GPT-6 Astra vs GPT-5.6 Sol ka comparison 3 September 2026 ke baad se har jagah chal raha hai — "2.5x mehnga" aur "lagbhag 99% ARC-AGI-3" wale headlines ne number dediye hain, lekin do claims aise hain jo top articles mein baar baar galat chhape hain: ek context window wala, ek pricing wala. Dono ko yahan OpenAI ke primary source se verify kar rahe hain, saath mein do hafte dono models chalane ke apne notes.
Ye post aapke liye hai agar aap developer hain jo decide kar rahe ho kaunsa model choose karein, ya agar aap sirf ye jaanna chahte ho ki Sol ab bhi worth rakhta hai ya nahi.
Spec Sheet: Dono Side By Side
| Spec | GPT-5.6 Sol | GPT-6 Astra |
|---|---|---|
| Launch | July 2026 | 3 September 2026 |
| Context window | 1,050,000 tokens | 1,050,000 tokens |
| Max output | 128,000 tokens | 128,000 tokens |
| Knowledge cutoff | 16 February 2026 | 30 April 2026 |
| API input / output | $4 / $20 per 1M (promo) | $10 / $50 per 1M |
| Cached input | $0.40 per 1M | $1.00 per 1M |
| Reasoning efforts | none → max | low → max |
| Intelligence Index (AA) | 47 | 53 |
| Output speed (AA) | ~85 tok/s | ~59 tok/s |
| ChatGPT access | Sabke liye, publicly | Sirf paid plans |
Dono ke official model pages OpenAI ke developers.openai.com par live hain (September 2026), aur dono hi gpt-5.6 alias ke saath aate hain — gpt-5.6 request Sol par route hota hai. Astra abhi tak koi alias ke naam se nahi, seedha gpt-6-astra.
Context Window Ka Sach: 272K Wala Claim Galat Hai
Ye sabse important correction hai. GadgetsNow samet kaafi articles likhte hain ki "Astra ka context ~1 million hai jabki Sol ka sirf 272 thousand" — aur isi comparison ko bahut si LinkedIn aur X posts ne bhi copy kar liya hai. Dono ke official pages par context window 1,050,000 tokens likha hai. Difference zero hai.
To 272K aaya kahan se? Wo OpenAI ki long-prompt pricing threshold hai, window nahi. Dono models ke docs mein ye line hai: 272K se zyada input tokens wali prompts par puri request 2x input rate (aur 1.5x output rate) se charge hoti hai. Yaani 272K ek billing boundary hai jo dono par lagti hai — ye Sol ki capacity nahi hai.
Practical matlab: purani conversation ya bade codebase ko yaad rakhne ki capacity dono model mein barabar hai. Agar koi aapko "Sol sirf 272K ka hai" bol kar Astra ki upgrade reason de raha hai, to wo galat number de raha hai. Context ke naam par upgrade karne ki zaroorat nahi — intelligence, speed aur price par decision lo.
Intelligence: Astra Jeeta Hai, Lekin Har Jagah Nahi
OpenAI ke apne numbers: ARC-AGI-3 (novel reasoning) par Astra ko lagbhag 99% mila hai (AndroidHire ke report mein exact 99.9%) jabki Sol wahi ~8% par tha. Computer use par OSWorld 2.0 mein 72.6% at roughly 40 minutes per task, aur DeepSWE v1.1 software engineering par 74.1% — ye teeno OpenAI ke claims hain. GadgetsNow ke report ke mutabik computer-use tasks jo Sol ko 75 minute lete the, Astra aadhe se bhi kam mein kar leta hai.
Independent side par Artificial Analysis (September 2026) ka Intelligence Index 53 vs 47 hai — Astra aage, clear. Unke breakdown mein fark dikhta hai:
- Terminal-Bench 4.0: Astra 59% vs Sol 40% — terminal/agent tasks mein bada gap
- Humanity's Last Exam: Astra 55% vs Sol 49%
- AA-Omniscience: Astra 43 vs Sol 22 — open-domain knowledge recall mein double
- AutomationBench: Astra 68% vs Sol 60%
Lekin har jagah Astra nahi jeetta. GDPval-AA v2.1 mein Sol aage hai (1588 vs 1542) — matlab professional real-world document quality par purana model abhi bhi competitive hai. SciCode (57% vs 56%) aur AA-LCR long-context recall (84% vs 81%) mein bhi Sol thoda aage hai. Ye wahi baat hai jo GadgetsNow ki FAQ mein bhi hai: Astra field mein har category mein lead nahi karta, aur practical gain task distribution par depend karta hai.
