🍀green field💚🍀

[MERA DEFI @meradefi]

The next internet won’t just be connected it will be intelligent.

@FastXNetwork is building the intelligent layer that connects AI, data, & Web3 into a system designed to understand,decide, & execute.

This is bigger than an AI project.

For more details https://t.co/LFQ9RrlcxH

[Abdulsalam @Prof_Abdulsalam]

If you’re hearing about @axisrobotics for the first time and wondering where to start, here’s the simple version.

Axis is building infrastructure for Physical AI by turning human interaction with simulated robots into useful training data.

You don’t need a physical robot or a GPU to begin.

Here’s the starting process 👇

→ 1. Create your account
Open Axis Hub through the link below
https://t.co/xoCnu3FR6X
and sign in with Privy using email, Google, X, or a wallet.

→ 2. Find an available task
Look through the Hub and check the remaining slots. Start with a task you can understand rather than jumping straight into the hardest ones.

→ 3. Run the robot
In Pre-training, you control the simulated robot and complete the task yourself. Your successful run becomes a training demonstration.

→ 4. Try Post-training
This is where it gets more interesting. The trained policy attempts the task, and you step in only when it starts going wrong. Your correction becomes data for improving the next iteration.

→ 5. Sign your completed run
Finishing the task isn't the final step. After Axis verifies your trajectory, sign it on-chain so the contribution becomes verifiable and counts.

→ 6. Build quality, not just volume
Axis looks at more than how many tasks you complete. Quality, difficulty and diversity matter, so I’d rather build a strong history across different tasks than repeatedly farm the easiest ones.

What I like about this model is the feedback loop:

Human → Robot → Data → Better Policy → Human Correction → Better Data

You’re not just clicking through a campaign.

You’re contributing examples of how robots should behave, and the system uses those examples to improve the policy.

If you’re new, this is probably the easiest place to start:

Give it a try and see how far you can take your first contribution.

[LửaCrypt 🧧 @LuaCrypt]

The part of this that matters most isn’t that gold protected purchasing power.

It’s that for centuries, gold holders had to accept one trade-off: you owned the asset, but your capital sat idle.

@stakemygold is attacking that exact weakness.
Gold preserved value.
Now it can generate yield. Up to 12% APR.
https://t.co/OUTDP5jVlc

[Essays Hub @Arielessayshelp]

$SUN trading volume just surged +30.08% in 24 hours.

The latest data puts $SUN’s 24H trading volume at $18.29M, showing a sharp increase in activity across the ecosystem.

But volume is more than just a number to watch.

Higher trading activity can mean more capital is moving through the protocol, which can contribute to stronger liquidity and greater fee generation when the activity is sustained.

Think of it as a simple DeFi flywheel:

→ More trading activity
→ More liquidity utilization
→ More protocol fees
→ Stronger economic activity across the ecosystem

The key is whether this momentum continues.

A single 24H spike is interesting. Sustained volume growth is where things become much more meaningful.

For $SUN, the current snapshot shows that on-chain activity is picking up.

$18.29M volume. +30.08% in 24H.

Worth watching what comes next.

Data as of Sept. 2, 13:00 SGT.

#TRONEcoStar
@justinsuntron
@BAI_AGI

[SAVVY @techsavvyy02]

CT has made people money.

It has also created plenty of exit liquidity 😅

So where’s the line between real alpha and timeline noise?

That’s the conversation this Saturday with @NewSightHQ.

2 PM UTC. Set your reminder👇🏽

[modern day woman 📿 @Udoh_Graceee]

The first world I explored in the @EvolveTKN Metaverse was Elysium, and that was enough to make me want to look beyond just one world.

So I went back in and picked another one this time: 𝘼𝙩𝙡𝙖𝙣𝙩𝙞𝙨.

Atlantis takes a completely different direction. Instead of building your life in a futuristic civilisation like Elysium, you’re going underwater, exploring a lost civilisation with deep-sea environments, submarine routes and ancient ruins waiting to be discovered.

But after spending some time looking through Atlantis, the part that really interests me is that the environment itself is becoming part of the experience.

EVOP has introduced Environmental Milestones, with the entire Atlantis community working toward eight server-wide goals around restoring coral ecosystems, reducing ocean pollution, increasing biodiversity, improving water quality and rebuilding species populations.

And these aren’t just progress bars sitting somewhere in the background.

Atlantis now has an Ocean Health Index that tracks the condition of the environment across five different metrics.

