Gemini 4 Argon: 1M Output Token, $2 Input — Par Abhi Aap Use Nahi Kar Sakte
Google ka naya frontier model ek hi jawab me 10 lakh token tak likh sakta hai aur $2 per million input token se launch hua hai. Par abhi ye sirf chune hue cyber-security teams ke liye hai.
Read in English
Google ne 30 September ko Gemini 4 Argon announce kiya — lambe software-engineering kaam, legal aur finance research, aur cyber defence ke liye. Numbers bade hain, par release chhota hai: abhi Argon sirf Google ke Fairwind Program ke "trusted cyber defenders" ko mil raha hai.
1 million wala number output hai, context nahi
Kai jagah likha hai ki Argon ka context window 10 lakh token ka hai. Google ye nahi kehta. Google ke announcement me 1M token output likha hai, "pehle ke 64K se". Matlab Argon ek hi jawab me bahut lamba kaam — bada code migration ya lambi report — likh sakta hai, alag-alag tukdon me nahi.
Input context window kitna hai, ye Google ne nahi bataya. Jab tak na bataye, koi bhi number unconfirmed maaniye.
Kitna kharch — jab milega
| Input (per 1M token) | Output (per 1M token) | |
|---|---|---|
| Introductory price | $2 | $10 |
| Standard price (intro period ke baad) | $4 | $20 |
| Cached input | input price se 95% kam | — |
95% chhoot ka matlab cached input intro rate par $0.10 per million aur standard rate par $0.20. Intro period kitne din chalega, Google ne nahi bataya. Tulna ke liye, September me aaye GPT-6 Astra aur Claude Fable 5.1 dono $10 input aur $50 output per million par hain. Kaagaz par Argon kaafi sasta hai — par abhi khareed nahi sakte.
Google ke diye hue benchmarks
Ye Google ke apne numbers hain. Google ne khud chalaye; kisi independent lab ne abhi dohraye nahi.
| Benchmark | Kya naapta hai | Argon ka score |
|---|---|---|
| DeepSWE v1.1 | Asli software engineering | 77.9% |
| AutomationBench | Multi-step kaam automate karna | 51.3% (#1) |
| LVBench | Lambi video samajhna | 91.7% |
| CWE-bench v1 | Security kamzoriyan dhundhna aur theek karna | 68% (pehle number par barabar) |
Google kehta hai Argon kuch aur benchmarks me bhi aage hai, par unke score nahi diye. Bina number ke "aage hai" ka dawa kam bharosemand hai, isliye hum use table me nahi daal rahe.
Release itna chhota kyun hai
Google iska kaaran safety batata hai — misuse, prompt-injection attack, model misalignment aur system ki kamzoriyon se bachav ke liye "phased approach". Jo model security flaws dhundh kar theek karne me itna achha hai, wahi unhe dhundh kar galat use bhi kar sakta hai. Isliye pehle defenders ko diya gaya hai, taaki wo pehle patch kar saken.
Aage kise milega, aur India ke liye matlab
- Abhi: Fairwind Program ki chuni hui cyber-security teams.
- Google ke mutabik agla: paid Gemini API customers aur Google AI Ultra subscribers, "jitni jaldi ho sake".
- Timeline: nahi diya. Google ke post me India ya kisi aur desh ka zikr nahi.
Indian developer ke liye aaj ka seedha jawab: Argon call hi nahi kar sakte, to migrate karne ko kuch nahi hai. Access khulne par apne asli token count ke saath AI cost calculator me hisaab zaroor lagaiye, sirf headline rate par nahi.
Sources
- Google: Gemini 4 Argon announcement (30 September 2026)
Frequently asked questions
Kya India me abhi Gemini 4 Argon use kar sakte hain?
Nahi. 30 September 2026 ke announcement ke mutabik Argon abhi sirf Google ke Fairwind Program ki cyber-security teams ko mil raha hai. Agla number paid API customers aur Google AI Ultra subscribers ka hai, par Google ne tareekh ya desh nahi bataye.
Kya Gemini 4 Argon ka context window 1 million token hai?
Google ke announcement me 1 million output token likha hai, pehle ke 64K se — yani jawab kitna lamba ho sakta hai. Input context window Google ne nahi bataya, isliye 1M context ka dawa confirm nahi hai.
Gemini 4 Argon kitne ka hai?
Intro price $2 per million input token aur $10 per million output token hai, jo intro period ke baad $4 aur $20 ho jayega. Cached input par input price se 95% chhoot hai.
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AICreatorHub Team
The AICreatorHub editorial team is a group of hands-on AI practitioners, writers and developers based in India. We test AI tools and models ourselves, track official releases from OpenAI, Anthropic, Google, Meta and xAI, and translate them into simple, India-first guides in English and Hindi. Every article is written for real Indian use cases — pricing in rupees, free-tier tips and practical, tested steps — so you get accurate, up-to-date and genuinely useful AI information.