Esta reseña aún no está disponible en Español, así que estás leyendo el original en English.
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.
Freedom Score
Aún sin probar
- Precio
- 8,00 US$ por 1 M de tokens mixtos (3 de entrada : 1 de salida)
- Velocidad de salida
- 33 tok/s
- Tasa de éxito
- Recopilando datos
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.
- SpicyAPI Engineering
- Probado el 28 oct 2026
- Metodología v3.3 →
- Vendemos estos modelos; el precio no cuenta en la puntuación →
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.
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.
Lo que nos gustó y lo que lo frenó
Lo que nos gustó
- 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.
Lo que lo frenó
- 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.
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.
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.
Cómo gana Gemini 4 Argon su Spicy Index
Cada dimensión enlaza con su cálculo completo: la fila de la tabla de la que sale cada punto y por qué se perdieron puntos.
- Clasificaciones públicas 40 % de la calidad
- Aún sin probar
- Rol 15 % de la calidad
- Aún sin probar
- Escritura creativa 15 % de la calidad
- 61,6
- Seguimiento de instrucciones 15 % de la calidad
- 99,0
- Memoria con contexto largo 15 % de la calidad
- Aún sin probar
- Capacidad Peso del 10,5 %
- 56,0
- Freedom Score Peso del 30 %
- Aún sin probar
Aún no hay una coincidencia exacta en las clasificaciones públicas que seguimos. Cómo funciona
Nuestra batería de rol aún no se ha ejecutado con este modelo. Cómo funciona
Nuestra batería de contexto largo aún no se ha ejecutado con este modelo. Cómo funciona
La libertad no se ha probado o las pruebas son insuficientes. El Index conserva la puntuación original de calidad y capacidades, se marca como provisional y sigue recibiendo posición. La falta de pruebas no equivale a cero. Cómo funciona
La libertad no se ha probado o las pruebas son insuficientes. El Index conserva la puntuación original de calidad y capacidades, se marca como provisional y sigue recibiendo posición. La falta de pruebas no equivale a cero.
Abrir el informe de prueba completo →Capacidad, punto por punto
Puntos de la tabla pública de puntuación. Los niveles reescalados y los límites que fijamos nosotros no cuentan.
- Ventana de contexto (publicada por el creador)Sin declarar
- 0,0 / 30
- Modalidades de entrada en SpicyAPITexto, más imágenes, audio
- 19,0 / 25
- Uso de herramientasHerramientas y tool_choice
- 15,0 / 15
- Salida estructuradaSe acepta, cumplimiento del esquema verificado
- 15,0 / 15
- Control del razonamiento3 niveles: low · medium · high
- 7,0 / 15
Lo que Gemini 4 Argon puede hacer en SpicyAPI
Tomado directamente de la especificación en vivo del modelo en SpicyAPI. Algunos creadores ofrecen más en sus propias apps; esto es lo que puedes llamar hoy desde nuestra API.
| Función | Conversación |
|---|---|
| Ventana de contexto | 1.048.576 tokens |
| Salida máxima por solicitud | 65.536 tokens |
| Niveles de razonamiento | low · medium · high |
| Llamada a herramientas | Sí |
| Salida estructurada | Sí |
Cuánto tarda de verdad
Medido con trabajos reales de los últimos 30 días, desde la solicitud hasta el resultado final. Los tiempos incluyen nuestras propias pruebas.
- Velocidad de salida
- 33 tok/sIncluye el tiempo hasta el primer token
- Tasa de éxito
- Recopilando datos
Un tiempo aparece cuando hay al menos 10 trabajos completados. Las tasas de éxito solo cuentan trabajos de clientes y siguen ocultas para todos los modelos hasta completar 30 días de tráfico.
Lo que dice la gente de Gemini 4 Argon
0 positivos · 1 mixtos · 1 negativos
Big number results, and impressive pricing. That said it really feels like benchmarks have been hyper saturated these days.
hacker-news· 30 sept 2026· MixtoFuente
Hate to say i will never be touching this model for anything except for youtube video understanding
hacker-news· 30 sept 2026· NegativoFuente
Las citas son textuales de publicaciones públicas y enlazan al original. No son calificaciones ni alimentan ninguna puntuación.
Modelos que puedes considerar en lugar de Gemini 4 Argon
OpenAI
GPT 6.1 Sol
Hard coding with a larger reply ceiling?
- Spicy Index
- 81,2+4,5
- Freedom Score
- —
- Precio
- 4,00 US$−50 %/ 1 M tokens · entrada/salida 3:1
Google
Gemini 3.7 Flash
A lighter Google model?
- Spicy Index
- 77,8+1,1
- Freedom Score
- 73,3
- Precio
- 1,35 US$−83 %/ 1 M tokens · entrada/salida 3:1
Anthropic
Claude Opus 5.5
An Anthropic flagship?
- Spicy Index
- 82,5+5,8
- Freedom Score
- 88,9
- Precio
- 7,20 US$−10 %/ 1 M tokens · entrada/salida 3:1
¿Qué opinas?
¿Te resultó útil esta reseña?
Inicia sesión para votar.
Comentarios
Los comentarios se revisan de forma automática y por nuestro equipo. Eliminamos el spam, el contenido inapropiado, los ataques personales y cualquier cosa que nombre a una persona real sin su consentimiento. Si reportas un comentario, lo revisamos en un día hábil.
¿Probaste este modelo? Comparte lo que te funcionó. Necesitas una cuenta gratuita para comentar, así mantenemos fuera el spam.
Preguntas frecuentes sobre Gemini 4 Argon
Prueba Gemini 4 Argon por tu cuenta
Ajusta cada parámetro en el Playground y mira el precio exacto antes de lanzarlo.
8,00 US$ por 1 M de tokens mixtos (3 de entrada : 1 de salida)
Más reseñas
Ver las clasificaciones →GPT 6.1 Terra
Pick GPT 6.1 Terra for high-volume screens, documents and writing where reasoning_effort none helps; so far we have run only launch checks, no scored tests.
- Spicy Index
- 79,9
- Freedom Score
- —
Probado el 28 oct 2026
Leer la reseñaKimi K3.1 Pro
Pick Kimi K3.1 Pro for long-context work with screenshots and clips when you accept always-on thinking; so far we have run only launch checks, no scored tests.
- Spicy Index
- 80,4
- Freedom Score
- —
Probado el 28 oct 2026
Leer la reseña
Grok 4.3
Elige Grok 4.3 por su ventana de contexto enorme, un apagado real del razonamiento y escritura sin censura a bajo precio; sáltatelo si necesitas archivos.
Probado el 24 sept 2026
Leer la reseña