Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

We just cut AI spend by 75% across an entire workforce in one click. Introducing: Merge for Workforce. Without Merge, your employees are left choosing one of two options: 1. Spend 100x the cost they should be from using frontier models for everything 2. Deliver subpar work from overly... show more

Shensi Ding

7,845 subscribers

524,744 views • 1 month ago •via X (Twitter)

Science & Technology Education Finance

Anya Rossi• Live Now

Private livecam show

57 Comments

Shensi Ding1 month ago

Route every employee task to the right model automatically. Try it now:

HENRY NORRIS1 month ago

If openrouter pumped peptides and had enterprise guardrails built in 🤯

Shensi Ding1 month ago

putting this on a billboard

Turner Novak 🍌🧢1 month ago

This is what you call enabling real AI adoption

Shensi Ding1 month ago

TM

Eric Myll1 month ago

incredibly proud of the team and excited to deliver on this for our customers

Shensi Ding1 month ago

same!!!

Anuj Jhunjhunwala1 month ago

massive, massive launch!! so pumped

Shensi Ding1 month ago

lfg! means everything coming from you, go check it out and tell me what you think!

Michelle Krameisen1 month ago

Super sick! Congrats team!

Shensi Ding1 month ago

Thanks! The team crushed it.

Pritak1 month ago

Merge desktop client just landed!!

Shensi Ding1 month ago

and WE ARE HERE TO STAY

Aidan Timmerman1 month ago

What does Merge do? Merge created the AI solution every company has been asking for

Shensi Ding1 month ago

wow thats beautiful

rachel lew1 month ago

🔥🔥🔥

Shensi Ding1 month ago

lets gooo!

Merge1 month ago

another day another slay

Shensi Ding1 month ago

Is this @spacegluder lol

Merge1 month ago

@spacegluder buzhidao

Aakash Gupte1 month ago

So awesome!!!

Katie Magnuson1 month ago

Been waiting for this one!!!

Jeanelle Wu1 month ago

yay!!!! everyone has been asking for this fr

Shensi Ding1 month ago

Yesss glad we shipped it fast

Jemma Baus1 month ago

slay team this is so epic

Liam Naughton1 month ago

Let’s go! Great work team!

Shensi Ding1 month ago

:)

Harry Stebbings1 month ago

LFG! 😎

Shensi Ding1 month ago

thank you harry!!!!

Floortje dR1 month ago

Go team!!

Shensi Ding1 month ago

🤠

Nicola Morris1 month ago

HUGE launch - go team!!

Kyle1 month ago

Crazy how @merge_api made a working desktop client when @riotgames @LeagueOfLegends still hasn’t had a good one in years 🙄

Kyle1 month ago

Merge for workforce saved my life

Shensi Ding1 month ago

saved mine too tbh

Nishka Chotai1 month ago

serious gamechanger

aaron1 month ago

let's gooooo

Christian Catalini1 month ago

In case you're wondering where the economics of this lead...

Austin Lenz1 month ago

And today the game changed. Huge launch!

Thomas Johnson1 month ago

This is monumental

Amy Leung1 month ago

such an exciting launch!

Shensi Ding1 month ago

tysm!! so hyped.

Mitchell1 month ago

SHENSI DO YOU EVER NOT COOK

Shensi Ding1 month ago

IM BASICALLY GRANT ACHATZ

verrsane1 month ago

This is super awesome, love the mdm usage here. What a banger

Shensi Ding1 month ago

aw yay! it was my cofounder @GilFeig 's idea

verrsane1 month ago

@GilFeig Buddy is tapped in , we do the same here for our ai gateway stuff

Cristina Cordova1 month ago

Congrats on the launch! 🔥

Shensi Ding1 month ago

Thank you!!!! ❤️❤️🫶🫶

Dikssha Dinesh1 month ago

Let’s go team!!!

Alex Kean1 month ago

wow !

Shensi Ding1 month ago

lfg!!