The state of that environment can actually affect what happens during exploration, higher pollution can reduce expedition rewards, while healthier ecosystems can make Atlantis more rewarding to explore.

I like this approach because it gives the world a reason to keep changing.

You’re not just entering Atlantis to look around. You can take part in restoration, respond to environmental events, work toward community goals and earn rewards as milestones are reached.

And it makes the idea of exploration feel a little different.

Imagine going into the same world at different points and finding that the condition of the ocean has changed because of what the community has collectively done.

That’s what I’m interested in exploring next with Atlantis.

Elysium felt like a world where you build your citizen and shape their story.

Atlantis feels like a world where the environment itself becomes part of the story.

And one thing is for sure, I love both,

Try the metaverse here
https://t.co/53VMetdh0f

[Cletus Elijah @cletusEllijah]

Imagine seeing people collect Apple stock every day from simply holding $IPOD while you kept scrolling past it.

Over $6K in $AAPLc has already gone to holders since yesterday.

➘ No staking. No claiming. Just hold.

Missing this one because you “wanted to check it later” would be a pretty painful excuse.

[Essays Hub @Arielessayshelp]

50% off peak pricing. 75% off peak rates. https://t.co/e3CtBGKX7Z is making DeepSeek-V4-Flash more affordable for developers running frequent AI workloads.

But the bigger lesson is how AI model pricing affects the cost of building and scaling applications.

Here’s how to understand the update.

1. Understand the discount

https://t.co/e3CtBGKX7Z now offers an extra 50% off DeepSeek’s official pricing for DeepSeek-V4-Flash and DeepSeek-V4-Flash-Vision-Exp.

→ Peak: Mon–Fri, 09:00–12:00 and 14:00–18:00 SGT — 50% off official rates
→ Off-peak: Other weekday hours and full weekends — 75% off official peak rates

So the cost of running workloads can depend on when those requests are made.

2. Why timing matters

For applications making thousands of API calls, lower-cost periods can help reduce operating expenses.

This can be useful for:

→ Batch processing
→ Background Agent tasks
→ Scheduled analysis
→ Coding workflows
→ Large-scale API testing

Not every workload can be shifted to off-peak periods, but when it can, timing becomes part of cost optimization.

3. Free alternatives remain available

https://t.co/e3CtBGKX7Z says GLM-5.3-Flash, Qwen3.8-Flash, Hy3, and MiMo V2.5 remain completely free.

This gives developers room to experiment without immediately paying for every workload.

A practical approach is:

→ Start with a free model
→ Compare its performance
→ Identify tasks that need stronger capabilities
→ Use premium models where they provide meaningful value

4. Choose based on the workload

Instead of asking only, “Which model is cheapest?”

Ask:

What am I building, and how often will it call the model?

Consider:

→ Performance
→ API frequency
→ Context requirements
→ Reliability
→ Total operating cost

The best model is not necessarily the most expensive.

It is the one that delivers the right performance at the right cost.

5. The bigger picture

AI infrastructure is becoming more competitive, and pricing is becoming an important part of that equation.

https://t.co/e3CtBGKX7Z’s DeepSeek discount gives developers another way to access powerful models while keeping high-frequency workloads more cost-efficient.

The real question isn’t just what a model costs per request.

It’s how much value that request delivers at scale.

Would you prioritize lower cost, stronger performance, or free access when choosing an AI model?

@BAI_AGI #TRONEcoStar @justinsuntron

[Essays Hub @Arielessayshelp]

2,300,027 users. But the bigger story is what https://t.co/e3CtBGKX7Z is building behind that number.

https://t.co/e3CtBGKX7Z has surpassed 2.3 million cumulative users, offering a useful way to understand how AI infrastructure is evolving.

The important question is not just how many people are using an AI platform.

It is how that platform makes intelligence easier to access, more efficient to use, and more useful in real-world applications.

Here’s how to read the milestone.

1. Look beyond user counts

User growth is an important adoption signal, but it does not tell you how much AI work is being performed.

That is why it helps to look at:

→ Users: How many people are accessing the platform?
→ Token throughput: How much AI-generated text is being processed?
→ API calls: How frequently are applications interacting with the infrastructure?
→ Workloads: Are users experimenting, coding, or running production applications?

Together, these metrics provide a more complete picture of adoption.

