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Agentic video understanding with Gemini 3.7 Flash is HUGE. Just reduced cost, less tokens, and higher accuracy. No biggie.

Shubham Saboo

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76,321 次观看 • 2 天前 •via X (Twitter)

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We’re launching agentic video understanding across our latest models: Gemini 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite! This new capability improves accuracy while cutting token consumption up to 88% and reducing costs by up to 66% for video analysis →

We’re launching agentic video understanding across our latest models: Gemini 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite! This new capability improves accuracy while cutting token consumption up to 88% and reducing costs by up to 66% for video analysis →

Google Cloud Tech

43,457 次观看 • 2 天前

Today, we’re launching Agentic Video Understanding in Gemini across 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite. 📉 ~88% fewer tokens 💰 ~66% lower cost 📈 ~7% higher accuracy The result: a new Pareto frontier for video understanding across accuracy and cost. Traditional video understanding processes video statically at a fixed sampling rate. With Agentic Video Understanding, Gemini can actively decide what to watch, at what speed, and which signals to use (frames, audio, or transcripts) by using native video tools. This enables split-second retrieval, rapid-motion understanding, and needle-in-a-haystack search across hours of video. Available now via the Gemini API - and coming soon to billions of users through the Gemini App and YouTube’s “Ask YouTube” experience. Learn more (details, demos, and docs): PMing this 0→1 has been a career highlight. Taking it from an idea and helping shape it into a frontier-defining capability we’re now shipping broadly has been incredibly rewarding. Huge thanks to Mario Lucic , Sergi Caelles Ahmet Iscen , Filip Pavetić, Suhas Yogin , JB Alayrac, Ben Caine, Nicole Brichtova, Bibo Xu , Tulsee Doshi, David Thacker, koray kavukcuoglu and the multimodal team at Google DeepMind.

Today, we’re launching Agentic Video Understanding in Gemini across 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite. 📉 ~88% fewer tokens 💰 ~66% lower cost 📈 ~7% higher accuracy The result: a new Pareto frontier for video understanding across accuracy and cost. Traditional video understanding processes video statically at a fixed sampling rate. With Agentic Video Understanding, Gemini can actively decide what to watch, at what speed, and which signals to use (frames, audio, or transcripts) by using native video tools. This enables split-second retrieval, rapid-motion understanding, and needle-in-a-haystack search across hours of video. Available now via the Gemini API - and coming soon to billions of users through the Gemini App and YouTube’s “Ask YouTube” experience. Learn more (details, demos, and docs): PMing this 0→1 has been a career highlight. Taking it from an idea and helping shape it into a frontier-defining capability we’re now shipping broadly has been incredibly rewarding. Huge thanks to Mario Lucic , Sergi Caelles Ahmet Iscen , Filip Pavetić, Suhas Yogin , JB Alayrac, Ben Caine, Nicole Brichtova, Bibo Xu , Tulsee Doshi, David Thacker, koray kavukcuoglu and the multimodal team at Google DeepMind.

Rohan Doshi

20,049 次观看 • 2 天前

We’re introducing a new capability to our latest Gemini models: agentic video understanding. This allows developers to process long-form video content with more accuracy, while using up to 88% less tokens. See how it works 🧵

We’re introducing a new capability to our latest Gemini models: agentic video understanding. This allows developers to process long-form video content with more accuracy, while using up to 88% less tokens. See how it works 🧵

Google

746,749 次观看 • 2 天前

Gemini 3.5 Flash is a step forward for Google on speed and agentic capabilities but comes at a trade-off of being higher cost than prior models We have measured up to ~280 output tokens/sec, placing it on the speed/intelligence Pareto frontier and well ahead of Gemini 3 Flash. It also shows a major uplift on agentic tasks, reaching ~1650 ELO on GDPVal-AA. The trade-off: cost is up ~5x versus Gemini 3 Flash, driven by higher token prices (3x higher than Gemini 3 Flash) and higher token usage. In this video, Declan Jackson, Member of Technical Staff at Artificial Analysis, breaks it down.

Gemini 3.5 Flash is a step forward for Google on speed and agentic capabilities but comes at a trade-off of being higher cost than prior models We have measured up to ~280 output tokens/sec, placing it on the speed/intelligence Pareto frontier and well ahead of Gemini 3 Flash. It also shows a major uplift on agentic tasks, reaching ~1650 ELO on GDPVal-AA. The trade-off: cost is up ~5x versus Gemini 3 Flash, driven by higher token prices (3x higher than Gemini 3 Flash) and higher token usage. In this video, Declan Jackson, Member of Technical Staff at Artificial Analysis, breaks it down.