Kieran Hill1 month ago

Big moves from the Merge crew 🫶

Shensi Ding1 month ago

🫶

Griffin Thompson1 month ago

man, merge saves the world yet again

Sarah Mazur1 month ago

the answer to my prayers!!! 💰📉

Shensi Ding1 month ago

we built this for you sarah

Related Videos

Launching today: the world’s first fully optimized LLM routing stack that can be embedded directly into your product, Merge Embedded Routing Stack. Model sovereignty is now table stakes for any AI product. Users and companies are demanding full control over the AI models running in your product. Right now, no company is able to do this without massive overhead. Until today. Merge makes it easy for your customers to use your product exactly the way they want to. With a single API, you can: 1. Allow customers to bring their own keys, manage their own budgets, and set policies like fallback rules, model allowlists, and more 2. Let each customer connect and switch their own models, right inside your product 3. Optimize each customer for cost, performance, or capability Without Merge, you’d be: - Building routing policies, provider integrations, and LLM key management - Giving your users zero model independence - Receiving endless customer support tickets asking “can I use 5.6 Sol?” Products that fight their customers' model strategy will lose to products that fit it. Merge is the only place that allows your users to produce the exact results they want, with the models they have access to. Give your customers the advantage, without the massive overhead costs.

Launching today: the world’s first fully optimized LLM routing stack that can be embedded directly into your product, Merge Embedded Routing Stack. Model sovereignty is now table stakes for any AI product. Users and companies are demanding full control over the AI models running in your product. Right now, no company is able to do this without massive overhead. Until today. Merge makes it easy for your customers to use your product exactly the way they want to. With a single API, you can: 1. Allow customers to bring their own keys, manage their own budgets, and set policies like fallback rules, model allowlists, and more 2. Let each customer connect and switch their own models, right inside your product 3. Optimize each customer for cost, performance, or capability Without Merge, you’d be: - Building routing policies, provider integrations, and LLM key management - Giving your users zero model independence - Receiving endless customer support tickets asking “can I use 5.6 Sol?” Products that fight their customers' model strategy will lose to products that fit it. Merge is the only place that allows your users to produce the exact results they want, with the models they have access to. Give your customers the advantage, without the massive overhead costs.

Shensi Ding

357,497 views • 2 months ago

We just built the #1 tool every AI team wants. Introducing Merge Gateway: LLM routing, fallback, cost guardrails, and security, all in one place. Everyone gets $10 free LLM usage on us to try it out. RT+ comment “Gateway” → we’ll double your credits.

We just built the #1 tool every AI team wants. Introducing Merge Gateway: LLM routing, fallback, cost guardrails, and security, all in one place. Everyone gets $10 free LLM usage on us to try it out. RT+ comment “Gateway” → we’ll double your credits.

Shensi Ding

100,476 views • 6 months ago

Introducing Helmor The open-source, local-first answer to Conductor. A more refined, faster GUI for orchestrating coding agents. No cloud. One-click import from Conductor. AI made coding faster. Helmor is about finishing the rest of the loop: orchestration, workspaces, review, testing, and merge. We believe the next generation of GUI agent orchestration should be built in the open — by the community.

Introducing Helmor The open-source, local-first answer to Conductor. A more refined, faster GUI for orchestrating coding agents. No cloud. One-click import from Conductor. AI made coding faster. Helmor is about finishing the rest of the loop: orchestration, workspaces, review, testing, and merge. We believe the next generation of GUI agent orchestration should be built in the open — by the community.

Caspian 東澔

122,987 views • 5 months ago

Introducing Merge Gateway - Build Your Own Router. You're three sprints into your coding assistant. You pick the most hyped model, integrate, test, deploy. A month later, a new model drops. Now you re-test, re-integrate, re-deploy. Your product didn't change, but the benchmark did. That's how most AI teams operate. Chasing a "best" defined by people who've never seen their product. There is no best model. There's only the right one for your product, users, and use-cases. Build Your Own Router runs on your definition of good. Pick your benchmarks, weigh them, add your own evals. Merge routes every request to your winner. 👉$100 in credits to the first 200 people that comment

Introducing Merge Gateway - Build Your Own Router. You're three sprints into your coding assistant. You pick the most hyped model, integrate, test, deploy. A month later, a new model drops. Now you re-test, re-integrate, re-deploy. Your product didn't change, but the benchmark did. That's how most AI teams operate. Chasing a "best" defined by people who've never seen their product. There is no best model. There's only the right one for your product, users, and use-cases. Build Your Own Router runs on your definition of good. Pick your benchmarks, weigh them, add your own evals. Merge routes every request to your winner. 👉$100 in credits to the first 200 people that comment

