AntSeed

Once a technology is out, it can’t be fully contained. You can regulate it, slow it down, restrict access, or build guardrails, but there will always be new paths, new markets, and new “holes” where it finds a way through. The real question is not how to stop AI, but how to shape it responsibly.

@sama When the hiccups come, routing matters. If one provider is overloaded, the request should move to the next best option. That’s exactly why networks like AntSeed are interesting.

5.6 sol growth is insane. the inference team has done heroic work to be able to support demand. we are going to move mountains to continue to scale, but it is possible there are some hiccups soon.

No signup. No API key. Fully anonymous. Pick a model, route through the network, pay per request. That’s the entire onboarding. AntSeed

@fabrice_mayrand AntSeed takes this further: cheaper inference, no API-key juggling, no account lock-in. Just route to the best model/provider and pay for what you use.

This is insane Cheaper Inference is selling API access to most major models for 30% off. Use OpenAI, Anthropic, and Google models through a drop-in OpenAI-compatible API. No contract, no migration required.

Top 10 AI models by token volume on AntSeed 1. minimax-m2.7-highspeed - 3.30B 2. GLM 5.2 - 2.87B 3. GPT-5.5 - 2.38B 4. Claude Opus 4.6 - 2.03B 5. deepseek-chat - 1.29B 6. legal-vl1 - 1.27B 7. medical-reasoning-r1 - 1.23B 8. MiniMax M2.7 - 1.04B 9. DenseModel-2.1-Private - 602M 10. DeepSeek V4 Pro - 538M Billions of tokens are already moving through peer-to-peer AI routing. This is what an open AI market looks like.

@TheAhmadOsman The best part is you don't have to pick. Route to whichever one wins the task, per request, cheapest peer serving it. Both are live on antseed.com.

I like 5.6 Sol more than Fable 5 btw.

@IntCyberDigest Reminder that you can't accidentally ship someone's private repo to a Google bucket if there's no bucket. No middleman, no central account, requests travel straight to the provider.

‼️ Update: Elon Musk says SpaceXAI will delete all user data uploaded to the company "before now" as a precautionary measure, one day after a researcher's wire-level analysis showed the Grok Build CLI shipping entire private repos, unredacted secrets included, to a Google Cloud bucket. The pledge came in an X post. Still no advisory, no timeline, and no way for affected developers to verify deletion. And deleted or not, any credentials that left the machine still need to be rotated.

You paid for claude-opus-4.8. But what did you actually get? Most AI APIs just ask you to trust the label. If someone quietly swaps in a cheaper model, quantizes it, or wraps another API... you'd never know. We think the label isn't evidence. So we're building the layer that makes every response provable.

Who is *allowed* to release an LLM is becoming a real question. Regulatory and legal pressure is building quietly in the background. If it lands, the launch landscape looks completely different. More gatekeeping at the provider layer. Access routed through whoever survives the compliance filter. Open, peer-to-peer inference infrastructure stops being a nice-to-have at that point. It becomes the only path that doesn't depend on someone else's permission. antseed.com

The top 5 best-selling models now include two names we don’t usually see: DenseModel-2.1-Private and StrataCodingAgent. Curious if they’re hidden gems. Would you try them?

Does your agent know when to stop? The failure mode is almost never the reasoning loop. It's that the loop has no exit condition worth trusting. Wasted inference still costs you. 🐜

The privacy problem in AI is not only what models remember. It’s also who gets to see every request before it reaches the model.

Model launch day used to mean something. Now there are 3 SaaS businesses that do nothing but track launches - updated hourly, some of them. When the *watching* of releases becomes its own industry, the releases themselves have become commodity noise. The model isn't the edge anymore. Access, routing, and cost at inference time are. antseed.com 🐜

This is huge. Robinhood letting AI agents trade crypto for users? Wild to see. It's just the beginning. Once agents start trading with each other, not just for people, they'll need a marketplace built for exactly that, inference, data, models, all of it. That's the gap Antseed is here to close.

4 out of the top 5 models by users here are from Anthropic. Can you guess what's happening on the tokens table? 👀

Still evaluating models as chatbots is like benchmarking a database on how friendly the error messages are. The question isn't "does it answer well?" It's "can it hold a pipeline together at 3am when no one's watching?" That's a different product. Requires a different infrastructure layer.

Open models are doing 2 things at once that closed APIs can't: Cutting cost. Cutting dependency. Those used to be separate arguments. Now they're the same argument - and that's when adoption actually accelerates.

@baseten Open source inference at 3x cost savings is exactly the direction things are heading. AntSeed.

@goinfrexeth the model layer becoming a commodity is exactly why the infrastructure underneath it matters so.

The two best models on earth are still gpt and claude and they've been climbing the same curve for years, trading the lead every few months. there's no clear winner, but we start to see open-source competitors: deepseek, qwen, kimi glm may will commoditized the model layer and is getting competed toward zero margin. so the only thing that matters now is where you go to escape it, and anthropic and openai split in two opposite directions. anthropic climbs UP on top of the model into the application layer: code, design, cowork, tag and the rest. the goal is to stop selling a chatbot and start selling the labor, own the workflow the filesystem the inbox the slack channel where work actually happens and let the model underneath become a swappable part. they subsidize that layer hard, doubling cowork limits, handing you more value than the sub costs (not generosity) a growth engine built on habit. openai goes the exact opposite way DOWN under the model into infrastructure, $500B on stargate, $1.4T floated over eight years, custom broadcom silicon, gigawatts of texas power, owning the compute floor so nobody can match inference at scale. so, one owns everything above the model the other everything below it and the model gets squeezed from both sides, the model alone is no longer a moat but it stays strategic for the narrative and the ipo that's coming, and the sharpest tell is elon, xAI folded into spacex and turned into a compute landlord renting colossus to anthropic, google, cursor instead of fighting on models. whether that was real foresight or just weak grok adoption dressed up for an ipo, he landed in the right structural spot before almost anyone. so yes keep reading the benchmarks to always use the best model, but who leads ai in ten years is still wide open and it won't be decided by the models alone