Artificial Analysis

16,055 次观看 • 3 个月前

Gemini 3.7 Flash: "Play 1 round of Wordle" using my Android emulator via ADB. The latency and visual reasoning make Gemini 3.7 Flash exceptionally good for multimodal agentic use case like mobile control and Computer Use.

Gemini 3.7 Flash: "Play 1 round of Wordle" using my Android emulator via ADB. The latency and visual reasoning make Gemini 3.7 Flash exceptionally good for multimodal agentic use case like mobile control and Computer Use.

Philipp Schmid

18,290 次观看 • 17 天前

Tired of high token costs for video workflows? Agentic video understanding gives Gemini the tools to dynamically search, scan, and inspect target video segments to achieve its goal. Building on agentic vision, Gemini now actively scans visual frames, audio, and transcripts instead of ingesting video at a static 1 FPS. This reduces token consumption by up to 88%, improves accuracy, and unlocks new ways to process long-form video. Tackle complex video workflows like: ▸ Sub-second retrieval: Catch split-second cuts missed at 1 FPS ▸ Long-form search: Query multi-hour videos without overflowing context ▸ Anomaly detection: Resample interesting windows at higher FPS ▸ Counting: Accurately track repeated actions and objects over time See how agentic video understanding transforms token efficiency in Gemini 3.7 Flash when compared with static video processing:

Tired of high token costs for video workflows? Agentic video understanding gives Gemini the tools to dynamically search, scan, and inspect target video segments to achieve its goal. Building on agentic vision, Gemini now actively scans visual frames, audio, and transcripts instead of ingesting video at a static 1 FPS. This reduces token consumption by up to 88%, improves accuracy, and unlocks new ways to process long-form video. Tackle complex video workflows like: ▸ Sub-second retrieval: Catch split-second cuts missed at 1 FPS ▸ Long-form search: Query multi-hour videos without overflowing context ▸ Anomaly detection: Resample interesting windows at higher FPS ▸ Counting: Accurately track repeated actions and objects over time See how agentic video understanding transforms token efficiency in Gemini 3.7 Flash when compared with static video processing:

Google for Developers

36,917 次观看 • 2 天前

Our most intelligent workhorse model yet for coding and agents has arrived ⚡ Meet Gemini 3.7 Flash. — Crush that seemingly endless to-do list. Gemini Spark in the Google Gemini now uses 3.7 Flash. The new model can equip your personal AI agent to work even smarter for you by seamlessly handling complex, multi-step tasks across your Google Workspace apps like Gmail, Google Calendar and Google Docs — Enjoy a smoother build experience. The model thinks more diligently, putting more effort into multi-step planning and tool calls. A more disciplined execution means less manual oversight and fewer retries across engineering workflows — Build more, spend less. 3.7 Flash is available through the end of the year with an introductory price of half the original 3.6 Flash cost per million tokens ($0.75/1M input tokens and $3.75/1M output tokens)

Our most intelligent workhorse model yet for coding and agents has arrived ⚡ Meet Gemini 3.7 Flash. — Crush that seemingly endless to-do list. Gemini Spark in the Google Gemini now uses 3.7 Flash. The new model can equip your personal AI agent to work even smarter for you by seamlessly handling complex, multi-step tasks across your Google Workspace apps like Gmail, Google Calendar and Google Docs — Enjoy a smoother build experience. The model thinks more diligently, putting more effort into multi-step planning and tool calls. A more disciplined execution means less manual oversight and fewer retries across engineering workflows — Build more, spend less. 3.7 Flash is available through the end of the year with an introductory price of half the original 3.6 Flash cost per million tokens ($0.75/1M input tokens and $3.75/1M output tokens)

Google AI

127,622 次观看 • 21 天前

3.7 Flash brings a big jump in agentic performance and coding accuracy. To demonstrate, we set up a 3-agent team to autonomously train a robotics control model from scratch. We hope you like 3.7 Flash, and you can read more here:

3.7 Flash brings a big jump in agentic performance and coding accuracy. To demonstrate, we set up a 3-agent team to autonomously train a robotics control model from scratch. We hope you like 3.7 Flash, and you can read more here:

koray kavukcuoglu

74,027 次观看 • 21 天前

Today we're introducing Gemini 3.7 Flash, our most intelligent workhorse model yet for coding and agents. This model brings substantial gains across software engineering, web development, and complex knowledge work. Now through the end of the year, Gemini 3.7 Flash is available at an introductory price* of $0.75/1M input and $3.75/1M output tokens — making it easier and more cost-effective for developers and customers to scale production-ready agents.