Shensi Ding

3,668,308 views • 4 months ago

Most AI tools give everyone access to the same generic models. The result? Everything looks the same. We have a different vision for AI creation. Introducing TITLES, a new creative studio built around AI models trained and owned by artists. In Studio, you can create with distinct visual perspectives developed by artists, across image and video — all in one place. This is the future we're building toward: not one model for everyone, but a growing network of unique styles you can build with — where artists get credited and paid as the work spreads. Enter Your Creative Studio:

Most AI tools give everyone access to the same generic models. The result? Everything looks the same. We have a different vision for AI creation. Introducing TITLES, a new creative studio built around AI models trained and owned by artists. In Studio, you can create with distinct visual perspectives developed by artists, across image and video — all in one place. This is the future we're building toward: not one model for everyone, but a growing network of unique styles you can build with — where artists get credited and paid as the work spreads. Enter Your Creative Studio:

TITLES

2,748,527 views • 5 months ago

Introducing Merge’s Universal Context Layer. It substantially decreases token cost while increasing accuracy. Every company uses AI wrong: Say your designer makes a deck using Claude. They teach Claude your design systems and typography. Now a Marketing hire makes a deck. None of the information your designer taught Claude gets passed over… why? Merge fixes this: All knowledge and memory across your entire company gets stored inside our context layer. When someone on the org teaches Al, that skill lives across the entire organization instead of staying locked in their session. Your AI runs faster, cheaper, and with more accuracy. You don’t have to switch systems, incur more costs, or retrain anyone on your team, Merge runs invisibly in the background. Book a demo here:

Introducing Merge’s Universal Context Layer. It substantially decreases token cost while increasing accuracy. Every company uses AI wrong: Say your designer makes a deck using Claude. They teach Claude your design systems and typography. Now a Marketing hire makes a deck. None of the information your designer taught Claude gets passed over… why? Merge fixes this: All knowledge and memory across your entire company gets stored inside our context layer. When someone on the org teaches Al, that skill lives across the entire organization instead of staying locked in their session. Your AI runs faster, cheaper, and with more accuracy. You don’t have to switch systems, incur more costs, or retrain anyone on your team, Merge runs invisibly in the background. Book a demo here:

Shensi Ding

599,942 views • 27 days ago

Excited to announce that Aamir Poonawalla and I are launching @understudylabs as part of Y Combinator 's S26 batch. We help you cut your company’s Anthropic bill by 80% with no loss of performance. Understudy is an inference cloud. We capture your AI traces, train smaller models, and automatically deploy them (only when they outperform the expensive model you are currently paying for). Instead of renting the same frontier model forever, your AI infrastructure gets cheaper and better every time it runs.

Excited to announce that Aamir Poonawalla and I are launching @understudylabs as part of Y Combinator 's S26 batch. We help you cut your company’s Anthropic bill by 80% with no loss of performance. Understudy is an inference cloud. We capture your AI traces, train smaller models, and automatically deploy them (only when they outperform the expensive model you are currently paying for). Instead of renting the same frontier model forever, your AI infrastructure gets cheaper and better every time it runs.

Luis Manrique

50,336 views • 2 months ago

Ex-JPMorgan engineer who wrote the LLM Course explained everything about fine-tuning and merging in 18 minutes - better than $2500 fine-tuning bootcamps. pick the base -> LoRA or QLoRA -> then DPO or KTO for alignment -> merge two fine-tunes into one stronger model -> ship a model that beats the base on your task. That loop is why Labonne's merges sit at the top of the Hugging Face leaderboard. LoRA + QLoRA + DPO + KTO + mergekit - that's the stack. Watch and save it, then merge your first two fine-tunes this week.

Ex-JPMorgan engineer who wrote the LLM Course explained everything about fine-tuning and merging in 18 minutes - better than $2500 fine-tuning bootcamps. pick the base -> LoRA or QLoRA -> then DPO or KTO for alignment -> merge two fine-tunes into one stronger model -> ship a model that beats the base on your task. That loop is why Labonne's merges sit at the top of the Hugging Face leaderboard. LoRA + QLoRA + DPO + KTO + mergekit - that's the stack. Watch and save it, then merge your first two fine-tunes this week.

h100envy

13,856 views • 2 months ago

AI token spend across Ramp customers is up 13x. Bills are spiking overnight and no one is noticing until the invoices hit. So our team built a solution. Now with Ramp AI Spend Intelligence, you can track your spending down to the token, team, and model, all in real time.

