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OpenAI: o3 (batch)

openai/o3:batch

Comparer

o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following. Use it to think through multi-step problems that involve analysis across text, code, and images.

Modalités
Prix en entrée / sortie
1 $US / 4 $USpar 1M
Contexte
200K
Publié
16 avr. 2025
Date limite des connaissances
juin 2024
Comparer
FournisseursTarificationPerformancesDisponibilitéÉvaluations comparativesApplicationsActivitéFAQExplorer

Fournisseurs

Ce modèle est hébergé par un seul fournisseur. OpenRouter lui transmet directement chaque requête — aucune décision de routage à prendre.

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: o3 (batch) (Artificial Analysis, Design Arena et Vals AI)
SourceTest de performanceScore
Artificial Analysiso3 GPQA Diamond82.7%
Artificial Analysiso3 HLE20.1%
Artificial Analysiso3 IFBench71.4%
Artificial Analysiso3 τ²-Bench Telecom80.7%
Artificial Analysiso3 AA-LCR74.7%
Artificial Analysiso3 CritPt1.1%
Artificial Analysiso3 LiveCodeBench80.8%
Artificial Analysiso3 Terminal-Bench Hard37.1%
Artificial Analysiso3 MMLU-Pro85.3%
Artificial Analysiso3 AIME 202588.3%
Artificial Analysiso3 AIME90.3%
Artificial Analysiso3 MATH-50099.2%
Design Arenao3 Models Arena Code Categories Elo1018
Design Arenao3 Models Arena Data Visualization Elo1200
Design Arenao3 Models Arena Game Development Elo1034
Design Arenao3 Models Arena UI Component Elo1011
Design Arenao3 Models Arena Website Elo1036
Vals AIo3 AIME85.3%
Vals AIo3 CorpFin v259.7%
Vals AIo3 Finance Agent v147.7%
Vals AIo3 GPQA Diamond84.1%
Vals AIo3 LiveCodeBench83.9%
Vals AIo3 LegalBench83.8%
Vals AIo3 MATH 50094.6%
Vals AIo3 MedCode47.3%
Vals AIo3 MedQA96.1%
Vals AIo3 MedScribe76.7%
Vals AIo3 MGSM91.7%
Vals AIo3 MMLU Pro85.6%
Vals AIo3 MMMU Pro80.4%
Vals AIo3 MortgageTax65.7%
Vals AIo3 SAGE v141.8%
Vals AIo3 TaxEval v274.6%

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

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----
--

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

o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following. Use it to think through multi-step problems that involve analysis across text, code, and images.

o3 (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.

o3 (batch) dispose d’une fenêtre de contexte de 200 000 jetons. Il prend en charge jusqu’à 100 000 jetons de complétion.

Oui. o3 (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.

o3 (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.

o3 (batch) est sorti le 16 avril 2025. Ses connaissances s’arrêtent au 30 juin 2024.

Autres modèles de OpenAI

GPT-6.1 Terra Pro

GPT-6.1 Terra Pro is the same underlying model as GPT-6.1 Terra, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

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

TexteContexte de 1,1M1 $US / 5 $US
GPT-6.1 Terra Pro (batch)

GPT-6.1 Terra Pro is the same underlying model as GPT-6.1 Terra, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

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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GPT-6.1 Terra

GPT-6.1 Terra is the mid-tier model in OpenAI's GPT-6.1 series, priced below GPT-6.1 Sol. It is suited for everyday agentic, coding, and writing work, is particularly strong at understanding screenshots and on-screen content, and is efficient enough for high-volume workloads.

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GPT-6.1 Terra (batch)

GPT-6.1 Terra is the mid-tier model in OpenAI's GPT-6.1 series, priced below GPT-6.1 Sol. It is suited for everyday agentic, coding, and writing work, is particularly strong at understanding screenshots and on-screen content, and is efficient enough for high-volume workloads.

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GPT-6 Luna Decisions

GPT-6 Luna Decisions is GPT-6 Luna served through OpenAI's Decisions API. Instead of generating text, it reads the content passed as state (text, JSON, or images) and returns typed, probabilistic answers to named questions in a single request: the probability of yes for a yes/no question (noul), a probability for every option plus the most likely one (choice), or a probability for every level of an ordered rubric plus the expected score (score).

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
GPT-6.1 Sol Pro

GPT-6.1 Sol Pro is the same underlying model as GPT-6.1 Sol, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

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 Sol 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 Sol 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 Sol 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 Sol instead.

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

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GPT-6 Luna Pro

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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 Luna 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 Luna instead.

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

TexteContexte de 1,1M0,10 $US / 0,50 $US
GPT-6 Luna Pro (batch)

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

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