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Google

1,174,864 次观看 • 21 天前

Today, we're introducing not one but TWO new models, striking the balance between efficiency and quality to enable you to build production AI agents. — Gemini 3.6 Flash: Addresses efficiency feedback we received from Gemini 3.5 Flash with upgrades in coding, knowledge work, and multimodal tasks faster, more accurately, and with substantially fewer tokens per task — Gemini 3.5 Flash-Lite: Our fastest, most cost-effective 3.5-class model yet built for agentic workflows, hitting ~350 output tokens/sec with improved coding and overall quality Start building with these today via the Gemini API in Google AI Studio or try them out in the Google Gemini

Today, we're introducing not one but TWO new models, striking the balance between efficiency and quality to enable you to build production AI agents. — Gemini 3.6 Flash: Addresses efficiency feedback we received from Gemini 3.5 Flash with upgrades in coding, knowledge work, and multimodal tasks faster, more accurately, and with substantially fewer tokens per task — Gemini 3.5 Flash-Lite: Our fastest, most cost-effective 3.5-class model yet built for agentic workflows, hitting ~350 output tokens/sec with improved coding and overall quality Start building with these today via the Gemini API in Google AI Studio or try them out in the Google Gemini

Google AI

437,800 次观看 • 1 个月前

We’re expanding the Gemini 3 family with the launch of Gemini 3 Flash. This model: — Combines Gemini 3’s Pro-grade reasoning with Flash-level latency, efficiency, and cost — Delivers frontier-level performance on PHD-level reasoning and knowledge benchmarks — Is our most impressive model for agentic workflows Watch Gemini 3 Flash handle hundreds of function calling options at low latency, compiling global recipes from 100 ingredients and 100 kitchen tools.

We’re expanding the Gemini 3 family with the launch of Gemini 3 Flash. This model: — Combines Gemini 3’s Pro-grade reasoning with Flash-level latency, efficiency, and cost — Delivers frontier-level performance on PHD-level reasoning and knowledge benchmarks — Is our most impressive model for agentic workflows Watch Gemini 3 Flash handle hundreds of function calling options at low latency, compiling global recipes from 100 ingredients and 100 kitchen tools.

Google AI

229,722 次观看 • 8 个月前

Our new Gemini 3.5 Flash is our strongest agentic and coding model yet, delivering frontier-level performance at 4x the speed of comparable frontier models at less than half the cost. We had Tulsee Doshi break down what you need to know about it.

Our new Gemini 3.5 Flash is our strongest agentic and coding model yet, delivering frontier-level performance at 4x the speed of comparable frontier models at less than half the cost. We had Tulsee Doshi break down what you need to know about it.

Google

77,764 次观看 • 3 个月前

We’re introducing Gemini 3.8 Flash ⚡️ built to tackle complex agentic and multi-step tasks with even greater diligence. Our most intelligent workhorse model yet delivers significant improvements in reasoning, evolving to an AI partner that doesn’t just write code, but can also navigate complex projects. While solving ambiguous and high-friction tasks is immensely helpful, it can also be expensive. Fortunately, 3.8 Flash features the usual effort controls, ensuring that the amount of thinking required to accomplish the task at hand is proportional to the tokens spent. Watch Gemini 3.8 Flash combine native video understanding with advanced coding to autonomously build this 3D game, play it to find errors, and execute code changes in a seamless agentic loop in Google Antigravity.

We’re introducing Gemini 3.8 Flash ⚡️ built to tackle complex agentic and multi-step tasks with even greater diligence. Our most intelligent workhorse model yet delivers significant improvements in reasoning, evolving to an AI partner that doesn’t just write code, but can also navigate complex projects. While solving ambiguous and high-friction tasks is immensely helpful, it can also be expensive. Fortunately, 3.8 Flash features the usual effort controls, ensuring that the amount of thinking required to accomplish the task at hand is proportional to the tokens spent. Watch Gemini 3.8 Flash combine native video understanding with advanced coding to autonomously build this 3D game, play it to find errors, and execute code changes in a seamless agentic loop in Google Antigravity.

Google AI

175,385 次观看 • 1 天前

With upgraded design adherence and web dev capabilities, your prompts now have more room to play with Gemini 3.7 Flash. Our team used 3.7 Flash to one-shot this playable game in Google Google Antigravity 👾

With upgraded design adherence and web dev capabilities, your prompts now have more room to play with Gemini 3.7 Flash. Our team used 3.7 Flash to one-shot this playable game in Google Google Antigravity 👾

Google

315,869 次观看 • 20 天前

I asked Gemini 3.7 Flash to write prompts for modern web UI video backgrounds (great challenge to see the creativity of any model) and I really love the resulting aeshetics, rendered with Gemini Omni Flash. Some of the prompts I liked best below - which one is your favourite?