2. Why cost efficiency matters

https://t.co/e3CtBGKX7Z says it is continuously optimizing computing costs to make advanced intelligence more accessible.

A powerful model still needs to be affordable enough for developers to use.

That means considering:

→ Cost per request
→ Frequency of usage
→ Pricing for the application
→ Infrastructure capacity

Better cost efficiency can make it easier for more developers to experiment, build, and scale.

3. The value of model aggregation

https://t.co/e3CtBGKX7Z aggregates frontier large models and uses intelligent routing to enable more efficient computing power invocation.

The practical idea is simple:

Different models can be better suited to different tasks.

A developer may need one model for coding, another for reasoning, and another for a specific production workflow.

Bringing these options together makes model selection and invocation more practical.

4. Why production infrastructure matters

AI infrastructure becomes more important when usage moves beyond occasional prompts.

For example:

→ A developer testing a new application
→ An agent handling a multi-step task
→ A production API serving repeated requests
→ A business integrating AI into daily operations

These workloads require more than model access.

They require infrastructure that can support scalability, reliability, and efficient usage.

5. Where Agents and payments fit in

https://t.co/e3CtBGKX7Z also highlights its LLM Services, BAIclaw, MCP, and Agent payments.

This matters because the AI ecosystem is moving beyond simple model interactions.

The broader workflow increasingly looks like:

Model invocation → Agent execution → Value settlement

A model generates an output.

An Agent uses that output to perform a task.

And the infrastructure needs to support how that activity is measured and paid for.

That is where routing, metering, and settlement become increasingly relevant.

6. The bigger picture

https://t.co/e3CtBGKX7Z’s 2.3 million user milestone is not just about growth.

It is also a reminder that AI infrastructure is becoming a larger part of how people access and use intelligence.

The long-term opportunity is to make advanced models accessible, efficient, scalable, and useful across real-world applications.

https://t.co/e3CtBGKX7Z describes its direction as:

“Above all models, beneath all Agents.”

That is a useful way to think about the infrastructure layer connecting model capabilities with the applications and workflows that depend on them.

The number to watch is not just how many users an AI platform has.

It is also how much useful work those users can accomplish through the infrastructure.

What matters more when evaluating an AI platform: user growth, cost efficiency, or the ability to support production workloads?

@justinsuntron #TRONEcoStar @BAI_AGI

[Rahmer @Rahmerhb]

Even if I tried to quit, the request would be 𝗿𝗲𝗷𝗲𝗰𝘁𝗲𝗱, 𝗱𝗲𝗻𝗶𝗲𝗱 𝗮𝗻𝗱 𝗱𝗲𝗰𝗹𝗶𝗻𝗲𝗱.

Leaving a regular casino might be possible.

Leaving @1win, the #1 crypto gaming casino, is 𝗶𝗺𝗽𝗼𝘀𝘀𝗶𝗯𝗹𝗲.

[BheeCrush | Web3 Content @bheecrush]

I joined @1win through their markets. Prediction markets and crypto is my thing, so that was the natural entry point for me.

What I didn't expect was how deep the rest of it goes

The Sportsbook pulled me in during a Champions League week I only meant to check once. Now it's part of the routine.

Betwave is a different kind of interesting. Actual athletes giving reads in their own sport.

The casino side is its own rabbit hole. Thousands of titles, some exclusive to 1win users, and those multiplier games always pull you back in.

The VIP Club ties it all together..
It's not just perks, it's the same circle as athletes and public figures, with real moments around things like UFC and the World Cup.

I came for Markets. I stayed for everything built around it.

[Essays Hub @Arielessayshelp]

AI can become more intelligent.

But if accessing that intelligence remains complicated, adoption will always have a ceiling.

Here’s how @AINFTcom makes the payment side simpler by bringing Web2 and Web3 funding options into one ecosystem.

𝗪𝗲𝗯𝟮 𝗣𝗮𝘆𝗺𝗲𝗻𝘁 𝗥𝗮𝗶𝗹𝘀

① WeChat Pay
② Alipay
③ UnionPay
④ Visa
⑤ Mastercard
⑥ Google Pay
⑦ Apple Pay

For users who prefer crypto, AINFT supports multiple blockchains and a wide range of assets.

