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Favicon für openai

OpenAI: GPT-4o-mini (batch)

openai/gpt-4o-mini:batch

Vergleich

GPT-4o mini is OpenAI's newest model after GPT-4 Omni, supporting both text and image inputs with text outputs.

As their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than GPT-3.5 Turbo. It maintains SOTA intelligence, while being significantly more cost-effective.

GPT-4o mini achieves an 82% score on MMLU and presently ranks higher than GPT-4 on chat preferences common leaderboardsOpens in new tab.

Check out the launch announcementOpens in new tab to learn more.

#multimodal

Modalitäten
Eingabe- / Ausgabepreis
0,075 $ / 0,30 $pro 1 Mio.
Kontext
128K
Veröffentlicht
18. Juli 2024
Wissensstand
Okt. 2023
Vergleich
AnbieterPreiseLeistungVerfügbarkeitLeistungsvergleicheAppsAktivitätFAQEntdecken

Anbieter

Verschiedene Unternehmen hosten dasselbe Modell. OpenRouter leitet Ihre Anfrage je nach gewähltem Routing-Modus an eines davon weiter — Balanced (Preis + Geschwindigkeit), Nitro (am schnellsten) oder Floor (am günstigsten).

Preise

Der durchschnittliche Preis, den Kunden tatsächlich für dieses Modell zahlen, neben den von Anbietern veröffentlichten Preisen. Durch Caching und Rabatte liegt der tatsächlich gezahlte Preis oft deutlich unter dem Listenpreis.

Leistung

Der Durchsatz gibt an, wie schnell das Modell schreibt (Token pro Sekunde – höher ist besser). Die Latenz ist die gesamte Umlaufzeit (niedriger ist besser). TTFT ist die Zeit bis zum ersten Token – also die Wartezeit, bis etwas angezeigt wird (niedriger ist besser).

Verfügbarkeit

Verfügbarkeit ist der prozentuale Anteil der letzten 3 Tage, in dem mindestens ein Anbieter auf Anfragen reagiert hat. Die Verfügbarkeit der Inferenz ist der prozentuale Anteil der Zeit, in der Inferenz erfolgreich bereitgestellt wurde. OpenRouter überwacht dies kontinuierlich und verwendet den nächstbesten Anbieter, wenn ein Anbieter einen Fehler zurückgibt.

Leistungsvergleiche

Ergebnisse standardisierter Bewertungen und eigene Ausgaben dieses Modells zu gemeinsamen Vergleichstest-Prompts. Höhere Prozentwerte sind besser – und jeder Rang zeigt, wo dieses Modell unter den anhand dieser Quelle bewerteten Modellen liegt.

Zusammenfassung der Benchmark-Ergebnisse für OpenAI: GPT-4o-mini (batch) (Artificial Analysis)
QuelleBenchmarkErgebnis
Artificial AnalysisGPT-4o mini Coding Index11,4
Artificial AnalysisGPT-4o mini GPQA Diamond42.6%
Artificial AnalysisGPT-4o mini HLE4.2%
Artificial AnalysisGPT-4o mini IFBench31.0%
Artificial AnalysisGPT-4o mini τ-Bench Banking2.9%
Artificial AnalysisGPT-4o mini GDPval-AA0.0%
Artificial AnalysisGPT-4o mini LiveCodeBench23.4%
Artificial AnalysisGPT-4o mini Terminal-Bench 2.15.6%
Artificial AnalysisGPT-4o mini MMLU-Pro64.8%
Artificial AnalysisGPT-4o mini AIME 202514.7%
Artificial AnalysisGPT-4o mini AIME11.7%
Artificial AnalysisGPT-4o mini MATH-50078.9%

Apps

Öffentliche Apps, die den meisten Datenverkehr an dieses Modell senden. Ein guter Anhaltspunkt dafür, wie echte Produktionsworkloads aussehen – und ein Hinweis darauf, für welche Anwendungsfälle dieses Modell am besten geeignet ist.

Aktivität

Token-Volumen und Anfrageaufkommen für dieses Modell im Zeitverlauf.

API

Direkt einsetzbarer Code zum Aufrufen dieses Modells. Die API von OpenRouter ist OpenAI-kompatibel – bei den meisten SDKs genügt es, die Basis-URL auszutauschen. Zwischen den Modellen ändert sich nur der unten stehende Modell-Slug.

Derzeit nicht über EU-regionales Routing verfügbar. Dokumentation zum regionsinternen Routing

Weitere Modelle entdecken

KI-Modelle mit Bildverarbeitung: Multimodale LLMs für das BildverständnisSammlungKI-ModellranglistenRangliste
0,075 $0,30 $0,0375 $----
--
AutoExacto-Leistungsvergleiche
GPQA DiamondTAU-BenchOpenAI43,6 %26,0 %

Noch nicht genügend Daten zur Verfügbarkeit für eine Anzeige vorhanden.

Wenn bei einem vorgelagerten Anbieter ein Fehler auftritt, können wir diesen durch die Weiterleitung an einen anderen funktionsfähigen Anbieter beheben, sofern Ihre Anfragefilter dies zulassen. Sie können programmgesteuert auf die Verfügbarkeitsdaten pro Anbieter zugreifen, und zwar über die Endpunkt-API. Erfahren Sie mehr über unsere Optionen für Lastverteilung und Anbieter-Routing.