I asked Gemini 3.7 Flash to write prompts for modern web UI video backgrounds (great challenge to see the creativity of any model) and I really love the resulting aeshetics, rendered with Gemini Omni Flash. Some of the prompts I liked best below - which one is your favourite?

genevieveh@

70,470 次观看 • 18 天前

Optimized for high-volume workloads, Gemini 3.5 Flash-Lite is now available for agentic Android development. 😎 This is one of our fastest, most cost-efficient models yet. Start building through the Gemini API in Android Studio →

Optimized for high-volume workloads, Gemini 3.5 Flash-Lite is now available for agentic Android development. 😎 This is one of our fastest, most cost-efficient models yet. Start building through the Gemini API in Android Studio →

Android Developers

29,093 次观看 • 1 个月前

glm 5.3 vs qwen 3.8 vs gemini 3.7 vs deepseek v4 flash four models designed and built three structures each on a physics-backed site, with no dimensions anywhere in the brief the setup: our own agent loop on OpenRouter, a construction site as the tool set – footings, walls, arches, roofs, scaffold, a lamp. the site enforces physics and nothing else: unsupported brick falls, a roof needs walls under it, a worker reaches 3.2 m above whatever he stands on, an arch needs centring until the keystone is set, concrete cures before it carries. no budget ceiling – material cost is tallied and reported, never blocked. tasks: 1. house – a plot and a palette, no plan. shape, height and material are the model's call 2. lighthouse – a headland cut by a gully, with a rock stack standing 30 m offshore. the lamp must burn, it must be the highest thing built, and the keeper must be able to walk to it 3. bridge – a river with one islet and banks at different heights. cross it however you want models: Z.ai glm 5.3 flash, Qwen qwen 3.8 flash, Google DeepMind gemini 3.7 flash, DeepSeek v4 flash vision all twelve objects were finished and signed off by the models themselves. tallest lighthouse is qwen's at 38.4 m, planted on the offshore stack with a bridge run out to it – the only model that read the site that way. deepseek signed off its bridge on an empty riverbed: 0 bricks, 107 minutes, $1.16m of material tallied - total cost, three builds #1 glm 5.3 flash – $0.201 #2 gemini 3.7 flash – $0.871 #3 qwen 3.8 flash – $1.058 #4 deepseek v4 flash – $1.567 - wall clock, three builds #1 gemini 3.7 flash – 91m #2 glm 5.3 flash – 228m #3 deepseek v4 flash – 502m #4 qwen 3.8 flash – 912m - total tokens #1 gemini 3.7 flash – 3,567,052 #2 glm 5.3 flash – 4,732,748 #3 qwen 3.8 flash – 13,469,333 #4 deepseek v4 flash – 18,230,076 - defects logged by the site #1 deepseek v4 flash – 59 #2 gemini 3.7 flash – 132 #3 glm 5.3 flash – 221 #4 qwen 3.8 flash – 350 - material tallied across three builds #1 gemini 3.7 flash – $359,884 #2 glm 5.3 flash – $583,358 #3 deepseek v4 flash – $1,327,484 #4 qwen 3.8 flash – $2,188,625 observations: • glm is the cheap one and nothing here is close – $0.201 for three buildings, $0.042 per million tokens, 6x under gemini's rate • what glm spends it on is bulk, not care: 166,228 bricks in one house and 156 defect weight, the worst single object in the set • gemini is the efficiency line – 91 minutes and 3.57m tokens for all three and an eighth of qwen's clock • gemini also builds the smallest of everything. its lighthouse is 22.5 m against qwen's 38.4, its house 6.9 m against 19.3 • qwen is the maximalist: 1.18m bricks, $2.19m of material, tallest on all three tasks, and 912 minutes – 15 hours – to get there conclusion: twelve finished objects for $3.80 all in, and a 7.8x price spread between the cheapest model and the priciest! follow thehype. for 24/7 ai news, analysis and breakdowns