□ 𝗧𝗥𝗢𝗡 𝗡𝗲𝘁𝘄𝗼𝗿𝗸

TRX | USDT | USDD | USD1 | WBTC | HTX | NFT

□ 𝗕𝗡𝗕 𝗖𝗵𝗮𝗶𝗻

BNB | USDT | USDC | USDD | U | HTX

□ 𝗘𝘁𝗵𝗲𝗿𝗲𝘂𝗺

ETH | TRX | USDT | USDC | USDD | WBTC | HTX

□ 𝗕𝗮𝘀𝗲

ETH | USDC

□ 𝗔𝗿𝗯𝗶𝘁𝗿𝘂𝗺

ETH | USDT | USDC | ARB

□ 𝗢𝗽𝘁𝗶𝗺𝗶𝘀𝗺

ETH | USDT | USDC | OP

□ 𝗣𝗼𝗹𝘆𝗴𝗼𝗻

USDT | USDC | POL

□ 𝗦𝗼𝗹𝗮𝗻𝗮

SOL | USDT | USDC | WBTC

The interesting part is that AINFT is not just supporting multiple payment methods.

There are also incentives attached to funding your account.

𝗕𝗡𝗕 𝗖𝗵𝗮𝗶𝗻 𝗨𝘀𝗲𝗿𝘀 𝗚𝗲𝘁 𝗮 𝟱𝟬% 𝗕𝗼𝗻𝘂𝘀

For a limited time, deposits through BNB Chain can receive an extra 50% bonus.

Deposit at least $10 through BNB Chain and you can unlock a $5 BNB official subsidy.

It is first-come, first-served, so the incentive is subject to availability.

There is also a broader top-up incentive offering a 1:0.5 bonus on deposits, capped at $100 in bonus credits per user.

𝗛𝗼𝘄 𝗜𝘁 𝗪𝗼𝗿𝗸𝘀

01 — Log in or create an AINFT account.

02 — Open the Purchase page.

03 — Choose Web2 or Web3 as your payment route.

04 — For Web3, select the blockchain you want to use.

05 — Choose a supported token.

06 — Complete the deposit.

07 — Your account receives the corresponding credits.

08 — Use those credits to access the AI models available on AINFT.

This is where the payment layer becomes important.

AI platforms can have powerful models, but accessibility depends on the infrastructure around those models.

Multiple payment rails remove one of the biggest barriers: forcing every user into the same way of paying.

Cards, mobile payments, stablecoins and crypto assets can all become different entry points into the same AI ecosystem.

And right now, BNB Chain users have an additional reason to look at the funding options carefully:

𝗗𝗲𝗽𝗼𝘀𝗶𝘁 $𝟭𝟬+ 𝘃𝗶𝗮 𝗕𝗡𝗕 𝗖𝗵𝗮𝗶𝗻 → 𝗚𝗲𝘁 𝗮 𝟱𝟬% 𝗕𝗼𝗻𝘂𝘀 𝗶𝗻𝗰𝗲𝗻𝘁𝗶𝘃𝗲

That makes the payment layer just as interesting as the AI layer.

@AINFTcom @justinsuntron #TRONEcoStar

[AJDominic 🐂🀄️ @A_J_Dominic]

one thing about stocks that felt strange to me was the clock.

You see something happen on a saturday. maybe a company news changes something in the market, or you simply want to act on a move you’ve been watching closely, but the market is closed…so you wait.

by the time monday comes around, you’re dealing with a completely different situation.

that’s a time wall blocking you from a lifetime opportunity.

Mexc stock products trade everyday, even on weekends, (except for RealStocks). you’re not restricted to the traditional market schedule when trading stocks.

@Mexc gives you more room to decide when you want to participate and how you want to trade.

in this way, if the market is moving, you can actually respond to it. #MEXC

[Mayor Fae 🦅 @Mayorfae_]

One of the things I value most about blockchain isn’t just the price charts.

It’s the visibility.
Transactions, wallet activity, token movements and liquidity can be tracked on-chain without having to rely entirely on someone’s report. That level of transparency matters even more when you’re dealing with real-world assets.

For something like @BiGODToken, where gold-backed value is part of the bigger picture, being able to verify and follow ecosystem activity adds another layer of confidence.

The future of finance shouldn’t just be digital, it should be open, trackable and accessible.

That’s where blockchain really starts to make sense to me.

#BIGOD #RWA

[Debbee 🔱 @Queen_Debbee]

Honestly, simpler rules just make sense.

You shouldn’t need to spend more time trying to understand restrictions than actually focusing on your trading.

Glad to see @AifoFunding listening to trader feedback.