AI token spend across Ramp customers is up 13x. Bills are spiking overnight and no one is noticing until the invoices hit. So our team built a solution. Now with Ramp AI Spend Intelligence, you can track your spending down to the token, team, and model, all in real time.

Ramp

29,662 views • 5 months ago

Choose a model (any model) and build your application with it. Do not spend time swapping models early on. Do not try to optimize before you have a working system. This is one of the first recommendations I make to every new team I consult with. Eventually, it will be time to optimize the model. • You may need a cheaper model • You may need a faster model • You might need a smarter model Good luck if you stitched together 12 different APIs and SDKs from 7 different vendors. Over half of the companies I consult for run on Microsoft software and have access to Microsoft Foundry. Microsoft Foundry is a complete agentic ecosystem. If you're in that world and building AI applications, Microsoft Foundry is where everything lives: • Models (largest selection in the market) • Agentic SDK (Python, C#, JavaScript/TypeScript) • Tools • Evaluations • Monitoring They are fully integrated with GitHub and Visual Studio Code. The best part: Their agentic platform is fully agnostic of the models you use. You can integrate with any model using the same OpenAI-style API. Swapping one model for another takes 1 second.

Choose a model (any model) and build your application with it. Do not spend time swapping models early on. Do not try to optimize before you have a working system. This is one of the first recommendations I make to every new team I consult with. Eventually, it will be time to optimize the model. • You may need a cheaper model • You may need a faster model • You might need a smarter model Good luck if you stitched together 12 different APIs and SDKs from 7 different vendors. Over half of the companies I consult for run on Microsoft software and have access to Microsoft Foundry. Microsoft Foundry is a complete agentic ecosystem. If you're in that world and building AI applications, Microsoft Foundry is where everything lives: • Models (largest selection in the market) • Agentic SDK (Python, C#, JavaScript/TypeScript) • Tools • Evaluations • Monitoring They are fully integrated with GitHub and Visual Studio Code. The best part: Their agentic platform is fully agnostic of the models you use. You can integrate with any model using the same OpenAI-style API. Swapping one model for another takes 1 second.

Santiago

12,014 views • 7 months ago

We all know the pain of choosing the right model. You have an idea, testing it one model at a time in ten different tabs, using a spreadsheet to track usable outputs. Stop guessing and start building with Creator Central by Atlas Cloud. Model Explorer runs the same prompt across models and puts the results side by side, up to 10 at once. Start from a curated set or assemble your own. With Wan3.0 coming shortly, we're dropping the price of Seedance 2.5 so creators can compare and choose the right model for their projects. Create something now with our Generator templated workflow: Pick what you like and access the exact prompt and settings behind that result, ready for you to edit. #AIVideo #GenerativeAI #VideoProduction #Seedance #Wan3

We all know the pain of choosing the right model. You have an idea, testing it one model at a time in ten different tabs, using a spreadsheet to track usable outputs. Stop guessing and start building with Creator Central by Atlas Cloud. Model Explorer runs the same prompt across models and puts the results side by side, up to 10 at once. Start from a curated set or assemble your own. With Wan3.0 coming shortly, we're dropping the price of Seedance 2.5 so creators can compare and choose the right model for their projects. Create something now with our Generator templated workflow: Pick what you like and access the exact prompt and settings behind that result, ready for you to edit. #AIVideo #GenerativeAI #VideoProduction #Seedance #Wan3

Atlas Cloud

644,923 views • 1 month ago

For 20+ years, we've stayed ahead of every major shift in technology. Today we take the next one: we're introducing the world's first AI-native tech services model. Most of the industry is adding AI to the way it already works. Like bolting a copilot onto old processes and calling it transformation because it's faster than before. That's not what enterprises actually need. works differently. It provides instant access to AI Pods (service units run by AI agents and supervised by Globant experts) that deliver tech services at machine speed, but with the rigor, the governance, and the quality that enterprise-grade work demands. It is a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes. With organizations access AI services with transparent, output or consumption-linked pricing, not per hour or per seat, and they own everything they produce. We are bringing the speed AI promises, with the rigor and quality any business needs. Join the waitlist at