glm 5.3 vs qwen 3.8 vs gemini 3.7 vs deepseek v4 flash four models designed and built three structures each on a physics-backed site, with no dimensions anywhere in the brief the setup: our own agent loop on OpenRouter, a construction site as the tool set – footings, walls, arches, roofs, scaffold, a lamp. the site enforces physics and nothing else: unsupported brick falls, a roof needs walls under it, a worker reaches 3.2 m above whatever he stands on, an arch needs centring until the keystone is set, concrete cures before it carries. no budget ceiling – material cost is tallied and reported, never blocked. tasks: 1. house – a plot and a palette, no plan. shape, height and material are the model's call 2. lighthouse – a headland cut by a gully, with a rock stack standing 30 m offshore. the lamp must burn, it must be the highest thing built, and the keeper must be able to walk to it 3. bridge – a river with one islet and banks at different heights. cross it however you want models: Z.ai glm 5.3 flash, Qwen qwen 3.8 flash, Google DeepMind gemini 3.7 flash, DeepSeek v4 flash vision all twelve objects were finished and signed off by the models themselves. tallest lighthouse is qwen's at 38.4 m, planted on the offshore stack with a bridge run out to it – the only model that read the site that way. deepseek signed off its bridge on an empty riverbed: 0 bricks, 107 minutes, $1.16m of material tallied - total cost, three builds #1 glm 5.3 flash – $0.201 #2 gemini 3.7 flash – $0.871 #3 qwen 3.8 flash – $1.058 #4 deepseek v4 flash – $1.567 - wall clock, three builds #1 gemini 3.7 flash – 91m #2 glm 5.3 flash – 228m #3 deepseek v4 flash – 502m #4 qwen 3.8 flash – 912m - total tokens #1 gemini 3.7 flash – 3,567,052 #2 glm 5.3 flash – 4,732,748 #3 qwen 3.8 flash – 13,469,333 #4 deepseek v4 flash – 18,230,076 - defects logged by the site #1 deepseek v4 flash – 59 #2 gemini 3.7 flash – 132 #3 glm 5.3 flash – 221 #4 qwen 3.8 flash – 350 - material tallied across three builds #1 gemini 3.7 flash – $359,884 #2 glm 5.3 flash – $583,358 #3 deepseek v4 flash – $1,327,484 #4 qwen 3.8 flash – $2,188,625 observations: • glm is the cheap one and nothing here is close – $0.201 for three buildings, $0.042 per million tokens, 6x under gemini's rate • what glm spends it on is bulk, not care: 166,228 bricks in one house and 156 defect weight, the worst single object in the set • gemini is the efficiency line – 91 minutes and 3.57m tokens for all three and an eighth of qwen's clock • gemini also builds the smallest of everything. its lighthouse is 22.5 m against qwen's 38.4, its house 6.9 m against 19.3 • qwen is the maximalist: 1.18m bricks, $2.19m of material, tallest on all three tasks, and 912 minutes – 15 hours – to get there conclusion: twelve finished objects for $3.80 all in, and a 7.8x price spread between the cheapest model and the priciest! follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

23,951 次观看 • 6 天前

Gemini 3.1 Flash Live just dropped and it's available with LiveKit today. This is the first Gemini 3 native audio model on the Live API. Better instruction following, improved tool calling, reduced speaker drift, and support for 70+ languages. Audio in, audio out. No text conversion in between.

Gemini 3.1 Flash Live just dropped and it's available with LiveKit today. This is the first Gemini 3 native audio model on the Live API. Better instruction following, improved tool calling, reduced speaker drift, and support for 70+ languages. Audio in, audio out. No text conversion in between.

LiveKit

40,277 次观看 • 5 个月前

Gemini Spark now runs on Gemini 3.7 Flash.⚡️ Whether you’re using Spark to compile vendors into Sheets or draft negotiation emails, 3.7 Flash makes your personal AI agent more precise and accurate with improved tool use for Google Workspace apps to help turn ideas into action.

Gemini Spark now runs on Gemini 3.7 Flash.⚡️ Whether you’re using Spark to compile vendors into Sheets or draft negotiation emails, 3.7 Flash makes your personal AI agent more precise and accurate with improved tool use for Google Workspace apps to help turn ideas into action.

Google Gemini

544,645 次观看 • 21 天前

Audio Transcription with Google Gemini 1.5 Flash In this video, Gemini-Flash was able to transcribe 13 minutes of audio in 50-60 seconds. I have tested this with multiple audio files, and the transcription accuracy is close to 99%. If the audio is clear, you get 100% correct transcription. Even if the audio is really bad with a lot of noise, you still get around 95-96% accuracy. The code for this is available on GitHub. If you're interested, you can download and run it. You just need a Google API key.

Audio Transcription with Google Gemini 1.5 Flash In this video, Gemini-Flash was able to transcribe 13 minutes of audio in 50-60 seconds. I have tested this with multiple audio files, and the transcription accuracy is close to 99%. If the audio is clear, you get 100% correct transcription. Even if the audio is really bad with a lot of noise, you still get around 95-96% accuracy. The code for this is available on GitHub. If you're interested, you can download and run it. You just need a Google API key.

AshutoshShrivastava

122,990 次观看 • 1 年前