[Mayor Fae 🦅 @Mayorfae_]

Most people think of gold as something you buy, hold, and leave there. @BiGODToken is taking that idea a step further.

Through staking, $BIGOD holders have another way to participate in the ecosystem while putting their holdings to work and earning staking rewards. That’s an interesting part of the GoldFi concept for me.

You have an asset built around gold-backed value, but you’re not limited to simply watching its price move. There’s room for participation, utility and rewards around the same ecosystem. Gold has always been good at preserving value.

Blockchain makes it possible to explore what else that value can do, that combination is what makes @BiGODToken worth watching.

#BIGOD

[Mayor Fae 🦅 @Mayorfae_]

There are thousands of tokens in crypto.

So what actually makes one worth paying attention to?

For me, it comes down to what sits behind the token. @BiGODToken takes a different route by connecting blockchain with physical gold-backed value. Gold brings the history and real-world foundation.

Blockchain brings accessibility, transparency and digital utility, that combination is what makes @BiGODToken interesting to me.

It’s not trying to create value from nothing, It’s taking something people already understand and giving it a new way to exist, move and participate in the digital economy.

Gold-backed. On-chain. Built for GoldFi.

#BIGOD #RWA

[_CryptoWave @CryptoWave2025]

Gold has been trusted for thousands of years.

What’s changing is not the value of gold it’s how we access, move, and use that value.

That’s where @BiGODToken comes in.

BIGOD is bringing physical gold into the digital economy through GoldFi, connecting a traditional store of value with blockchain infrastructure.

The bigger idea goes beyond simply putting gold on-chain.

It’s about creating a more accessible way to interact with gold while bringing transparency, digital ownership, and on-chain settlement into the equation.

With each $BIGOD token backed by physical gold, the focus remains on the asset behind the token.

Gold first. Token second.

As the RWA sector continues moving from narrative to real-world adoption, assets like gold are naturally becoming part of that transition.

BIGOD is building at that intersection — where centuries-old trust meets modern blockchain infrastructure.

The future of RWA won’t only be about tokenizing assets.

It will be about making real-world value more accessible, transparent, and usable on-chain.

That’s the GoldFi thesis.

Trust Digital Gold.
Gold First. Token Second.
#BigodInvest

[Essays Hub @Arielessayshelp]

𝗛𝗲𝗿𝗲’𝘀 𝗵𝗼𝘄 𝗔𝗜𝗡𝗙𝗧𝗰𝗼𝗺 𝗶𝘀 𝗺𝗮𝗸𝗶𝗻𝗴 𝗺𝘂𝗹𝘁𝗶-𝗺𝗼𝗱𝗲𝗹 𝗔𝗜 𝗮𝗰𝗰𝗲𝘀𝘀 𝗺𝘂𝗰𝗵 𝗺𝗼𝗿𝗲 𝘀𝗶𝗺𝗽𝗹𝗲.

𝗔𝗜𝗡𝗙𝗧 𝗰𝘂𝗿𝗿𝗲𝗻𝘁𝗹𝘆 𝗹𝗶𝘀𝘁𝘀 𝟰𝟳 𝗔𝗜 𝗺𝗼𝗱𝗲𝗹𝘀 𝗳𝗿𝗼𝗺 𝟵 𝗔𝗜 𝗽𝗿𝗼𝘃𝗶𝗱𝗲𝗿𝘀.

That matters because AI is no longer about finding one model that does everything.

Different models are built with different strengths.

Some are better suited for reasoning.
Some for coding.
Some for long-form content.
Some for visual understanding.
Some for speed.
Some for building AI agents.

Instead of constantly moving between different platforms, AINFT brings a broad selection of models into one environment, giving users more flexibility over which model they use for a particular task.

Here’s how the current model lineup breaks down:

■ 𝗗𝗲𝗲𝗽𝗦𝗲𝗲𝗸
DeepSeek V4 Flash
DeepSeek V4 Flash Vision Exp
DeepSeek V4 Pro

■ 𝗧𝗲𝗻𝗰𝗲𝗻𝘁
HY3
HY4 Preview

■ 𝗫𝗶𝗮𝗼𝗺𝗶
MiMo V2.5
MiMo V2.5 Pro

■ 𝗭.𝗮𝗶
GLM-5.3 Flash
GLM-5.3
GLM-5.2
GLM-5.1

■ 𝗔𝗹𝗶𝗯𝗮𝗯𝗮
Qwen3.8 Flash
Qwen3.8 Max
Qwen3.8 27B, powered by BTTInferGrid

■ 𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰
Claude Fable 5.1
Claude Fable 5
Claude Opus 5
Claude Opus 4.8
Claude Opus 4.7
Claude Opus 4.6
Claude Opus 4.5
Claude Sonnet 5
Claude Sonnet 4.6
Claude Sonnet 4.5
Claude Haiku 4.5