Für Apps, die dieses Modell verwenden, liegen noch nicht genügend Daten vor.

Häufig gestellte Fragen

GPT-4o mini is OpenAI's newest model after GPT-4 Omni, supporting both text and image inputs with text outputs. As their most advanced small model, it is many multiples more affordable than other recent frontier models, and more than 60% cheaper than GPT-3.5 Turbo. It maintains SOTA intelligence, while being significantly more cost-effective.

GPT-4o-mini (batch) kostet 0,075 $/M Eingabe-Token und 0,30 $/M Ausgabe-Token, mit separaten Tarifen für Cache Read für 0,0375 $/M tokens.

GPT-4o-mini (batch) hat ein Kontextfenster von 128.000 Token. Es unterstützt bis zu 16.384 Completion-Token.

Ja. GPT-4o-mini (batch) akzeptiert tools und tool_choice für Funktionsaufrufe. Es unterstützt auch strukturierte Ausgaben über ein JSON-Schema in response_format.

GPT-4o-mini (batch) akzeptiert Text, Bilder und Dateien wie PDFs als Eingabe und gibt Text zurück.

GPT-6.1 Terra Pro, GPT-6.1 Terra, GPT-6 Luna Decisions und 58 weitere sind weitere Modelle von OpenAI für die Modalität Text.

GPT-4o-mini (batch) wurde am 18. Juli 2024 veröffentlicht. Der Wissensstand reicht bis zum 31. Oktober 2023.

Weitere Modelle von 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

Text1,1M Kontext1 $ / 5 $
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

Text1,1M Kontext0,50 $ / 2,50 $
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.

Text1,1M Kontext1 $ / 5 $
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.

Text1,1M Kontext0,50 $ / 2,50 $
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.

Entscheidungen0,10 $ / 0 $
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

Text1,1M Kontext2 $ / 10 $
GPT-6.1 Sol Pro (batch)

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

Text1,1M Kontext1 $ / 5 $
GPT-6.1 Sol

GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series. It is suited for agentic coding, computer use, document-heavy professional work, and multi-step business workflow automation, and approaches Astra-level results on these tasks at a much lower cost. Compared with GPT-6 Sol, it makes fewer factual errors and is more reliable at respecting explicit restrictions and user intent during agentic tasks.

Text1,1M Kontext2 $ / 10 $
GPT-6.1 Sol (batch)

GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series. It is suited for agentic coding, computer use, document-heavy professional work, and multi-step business workflow automation, and approaches Astra-level results on these tasks at a much lower cost. Compared with GPT-6 Sol, it makes fewer factual errors and is more reliable at respecting explicit restrictions and user intent during agentic tasks.

Text1,1M Kontext1 $ / 5 $
GPT-6 Luna Pro

GPT-6 Luna Pro is the same underlying model as GPT-6 Luna, 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 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

Text1,1M Kontext0,10 $ / 0,50 $
GPT-6 Luna Pro (batch)

GPT-6 Luna Pro is the same underlying model as GPT-6 Luna, 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 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

Text1,1M Kontext0,05 $ / 0,25 $
GPT-6 Luna

GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks, and at higher reasoning effort it can take on complex software engineering and computer-use tasks that previously called for a Sol-tier model. It shares the GPT-6 family's gains in factual reliability and its clearer, more concise communication style.

Text1,1M Kontext0,10 $ / 0,50 $
GPT-6 Luna (batch)

GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks, and at higher reasoning effort it can take on complex software engineering and computer-use tasks that previously called for a Sol-tier model. It shares the GPT-6 family's gains in factual reliability and its clearer, more concise communication style.

Text1,1M Kontext0,05 $ / 0,25 $
GPT-6 Sol Pro

GPT-6 Sol Pro is the same underlying model as GPT-6 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 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 Sol instead.

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

Text1,1M Kontext2 $ / 10 $
GPT-6 Sol Pro (batch)

GPT-6 Sol Pro is the same underlying model as GPT-6 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 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 Sol instead.

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

Text1,1M Kontext1 $ / 5 $
GPT-6 Sol

GPT-6 Sol is the cost-efficient high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra and above the fast GPT-6 Luna tier. It is suited for demanding professional work, agentic coding, business workflow automation, and computer use, and is particularly strong at long-horizon software engineering tasks in real codebases. It approaches Astra-level factual reliability at a much lower cost and shares Astra's clearer, more concise communication style in technical and coding conversations.

Text1,1M Kontext2 $ / 10 $
GPT-6 Sol (batch)

GPT-6 Sol is the cost-efficient high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra and above the fast GPT-6 Luna tier. It is suited for demanding professional work, agentic coding, business workflow automation, and computer use, and is particularly strong at long-horizon software engineering tasks in real codebases. It approaches Astra-level factual reliability at a much lower cost and shares Astra's clearer, more concise communication style in technical and coding conversations.

Text1,1M Kontext1 $ / 5 $
GPT Astra Latest

This model always redirects to the latest model in the GPT Astra family.

Text1,1M Kontext
GPT Sol Latest

This model always redirects to the latest model in the GPT Sol family.

Text1,1M Kontext
GPT Terra Latest

This model always redirects to the latest model in the GPT Terra family.

Text1,1M Kontext