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Gemini 4 Argon Review: 1M Context, but a 65,536-Token Reply Cap

Pick Gemini 4 Argon for million-token analysis with images and audio, but plan around its 65,536-token reply cap; so far we have run only launch checks.

Spicy Index

76,7/ 100

Preliminar

Freedom Score

Ainda não testado

Preço
US$ 8,00 por 1 M de tokens mistos (3 de entrada : 1 de saída)
Velocidade de saída
32 tok/s
Taxa de sucesso
Coletando dados

Gemini 4 Argon is Google's new frontier model, announced on 30 September 2026 and aimed at software engineering, enterprise knowledge work and cyber defence. On our API it is one OpenAI-compatible chat endpoint that takes text, images and audio, reads up to 1,048,576 tokens and returns up to 65,536 tokens per reply, with function calling, streaming and three reasoning levels.

The verdict

The most common point of confusion is the output limit. Google's announcement mentions a 1M-token output ceiling, but its developer documentation ties that to a separate long-running mode, while ordinary synchronous calls stop at 65,536 tokens. Our endpoint is the synchronous kind, so plan for 65,536 per reply and split longer work across turns.

This is a launch-day review. On 28 October 2026 our platform ran a real request through the endpoint as part of launch: one neutral message, answered without streaming at low reasoning effort. It returned a complete answer. We also tried video input three ways during integration and it was rejected each time, so this endpoint does not offer video. We have not run a quality blind test or a content-level test, and this page does not score the model.

Try Gemini 4 Argon →

Key facts

  • Tested: one real launch request on 28 Oct 2026 (neutral prompt, low reasoning effort, no streaming), plus integration checks of image and audio input and of video rejection. No scored runs yet.
  • Price: the live price, including cached input, is on the model page.
  • Limits: 1,048,576-token context shared by input and output, replies up to 65,536 tokens (default 4,096, thinking included), text, image and audio input (wav or mp3, 14 MB combined inline), no video or PDF parts.
  • Reasoning: reasoning_effort takes low, medium or high (default medium); thinking cannot be switched off.
  • Sources: scoring rules are on our review methodology page, full parameters on the Gemini 4 Argon model page.

O que gostamos e o que atrapalhou

O que gostamos

  • Audio is accepted directly. wav or mp3 can be sent as audiourl or base64 inputaudio next to text and images, so a voice note or call recording sits in the same conversation as your instructions.
  • A million-token window. Contracts, transcripts, a specification and the code it describes can travel together as written.
  • Sampling stays adjustable. temperature (0 to 2) and topp are available, along with stop sequences and responseformat.
  • Tool calling is on the endpoint. Up to 128 function definitions per request with toolchoice and paralleltool_calls; we have not graded tool-use quality yet.
  • Google publishes numbers. Google reports 77.9% on DeepSWE v1.1 (long-horizon software engineering) and 51.3% on AutomationBench. Those are Google's figures; we have not reproduced them.

O que atrapalhou

  • Replies stop at 65,536 tokens here. The 1M-output figure in Google's announcement does not apply to this endpoint, and thinking counts toward the 65,536.
  • No video input. Google lists video among the model's input types, but our three integration attempts were all rejected, so frames or a separate audio track are the workaround.
  • No PDF parts. Send pages as images or extracted text.
  • Thinking cannot be turned off, and low is the lightest setting, so short lookups still pay for a reasoning pass.
  • No quality numbers of our own yet. We have not run a blind test, a speed test or a long-document test.

What we tested

On 28 October 2026 our platform sent Gemini 4 Argon one real request as part of launch: a single neutral user message, answered without streaming at low reasoning effort with a 1,024-token cap. It returned a complete answer, and the request was priced at the published rate. The endpoint also passed our pre-launch checks of its price table and request limits.

During integration, image and audio input were accepted and answered. Video was different: a one-second clip with sound, a five-second silent clip and the same clip sent inline each came back as a rejected request, so the endpoint declares only images and audio.

That is a working-endpoint check, not a benchmark. We have not compared Argon's answers with another model, measured speed, or tried a prompt near the 1,048,576-token limit.

Prompts to start from

These starting prompts come from the model page's published examples. We have not graded the outputs, so they are a place to begin rather than prompts proven on this model.

1. Compare a transcript with a brief. Paste both documents, label them, and say which is authoritative.

text
Compare a meeting transcript with the product brief and list unresolved decisions. Work from the material I provide, cite the relevant evidence, distinguish facts from assumptions, and identify missing information before proposing changes.

Run this prompt on Gemini 4 Argon →

2. A tool step. Confirms your function-calling loop end to end with a trivial function.

text
Call report_status with status ready.

Settings that matter: raise maxtokens as you raise reasoningeffort, because thinking is paid for out of the same 65,536; send audio inline and keep it under 14 MB combined; for work longer than one reply, ask for it in parts.

