.1 Finance Agent v124.6%
Vals AIGPT 4.1 GPQA Diamond65.4%
Vals AIGPT 4.1 LiveCodeBench54.7%
Vals AIGPT 4.1 LegalBench83.1%
Vals AIGPT 4.1 MATH 50087.2%
Vals AIGPT 4.1 MedQA91.2%
Vals AIGPT 4.1 MGSM87.7%
Vals AIGPT 4.1 MMLU Pro80.5%
Vals AIGPT 4.1 MMMU Pro72.4%
Vals AIGPT 4.1 MortgageTax65.9%
Vals AIGPT 4.1 TaxEval v275.1%
Vals AIGPT 4.1 Terminal-Bench 2.014.6%

Applications

Applications publiques qui envoient le plus de trafic à ce modèle. Un bon indicateur des charges de travail réelles en production — et un aperçu des cas d’usage auxquels ce modèle convient le mieux.

Activité

Volume de jetons et trafic des requêtes vers ce modèle au fil du temps.

API

Code prêt à l’emploi pour appeler ce modèle. L’API d’OpenRouter est compatible avec OpenAI — la plupart des SDK fonctionnent en remplaçant simplement l’URL de base. Seul le slug du modèle ci-dessous change d’un modèle à l’autre.

Actuellement indisponible via le routage dans la région UE. Documentation sur le routage intrarégional

Documentation

Guides, recueils de recettes, articles de blog et outils pour développer avec OpenAI: GPT-4.1 (batch) sur OpenRouter.

  • Quasar Alpha and Optimus Alpha RevealArticle de blog

Explorer d’autres modèles

Modèles d’IA avec vision : LLM multimodaux pour la compréhension d’imagesCollectionClassements des modèles d’IAClassement
1,00 $US4,00 $US0,25 $US----
--
Évaluations comparatives AutoExacto
GPQA DiamondTAU-BenchOpenAI64,8 %48,7 %

Les données de disponibilité sont encore insuffisantes pour être affichées.

Lorsqu’une erreur survient chez un fournisseur en amont, nous pouvons rétablir le service en routant la requête vers un autre fournisseur opérationnel, si les filtres de votre requête le permettent. Vous pouvez accéder par programmation aux données de disponibilité de chaque fournisseur via l’ API des points de terminaison. Découvrez nos options d’ équilibrage de charge et de routage des fournisseurs.

Pas encore assez de données sur les applications utilisant ce modèle.

Questions fréquentes

GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and GPT-4.5 across coding (54.6% SWE-bench Verified), instruction compliance (87.4% IFEval), and multimodal understanding benchmarks.

La documentation de GPT-4.1 (batch) sur OpenRouter comprend l’article de blog Quasar Alpha and Optimus Alpha Reveal. Le guide de démarrage rapide présente les clés API et votre première requête, et la référence API répertorie tous les paramètres.

GPT-4.1 (batch) coûte 1,00 $US/M de jetons d’entrée et 4,00 $US/M de jetons de sortie, avec des tarifs distincts pour Cache Read à 0,25 $US/M tokens et Web Search à 10,00 $US/1K calls.

GPT-4.1 (batch) dispose d’une fenêtre de contexte de 1 047 576 jetons. Il prend en charge jusqu’à 32 768 jetons de complétion.

Oui. GPT-4.1 (batch) accepte tools et tool_choice pour l’appel de fonctions. Il prend également en charge les sorties structurées via un schéma JSON dans response_format.

GPT-4.1 (batch) accepte images, texte et fichiers tels que des PDF en entrée et renvoie texte.

GPT-6.1 Terra Pro, GPT-6.1 Terra, GPT-6 Luna Decisions et 58 de plus sont d’autres modèles de type texte de OpenAI.

GPT-4.1 (batch) est sorti le 14 avril 2025. Ses connaissances s’arrêtent au 30 juin 2024.

Autres modèles de OpenAI

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Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6.1 Terra and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6.1 Terra instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6.1 Terra and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6.1 Terra instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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It is built for classification, routing, moderation, and rubric grading where application code thresholds the returned numbers rather than parsing a chat reply. A request can carry up to 200 questions about the same content.

Décisions0,10 $US / 0 $US
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