This model is deprecated. We only continue performance benchmarking for the default 10k input token workload. Results for other workloads are historical and no longer updated.

Google has launched a newer model, Gemini 3 Flash. We suggest considering it instead.

For more information, see comparison of Gemini 3 Flash to other models and API provider benchmarks for Gemini 3 Flash.

Gemini 2.5 Flash Preview (Sep '25) (Reasoning) logo
Google
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Proprietary model

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Released September 2025

Análise de inteligência, desempenho e preço do Gemini 2.5 Flash Preview (Sep '25) (Reasoning)

Benchmarks de provedores de API

Resumo do modelo

Inteligência

24
Artificial Analysis Intelligence Index
3 de 4 unidades para Inteligência.

Velocidade

N/D
Tokens de saída por segundo
Valor desconhecido entre 4 unidades para Velocidade.

Preço de entrada

US$ 0,00
USD por 1M de tokens
1 de 4 unidades para Preço de entrada.

Preço de saída

US$ 0,00
USD por 1M de tokens
1 de 4 unidades para Preço de saída.

Verbosidade

N/D
Tokens de saída do Intelligence Index
Valor desconhecido entre 4 unidades para Verbosidade.

Gemini 2.5 Flash Preview (Sep '25) (Reasoning) está acima da média em inteligência e tem preço competitivo em comparação com outros modelos de preço semelhante. O modelo aceita entrada em texto, imagem, fala e vídeo, gera saída em texto e tem uma janela de contexto de 1M tokens.

Gemini 2.5 Flash Preview (Sep '25) (Reasoning) alcança 24 pontos no Artificial Analysis Intelligence Index, ficando acima da média entre os modelos comparáveis (mediana: 15).

O preço do Gemini 2.5 Flash Preview (Sep '25) (Reasoning) é de $0.00 por 1M de tokens de entrada (preço competitivo, mediana: $0.20) e $0.00 por 1M de tokens de saída (preço competitivo, mediana: $0.60).

RaciocínioSim

Esta página mostra a versão com raciocínio deste modelo.

Também pode existir uma variante sem raciocínio.

Modalidade de entrada

Compatível com: texto, imagem, fala e vídeo

Modalidade de saída

Compatível com: texto

Janela de contexto1M
~1500 páginas A4 em fonte Arial tamanho 12

As métricas são comparadas com modelos da mesma classe:

  • Modelos sem raciocínio → comparados apenas com outros modelos sem raciocínio
  • Modelos de raciocínio → comparados com modelos com e sem raciocínio
  • Modelos de pesos abertos → comparados apenas com outros modelos de pesos abertos da mesma classe de tamanho:
    • Muito pequeno: ≤4B parâmetros
    • Pequeno: 4B–40B parâmetros
    • Médio: 40B–150B parâmetros
    • Grande: >150B parâmetros
  • Modelos proprietários → comparados com modelos proprietários e de pesos abertos da mesma faixa de preço, usando uma proporção combinada de 3:1 entre os preços de entrada e saída:
    • <$0.15 por 1M de tokens
    • $0.15–$1 por 1M de tokens
    • >$1 por 1M de tokens

Destaques

Inteligência

Artificial Analysis Intelligence Index · Higher is better

Velocidade

Output tokens per second · Higher is better

Custo por tarefa

Weighted average cost (USD) per Intelligence Index task · Lower is better

Inteligência

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR
Estimate (independent evaluation forthcoming)
Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR
Estimate (independent evaluation forthcoming)
Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if the weights are available but commercial use is limited (typically requires obtaining a paid license).

Avaliações

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better
GDPval-AA v2

Agentic real-world work tasks, (Elo-500)/2000

𝜏³-Banking

Agentic tool use

Terminal-Bench v2.1

Agentic coding & terminal use

SciCode

Coding

Humanity's Last Exam

Reasoning & knowledge

GPQA Diamond

Scientific reasoning

CritPt

Physics reasoning

AA-Omniscience Accuracy

Knowledge

AA-Omniscience Non-Hallucination Rate

1 - hallucination rate

AA-LCR

Long context reasoning

AA-Briefcase

Agentic knowledge work, Elo

AutomationBench-AA

Agentic SaaS workflows

Harvey LAB-AA

Legal agentic work, criterion pass rate

EnterpriseOps-Gym-AANew

Agentic business operations

IFBench

Instruction following

APEX-Agents-AA

Long-horizon agentic tasks

ITBench-AA

Kubernetes incident root-cause analysis

MMMU-Pro

Visual reasoning

Reasoning models are indicated by a lightbulb icon

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

AA-Omniscience

AA-Omniscience Index

AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.
Reasoning models are indicated by a lightbulb icon

AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.

Comparações do Intelligence Index

Intelligence Index vs. Cost per Intelligence Index Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task
Most attractive quadrant
Pareto line
Reasoning models are indicated by a lightbulb icon

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Custo

Cost per Intelligence Index Task

Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better
Reasoning models are indicated by a lightbulb icon

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

Cost to Run Artificial Analysis Intelligence Index

Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index
Reasoning models are indicated by a lightbulb icon

The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats).

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens)
Reasoning models are indicated by a lightbulb icon

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

Janela de contexto

Context Window

Context window: tokens limit · Higher is better
Reasoning models are indicated by a lightbulb icon

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Perguntas frequentes

Perguntas comuns sobre o Gemini 2.5 Flash Preview (Sep '25) (Reasoning)

O Gemini 2.5 Flash Preview (Sep '25) (Reasoning) foi lançado em 25 de setembro de 2025.

Google criou o Gemini 2.5 Flash Preview (Sep '25) (Reasoning).

Gemini 2.5 Flash Preview (Sep '25) (Reasoning) alcança 24 pontos (estimativa) no Artificial Analysis Intelligence Index, ficando acima da média entre outros modelos de raciocínio em uma faixa de preço semelhante (mediana: 15).

Sim, o Gemini 2.5 Flash Preview (Sep '25) (Reasoning) é um modelo de raciocínio. Ele usa reflexão prolongada ou raciocínio em cadeia para resolver problemas complexos antes de fornecer uma resposta.

Gemini 2.5 Flash Preview (Sep '25) (Reasoning) aceita entrada em texto, imagem, fala e vídeo.

Gemini 2.5 Flash Preview (Sep '25) (Reasoning) permite saída em texto.

Sim, o Gemini 2.5 Flash Preview (Sep '25) (Reasoning) aceita imagens como entrada e pode analisá-las, descrevê-las e responder a perguntas sobre elas.

Sim, o Gemini 2.5 Flash Preview (Sep '25) (Reasoning) é multimodal. Ele consegue processar entrada em texto, imagem, fala e vídeo e gerar saída em texto.

Gemini 2.5 Flash Preview (Sep '25) (Reasoning) tem uma janela de contexto de 1.0M tokens. Isso determina quanto texto e histórico da conversa o modelo consegue processar em uma única solicitação.

Não, o Gemini 2.5 Flash Preview (Sep '25) (Reasoning) é proprietário. Os pesos não estão disponíveis publicamente.

Gemini 2.5 Flash Preview (Sep '25) (Reasoning) é um modelo proprietário, e Google não divulgou o tamanho nem o número de parâmetros do modelo.

Gemini 2.5 Flash Preview (Sep '25) (Reasoning) alcança 24 pontos no Artificial Analysis Intelligence Index. Esse benchmark composto avalia os modelos em raciocínio, conhecimento, matemática e programação.

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