How far it writes

We have not run our content-level test on Gemini 4 Argon, so we have no result to report and the endpoint carries no Unrestricted label. The model page states the position plainly: content decisions come from the model, behaviour can vary, and no guarantee of unrestricted output is made.

Not tested yet: the content-level ladder, multi-turn behaviour over a long session, languages other than English, audio quality on noisy recordings, and prompts close to the context limit.

Every character in a request should be an adult, keep real, identifiable people out of it, and you are responsible for the law where you publish.

What the community says

Reaction on the launch thread was cautious about the benchmarks. One reader wrote "Big number results, and impressive pricing. That said it really feels like benchmarks have been hyper saturated these days." Another was blunter about where they would use it: "Hate to say i will never be touching this model for anything except for youtube video understanding", which is the one input type our endpoint does not offer.

Alternatives

  • Hard coding with a larger reply ceiling? GPT 6.1 Sol allows replies up to 128,000 tokens and takes images but not audio.
  • A lighter Google model? Gemini 3.7 Flash is the Flash-class option from the same publisher.
  • An Anthropic flagship? Claude Opus 5.5 is the Anthropic option on the same API; compare it on your own prompts.

Como Gemini 4 Argon conquista seu Spicy Index

Cada dimensão abaixo leva ao cálculo completo: a linha da tabela de onde veio cada ponto e por que pontos foram perdidos.

Rankings públicos 40% da qualidade
Ainda não testado

Ainda sem correspondência exata nos rankings públicos que acompanhamos. Como funciona

Roleplay 15% da qualidade
Ainda não testado

Nosso conjunto de testes de roleplay ainda não rodou neste modelo. Como funciona

Escrita criativa 15% da qualidade
61,6
Seguimento de instruções 15% da qualidade
99,0
Memória em contexto longo 15% da qualidade
Ainda não testado

Nosso conjunto de testes de contexto longo ainda não rodou neste modelo. Como funciona

Capacidade Peso de 10,5%
56,0
Freedom Score Peso de 30%
Ainda não testado

A liberdade não foi testada ou as evidências são insuficientes. O Index mantém a pontuação original de qualidade e capacidades, recebe a marca preliminar e continua no ranking. Evidência ausente não equivale a zero. Como funciona

A liberdade não foi testada ou as evidências são insuficientes. O Index mantém a pontuação original de qualidade e capacidades, recebe a marca preliminar e continua no ranking. Evidência ausente não equivale a zero.

Abrir o relatório de teste completo →

Capacidade, item por item

Pontos da tabela pública de pontuação. Níveis obtidos por ampliação e limites definidos por nós não contam.

Janela de contexto (publicada pelo criador)Não informado
0,0 / 30
Modalidades de entrada na SpicyAPITexto, mais imagens, áudio
19,0 / 25
Uso de ferramentasFerramentas e tool_choice
15,0 / 15
Saída estruturadaAceito, aderência ao esquema verificada
15,0 / 15
Controle de raciocínio3 níveis: low · medium · high
7,0 / 15

O que Gemini 4 Argon faz na SpicyAPI

Direto da especificação atual do modelo na SpicyAPI. Alguns criadores oferecem mais nos próprios apps; estas são as funções que você pode usar pela nossa API hoje.

Capacidades por endpoint
RecursoConversa
Janela de contexto1.048.576 tokens
Saída máxima por solicitação65.536 tokens
Níveis de raciocíniolow · medium · high
Chamada de ferramentasSim
Saída estruturadaSim
Ver todos os parâmetros e exemplos de código →

Quanto tempo leva de verdade

Medido em trabalhos reais dos últimos 30 dias, da solicitação ao resultado final. Os tempos incluem nossos próprios testes.

Velocidade de saída
32 tok/sInclui o tempo até o primeiro token
Taxa de sucesso
Coletando dados

Um tempo aparece quando há pelo menos 10 trabalhos concluídos. As taxas de sucesso contam só trabalhos de clientes e ficam ocultas para todos os modelos até completarmos 30 dias de tráfego.

O que falam sobre Gemini 4 Argon

0 positivos · 1 mistos · 1 negativos

  • Big number results, and impressive pricing. That said it really feels like benchmarks have been hyper saturated these days.

    hacker-news· 30 de set. de 2026· MistoFonte

  • Hate to say i will never be touching this model for anything except for youtube video understanding

    hacker-news· 30 de set. de 2026· NegativoFonte

As citações são literais de posts públicos, com link para o original. Não são notas e não entram em nenhuma pontuação.

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Perguntas frequentes sobre Gemini 4 Argon

Teste Gemini 4 Argon você mesmo

Ajuste cada parâmetro no Playground e veja o preço exato antes de rodar.

US$ 8,00 por 1 M de tokens mistos (3 de entrada : 1 de saída)

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