■ 𝗢𝗽𝗲𝗻𝗔𝗜
GPT-5.6 Sol
GPT-5.6 Terra
GPT-5.6 Luna
GPT-5.5
GPT-5.5 Instant
GPT-5.4
GPT-5.2
GPT-5.4 Pro
GPT-5.4 Mini
GPT-5 Mini
GPT-5.4 Nano
GPT-5 Nano
GPT-6 Astra

■ 𝗚𝗼𝗼𝗴𝗹𝗲
Gemini 3.1 Pro
Gemini 3.8 Flash
Gemini 3.5 Flash
Gemini 3 Flash
Gemini 3.5 Flash Lite
Gemini 3.6 Flash

■ 𝗠𝗶𝗻𝗶𝗠𝗮𝘅
MiniMax M3
MiniMax M2.7

■ 𝗠𝗼𝗼𝗻𝘀𝗵𝗼𝘁
Kimi K2.6
Kimi K3

The important part isn’t simply the number 47.

It’s what having this much model choice changes for the user.

𝗖𝗼𝗱𝗶𝗻𝗴?

Choose a model optimized for software development, debugging, technical reasoning, or code generation.

𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴?

Use a model designed to handle complex instructions, analysis, and multi-step problems.

𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗰𝗿𝗲𝗮𝘁𝗶𝗼𝗻?

Different models can offer different writing styles, response speeds, and levels of contextual understanding.

𝗩𝗶𝘀𝘂𝗮𝗹 𝘁𝗮𝘀𝗸𝘀?

Vision-capable models can process and reason about visual information rather than working with text alone.

𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀?

Model selection becomes even more important because agents may need to reason, plan, use tools, interpret information, and execute multi-step workflows.

So the practical framework is simple:

𝟭. 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝘁𝗮𝘀𝗸
Know exactly what needs to be accomplished before choosing a model.

𝟮. 𝗠𝗮𝘁𝗰𝗵 𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹 𝘁𝗼 𝘁𝗵𝗲 𝘄𝗼𝗿𝗸
Don’t automatically use the same model for every task.

𝟯. 𝗖𝗼𝗺𝗽𝗮𝗿𝗲 𝗼𝘂𝘁𝗽𝘂𝘁𝘀
When several models are available, test which one produces the best result for the specific workflow.

𝟰. 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗳𝗼𝗿 𝘀𝗽𝗲𝗲𝗱 𝗮𝗻𝗱 𝗰𝗼𝘀𝘁
The most powerful model isn’t always the most practical model. For simpler tasks, a faster or lighter model may be enough.

That is the bigger idea behind multi-model AI.

𝗧𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗔𝗜 𝗶𝘀𝗻’𝘁 𝗻𝗲𝗰𝗲𝘀𝘀𝗮𝗿𝗶𝗹𝘆 𝗮𝗯𝗼𝘂𝘁 𝗼𝗻𝗲 𝗺𝗼𝗱𝗲𝗹 𝘄𝗶𝗻𝗻𝗶𝗻𝗴.

It’s about having the right intelligence available for the right job.

And with 47 models currently listed across DeepSeek, Tencent, Xiaomi, https://t.co/TTujOlKoHW, Alibaba, Anthropic, OpenAI, Google, MiniMax, and Moonshot, AINFT is positioning itself as a single access layer for a broad range of AI capabilities.

More choice.

More flexibility.

More ways to match the model to the task.

Try it today! https://t.co/D67CNazBvP

@BAI_AGI @AINFTcom @justinsuntron #TRONEcoStar

[†εςhgεεg @Techgeeg]

Tokenized equities hitting $4.45B is a pretty big signal.

Stocks aren’t just staying on-chain as an experiment anymore. They’re becoming a real part of the tokenized asset market.

And this is where Injective gets interesting.

If more traditional assets are moving on-chain, the infrastructure underneath them needs to be fast, efficient, and built for real financial activity.

Stocks are having their onchain moment. Injective is built for what comes next. 🥷

@injective