जेमिनी 3.8 Flash
नवीनLatest Flash generation; fast multimodal reasoning across every input type.
लाँच दिनांक: 2 सप्टें, 2026
₹360.00
प्रति 10 लाख आउटपुट Tokens
इनपुट: ₹72.00 प्रति 10 लाख Tokens
प्रोव्हायडरच्या मूळ दरानुसार 0% मार्कअपसह प्रति US डॉलर ₹96 दराने रूपांतरित।
वैशिष्ट्ये
- Context विंडो
- 10,48,576 Tokens
- कमाल आउटपुट
- 65,536 Tokens
- स्वीकारतो
- टेक्स्ट, इमेजेस, PDF फाइल्स, ऑडिओ, व्हिडिओ
- Reasoning
- बाय डीफॉल्ट चालू
- Effort लेव्हल्स
- low, medium, high
- टूल वापर
- होय
- स्ट्रक्चर्ड आउटपुट
- होय
- Code एक्झिक्यूशन
- होय
- इंटेलिजन्स रँक
- 54 पैकी #12
- व्हॅल्यू रँक
- 54 पैकी #7
दरपत्रक
बेंचमार्क
रेटिंग म्हणून नमूद केलेले नसल्यास स्कोअर टक्केवारीत आहेत. सर्व बेंचमार्क स्वतंत्रपणे तपासले जातात.
95.3%
GPQA Diamond
GPQA Diamond - graduate-level science Q&A
47.8%
HLE
Humanity's Last Exam
56.6%
SciCode
SciCode - scientific code generation
81.3%
Long Context
Long Context Reasoning - reasoning over long inputs
87.6%
Terminal-Bench 2
Terminal-Bench 2.1 - agentic terminal tasks, second edition
1567
WebDev Arena
WebDev Arena - head-to-head web-app builds, Elo rating
जेमिनी 3.8 Flash विषयी
Google's latest workhorse Flash model, delivering its predecessor's speed and price with a marked step up in software engineering, agentic work and multi-step reasoning in specialised domains. It accepts text, images, audio, video and files across a million-token context, and carries three thinking levels. Google is explicit that it works harder than 3.7 Flash -- more reasoning steps and more iterative tool calls -- so it can spend more tokens on the same task, especially at higher effort.
This is the third Flash release in six weeks, and the pattern holding across all three is that the price does not move. Google calls 3.8 Flash its most intelligent workhorse model and puts it out at exactly what 3.7 Flash costs, aiming the gains at software engineering, agentic tasks and multi-step reasoning in specialised domains rather than at general chat.
Its reported results follow that aim. On DeepSWE v1.1, which measures long-horizon software engineering, Google says it outperforms most larger frontier models at autonomously solving complex engineering problems end to end, at a fraction of their cost. It reports 54.9% on HLE-Verified for multi-step reasoning across STEM, humanities and professional fields, and says it exceeds 3.7 Flash and other frontier models on the Vals Finance Agent V2 and Harvey Legal Agent benchmarks - two evaluations pointed at professional domains rather than at coding. Google also reports a significant leap in prompt-injection robustness on Gray Swan, which matters more than usual for a model this cheap to run in an agent loop.
The interesting caveat is one Google raises itself, and it is a cost caveat rather than a quality one. It says 3.8 Flash "works harder": it executes extra reasoning steps and calls tools iteratively, and it may therefore use more tokens to reach a better answer, especially at higher effort. Google's own recommendation is that if efficiency matters more than the last few points of quality, 3.7 Flash remains the model to reach for - the two are siblings on the same price sheet, not a replacement and a legacy.
The price sheet has a date on it, which is the one thing about this model most likely to catch someone out. The $0.75 input and $3.75 output rates run through 31 December 2026 and double to $1.50 and $7.50 on 1 January 2027, with context caching moving from $0.075 to $0.15 in step. That is introductory pricing, not a permanent rate.
Google shipped a second model in the same post, Gemini 3.8 Flash Cyber, its most capable cybersecurity model, aimed at vulnerability detection and automated patching and available to trusted defenders through a new Fairwind Program. That one is not served here; everything above describes the general model.
लाँचवेळी Google ने काय सांगितले
- Same price, more capability
- Google's third Flash release in six weeks holds 3.7 Flash's rates while improving software engineering, agentic work and multi-step reasoning in specialised domains.