For 20+ years, we've stayed ahead of every major shift in technology. Today we take the next one: we're introducing the world's first AI-native tech services model. Most of the industry is adding AI to the way it already works. Like bolting a copilot onto old processes and calling it transformation because it's faster than before. That's not what enterprises actually need. works differently. It provides instant access to AI Pods (service units run by AI agents and supervised by Globant experts) that deliver tech services at machine speed, but with the rigor, the governance, and the quality that enterprise-grade work demands. It is a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes. With organizations access AI services with transparent, output or consumption-linked pricing, not per hour or per seat, and they own everything they produce. We are bringing the speed AI promises, with the rigor and quality any business needs. Join the waitlist at

Martin Migoya

395,548 views • 2 months ago

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

439,038 views • 2 months ago

Introducing EVO Router - a smart router that continuously optimizes and hill-climbs on your AI inference workloads. It learns from your code, prompts, production traffic, use cases, and SLAs, then searches for the best setup for every workload. That can mean more than choosing just a single model or routing through a classifier. EVO (YC F26) can optimize across model × provider combinations, fusion systems, cascades, routing policies, and prompts — whatever the workload allows, while staying within your quality, latency, and reliability constraints. As open-source models move closer to frontier-model performance, we believe this kind of workload-specific hill-climbing will become an important part of how AI systems are deployed and operated. Our early users have seen 30–60% lower inference costs across use cases ranging from complex multi-turn agents to asynchronous batch workloads. EVO Router has also reached the Pareto frontier on several benchmarks, outperforming existing setups on cost, quality, or both.

Introducing EVO Router - a smart router that continuously optimizes and hill-climbs on your AI inference workloads. It learns from your code, prompts, production traffic, use cases, and SLAs, then searches for the best setup for every workload. That can mean more than choosing just a single model or routing through a classifier. EVO (YC F26) can optimize across model × provider combinations, fusion systems, cascades, routing policies, and prompts — whatever the workload allows, while staying within your quality, latency, and reliability constraints. As open-source models move closer to frontier-model performance, we believe this kind of workload-specific hill-climbing will become an important part of how AI systems are deployed and operated. Our early users have seen 30–60% lower inference costs across use cases ranging from complex multi-turn agents to asynchronous batch workloads. EVO Router has also reached the Pareto frontier on several benchmarks, outperforming existing setups on cost, quality, or both.

Alok Bishoyi

16,103 views • 2 months ago

There is no best model. There's a lot of noise about models right now. Who is training them, who owns them, where legal intelligence should live. One question actually matters: what produces the best outcome for the legal task in front of you? That's how we decide things at Legora. We optimize for the end-to-end outcome on a legal task. The model is one layer of that system, not the system. Models are uneven and the frontier changes almost weekly. One model plans a long job well, another runs deep analysis across thousands of documents. Some have to be told exactly what to do, and some are fine with a vague brief. They all break in different ways. So our lawyers write evals and we test them with the Legora BAR, our benchmark for agentic reasoning. Every model takes every test, and the model that wins gets the work. We post-train when we know it buys our customers better performance on a specialized task. Training is a tool we reach for when it helps, nothing more than that. The intelligence that compounds sits in the orchestration layer. Precedents, review standards, client requirements. That knowledge has to stay editable, auditable and portable. In our system, a changed review standard is an edit that takes effect the same day, with no new model training required. No lawyer should have to worry about which model did the work, any more than they think about which chip is in their laptop. They should only care about the quality of the work. That's what we are focused on. If you want the engineering version of this argument rather than the CEO version, our CPO, Bryan Tsao, and CTO, Jacob Lauritzen, take it apart in the video below.

There is no best model. There's a lot of noise about models right now. Who is training them, who owns them, where legal intelligence should live. One question actually matters: what produces the best outcome for the legal task in front of you? That's how we decide things at Legora. We optimize for the end-to-end outcome on a legal task. The model is one layer of that system, not the system. Models are uneven and the frontier changes almost weekly. One model plans a long job well, another runs deep analysis across thousands of documents. Some have to be told exactly what to do, and some are fine with a vague brief. They all break in different ways. So our lawyers write evals and we test them with the Legora BAR, our benchmark for agentic reasoning. Every model takes every test, and the model that wins gets the work. We post-train when we know it buys our customers better performance on a specialized task. Training is a tool we reach for when it helps, nothing more than that. The intelligence that compounds sits in the orchestration layer. Precedents, review standards, client requirements. That knowledge has to stay editable, auditable and portable. In our system, a changed review standard is an edit that takes effect the same day, with no new model training required. No lawyer should have to worry about which model did the work, any more than they think about which chip is in their laptop. They should only care about the quality of the work. That's what we are focused on. If you want the engineering version of this argument rather than the CEO version, our CPO, Bryan Tsao, and CTO, Jacob Lauritzen, take it apart in the video below.