Speed Aur Latency: Yahan Sol Aage Hai
Ek comparison jise headlines miss karte hain: Astra Sol se slow hai. Artificial Analysis ke measurements (max reasoning par): Astra ~59 tokens/sec generate karta hai bana Sol ke ~85 tokens/sec, aur time-to-first-token ~326 second vs Sol ka ~124 second. End-to-end (500-token response) mein bhi farak hai — ~335s vs ~130s.
Ye numbers extreme reasoning setting ke hain, lekin direction clear hai: Astra sochta zyada hai, jawab deta der se hai. Quick chat, turant draft, lightweight tool call — ye sab Sol par snappy feel hoga. Jab mera test prompt ek simple rewriting task tha, to wait ka difference bilkul notice kiya ja sakta hai — high-effort Astra apna thinking loop khatam karne se pehle Sol jawab de chuka hota hai.
Iska simple rule bana lijiye: latency-sensitive pipeline mein default Astra mat karo. Router lagao — mushkil step Astra, baaki Sol — warna per-call cost bhi badega aur response time bhi.
Pricing: "2.5x Mehnga" Ka Pura Hisaab
Astra: $10 input / $50 output per 1M tokens, cached input $1, cache writes $12.50. Sol: $4 / $20 per 1M — lekin ye promotional rate hai jo OpenAI ke docs ke mutabik kam se kam 21 November 2026 tak ke liye hai; pre-promotion list rate $5 / $30 thi (OrcaRouter ke report ke mutabik).
Ab "2.5x" ka figure: promotional Sol rate ke against $10/$50 exactly 2.5x hai input aur output dono par — GadgetsNow aur OpenAI dono ye number is tarah use karte hain. Lekin purani list rate ($5/$30) ke against ratio 2x input aur ~1.67x output hai. Yaani "2.5x" wohi tab lagta hai jab base mein Sol ka discount ho — figure ke saath rate ka context dena zaroori hai.
Blended (cache/input/output ko 7:2:1 weight par) Artificial Analysis hisaab se Astra $7.70 per 1M padta hai bana Sol ke $3.08 ke. Per-task cost bhi wahi pattern: $3.26 vs $1.99.
OpenAI ka counter-argument: Astra ko kam steps chahiye — company kehti hai kuch tasks par per-task cost ~57% kam aa sakti hai. Ye OpenAI ke apne test workloads ka claim hai, independent verification nahi. Isliye measured advice yahi hai ki apne pipeline ka cost ek hafte Astra par, ek hafte Sol par chala kar dekho — assumptions nahi, real bill dekho. Batch mode dono par 50% discount par milta hai.
Features Aur Safety: Dono Mein Changes Hain
Capability list officially dono ki lagbhag same hai: web search, code interpreter, computer use, apply patch, skills, MCP — dono models support karte hain. Astra ka difference kitna achha karta hai mein hai, feature checklist mein nahi. Do exceptions:
- Reasoning dial: Sol
noneeffort bhi allow karta hai (scripted/cheap calls ke liye); Astra ka minimumlowhai — uske neeche koi option hi nahi - Safety classification: Astra ko OpenAI ke Preparedness Framework mein "Critical" rating mili — pehli baar kisi OpenAI model ko. ExploitBench par 100% aur do naye zero-days ki khoj ki wajah se uski cybersecurity superpowers sirf trusted users tak limited hain. Sol par ye restriction nahi
Knowledge cutoff ka farak bhi real hai: Sol 16 February 2026 tak, Astra 30 April 2026 tak — do mahine ka fresh data Astra ko events ke sawalon mein edge deta hai.
Kaunsa Model, Kis Kaam Ke Liye?