- Long-horizon software engineering
- On DeepSWE v1.1 Google reports it outperforming most larger frontier models at solving complex engineering problems end to end autonomously, at a fraction of their cost.
- Reasoning outside code
- It reports 54.9% on HLE-Verified across STEM, humanities and professional fields, and says it exceeds 3.7 Flash and other frontier models on the Vals Finance Agent V2 and Harvey Legal Agent benchmarks.
- Harder to inject
- Google reports a significant leap in prompt-injection robustness on Gray Swan - the property that decides whether a cheap model is safe to leave running in an agent loop.
- Introductory pricing, with a date
- The $0.75 and $3.75 rates run through 31 December 2026 and double on 1 January 2027, with cached input moving from $0.075 to $0.15 at the same time.
- What it is not for
- Google says this model works harder - more reasoning steps, more iterative tool calls - and may spend more tokens for the same task at higher effort. It points at 3.7 Flash when efficiency matters more than the last few points.
भारतीय भाषा
जेमिनी 3.8 Flash हे 15 भारतीय भाषांमध्ये उत्तरे देते। मेसेज बॉक्ससमोरील मेनूमधून भाषा निवडा आणि त्याच भाषेत उत्तर मिळवा।
Frequently Asked Questions
जेमिनी 3.8 Flash बद्दल वारंवार विचारले जाणारे प्रश्न।
जेमिनी 3.8 Flash कधी लाँच झाले?
Google ने जेमिनी 3.8 Flash मॉडेल 2 सप्टें, 2026 रोजी लाँच केले.
जेमिनी 3.8 Flash ची निर्मिती कोणी केली?
जेमिनी 3.8 Flash ची निर्मिती Google ने केली आहे। 99Models प्रोव्हायडरच्या मूळ दरात थेट तिच्याशी जोडते।
जेमिनी 3.8 Flash किती कार्यक्षम आहे?
स्वतंत्र बेंचमार्क गुणांवर आधारित आमच्या बुद्धिमत्ता रँकिंगमध्ये 54 पैकी या Model चा क्रमांक 12 आहे। तिचे सर्व गुण वरील Benchmarks तक्त्यामध्ये पाहू शकता।
जेमिनी 3.8 Flash चे दर किती आहेत?
0% मार्कअपसह दर प्रति 10 लाख इनपुट Tokens साठी ₹72.00 आणि प्रति 10 लाख आउटपुट Tokens साठी ₹360.00 आहे। कोणतेही सबस्क्रिप्शन नाही; तुम्ही वापरानुसार पेमेंट करता।
जेमिनी 3.8 Flash चे अमेरिकन डॉलरमधील दर काय आहेत?
प्रोव्हायडर प्रति 10 लाख इनपुट Tokens साठी $0.75 आणि प्रति 10 लाख आउटपुट Tokens साठी $3.75 आकारतो। रुपयांचे दर प्रति अमेरिकन डॉलर ₹96 या दराने रूपांतरित केले आहेत।
जेमिनी 3.8 Flash किती मोठे संभाषण लक्षात ठेवू शकते?
याची Context विंडो 10.5 lakh Tokens आहे। एकाच विनंतीमध्ये हे Model संभाषण आणि जोडलेल्या फाइल्स मिळून एवढा एकूण मजकूर वाचू शकते।
मूल्याच्या (Value) बाबतीत जेमिनी 3.8 Flash चा क्रमांक कितवा आहे?
मूल्य रँकिंगमध्ये 54 मॉडेलपैकी हिचा क्रमांक 7 आहे। हे रँकिंग मॉडेलची बुद्धिमत्ता आणि Tokens च्या किमतीची तुलना करून ठरवले जाते।
जेमिनी 3.8 Flash उत्तर देण्यापूर्वी विचार (Reasoning) करते का?
बाय डीफॉल्ट चालू। Reasoning उपलब्ध असल्यास, तुम्ही मेसेज कंपोजरमध्ये विचार करण्याची पातळी (effort level) निवडू शकता।
जेमिनी 3.8 Flash कोणत्या भारतीय भाषांमध्ये उत्तरे देते?
हे 15 भारतीय भाषांमध्ये उत्तरे देते। मेसेज बॉक्ससमोरील मेनूमधून भाषा निवडा आणि त्याच भाषेत उत्तर मिळवा।
Google कडील इतर मॉडेल्स
कॅटलॉग अपडेट: 9 सप्टें, 2026