Max Junestrand

49,478 views • 20 days ago

Introducing Ollama fully Integrated into VSCode with CodeGPT Now you can download open-source models from ollama with a single click and install them as code assistants in VSCode. In this case, I download the qwen2:0.5b (Qwen) model in under a minute, and it becomes fully functional with just one click. The era of locally running code assistants has begun! 🚀

Introducing Ollama fully Integrated into VSCode with CodeGPT Now you can download open-source models from ollama with a single click and install them as code assistants in VSCode. In this case, I download the qwen2:0.5b (Qwen) model in under a minute, and it becomes fully functional with just one click. The era of locally running code assistants has begun! 🚀

Daniel San

101,567 views • 2 years ago

Right now, most developers are still doing the job AI should be doing. Assign a task. Wait. Review the result. Fix it. Repeat. You're not building with AI. You're babysitting it. The shift happening now is much bigger than better coding agents. It's loop engineering. Instead of managing every AI agent yourself, you build a system that manages them for you. One loop assigns the work. Another checks the output. A third retries failures. Everything keeps moving without waiting for your next prompt. Your job doesn't disappear. It changes. You stop acting like a project manager... ...and start designing the system that manages the entire team. That's exactly the transition I break down in the article below.

Right now, most developers are still doing the job AI should be doing. Assign a task. Wait. Review the result. Fix it. Repeat. You're not building with AI. You're babysitting it. The shift happening now is much bigger than better coding agents. It's loop engineering. Instead of managing every AI agent yourself, you build a system that manages them for you. One loop assigns the work. Another checks the output. A third retries failures. Everything keeps moving without waiting for your next prompt. Your job doesn't disappear. It changes. You stop acting like a project manager... ...and start designing the system that manages the entire team. That's exactly the transition I break down in the article below.

Pure

11,344 views • 2 months ago

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

129,191 views • 1 month ago

Introducing: OpenRouter for everything. One prepaid balance for every API your agents and products need. It’s the billing and metering layer every AI team needed from day one. An OpenRouter for everything. Every model call, search, scrape, or data request - one key, one balance, charged as it happens at the price you set. The markup is yours. Failed calls cost nothing. Full ledger down to the individual user. 286+ providers. 2,404+ endpoints. And now it fuels our consumer product, Locus Founder. No more juggling provider accounts, month-end invoices, or building your own usage billing system. Teams building agentic products can finally treat their API spend like any other line item: priced, capped, and billed through to their users. Comment “LOCUS” for priority early access. Book a call at

Introducing: OpenRouter for everything. One prepaid balance for every API your agents and products need. It’s the billing and metering layer every AI team needed from day one. An OpenRouter for everything. Every model call, search, scrape, or data request - one key, one balance, charged as it happens at the price you set. The markup is yours. Failed calls cost nothing. Full ledger down to the individual user. 286+ providers. 2,404+ endpoints. And now it fuels our consumer product, Locus Founder. No more juggling provider accounts, month-end invoices, or building your own usage billing system. Teams building agentic products can finally treat their API spend like any other line item: priced, capped, and billed through to their users. Comment “LOCUS” for priority early access. Book a call at

cole

76,099 views • 1 month ago

Introducing Docker 🐳 AI Models for local + private LLMs in VSCode 🤩 You can now use Docker as a local model provider in VSCode, JetBrains, Cursor, and soon Visual Studio Enterprise. With Docker Model Runner (v4.40+), run AI models locally on your machine... no data sharing, no cloud dependency 👏 Just update Docker, open CodeGPT, select the model, click "Download", and enjoy 👉 Here’s how to update Docker:

Introducing Docker 🐳 AI Models for local + private LLMs in VSCode 🤩 You can now use Docker as a local model provider in VSCode, JetBrains, Cursor, and soon Visual Studio Enterprise. With Docker Model Runner (v4.40+), run AI models locally on your machine... no data sharing, no cloud dependency 👏 Just update Docker, open CodeGPT, select the model, click "Download", and enjoy 👉 Here’s how to update Docker:

Daniel San

65,228 views • 1 year ago