Ek decision table jo mera abhi tak ka experience summarize karti hai:
| Aapka kaam | Kaunsa | Kyun |
|---|---|---|
| Coding agent, browser automation | Astra | Terminal-Bench 59% vs 40%, fewer errors on multi-step |
| Long documents, research synthesis | Astra ya dono A/B test | Better context retention (AA) par recall mein Sol close hai |
| Writing, customer support, drafts | Sol ya Terra | GDPval mein Sol aage; sasta aur fast |
| Quick answers, latency-sensitive API | Sol | ~85 vs ~59 tok/s, TTFT ~124s vs ~326s |
| Budget pipeline, heavy volume | Sol | Blended ~2.5x cheaper per token |
| Free ChatGPT users | Sol (default) | Astra tak paid plan zaroori — <!-- TODO internal link: GPT-6 Astra free access aur cheapest way --> |
Ye table September 2026 ke rate par hai, aur Sol ka promotional rate November ke baad badal sakta hai — pricing page har launch ke baad check karte rahiye. Dono models ki naming story samajhni ho to <!-- TODO internal link: AI model naming explained --> padhiye, aur Astra ke basics chahiye to hamari GPT-6 Astra guide hai.
Ek caution: koi bhi "X% faster/cheaper" headline dekh kar mat chuniye — uska base rate, task type aur reasoning setting confirm kiye bina number ka half meaning nahi hota.
Asli Testing Notes: Agents Mein Dono Kaise Behave Karte Hain
Numbers ke alawa behavioural farak bhi dikhta hai. Artificial Analysis ke agent tests mein ek clear pattern: Astra apne aap calculate kar leta hai jahan Sol function-call karta hai — matlab agent loop mein ek tool call kam. Long research chalate waqt Astra ki research summaries zyada error-prone mili (0.4 errors/1k chars), lekin frugal mode on karte hi wo ghut jaata hai (0.2) — config ki setting farak badal deti hai.
Doosra point reasoning transparency ka hai: GadgetsNow ki report mein OpenAI mana raha hai ki Astra ka internal reasoning pehle se zyada compact hai, jo researchers ke liye externally monitor karna mushkil banata hai. Matlab Astra behtar sochta hai, par "kaise socha" itna dikhata nahi — high-stakes workflow mein ye ek real trade-off hai.
Rollout ka pattern bhi alag tha. OpenAI ne Sol par staged rollout dikhaya tha; Astra ka ek 100k-users gradation par independent measurement (AndroidHire) batata hai ki company ke apne routing test mein default chatbot traffic ka ~75% Sol ko hi ja raha tha — system dono ko ek saath hi run kar raha hai, zero-sum winner nahi hai. Free tier par Sol hi default hai: isse juda pura free-access hisaab hamare GPT-6 Astra guide mein hai, aur Jev jaise non-chat models ka angle <!-- TODO internal link: Jev AI kya hai --> par.
FAQs
Kya GPT-5.6 Sol ka context window sach mein 272K hai?
Nahi. OpenAI ke official model page par dono models ka context window 1,050,000 tokens hai. 272K wo pricing threshold hai jiske upar long prompts 2x input rate se charge hote hain — ye billing rule hai, context capacity nahi.
GPT-6 Astra vs GPT-5.6 Sol — kaun zyada fast hai?
GPT-5.6 Sol. Artificial Analysis ke measurements mein Sol ~85 tokens/sec par chalta hai aur Astra ~59 par; max reasoning par pehla token aane mein bhi Sol (~124s) Astra (~326s) se kaafi aage hai.
Astra 2.5x mehnga hai — koi jariya hai isko sasta karne ka?
Do tarike hain: batch mode (50% off, dono models par) aur Astra ko sirf mushkil steps par dena, simple steps Sol/Terra par — yaani router pattern. OpenAI ka apna claim hai ki Astra kam steps mein kaam khatam karta hai, jisse per-task cost ~57% tak ghat sakti hai — par ye company ke test workloads ka figure hai.
Kya GPT-5.6 Sol ab bhi available hai?
Haan. Sol publicly available hai, koi waitlist nahi — free ChatGPT accounts par wo default hi hai. Astra sirf paid ChatGPT plans (Plus/Pro/Business/Enterprise) aur API par hai. ChatGPT plans wala full hisaab hamare GPT-6 Astra guide mein hai.