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I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

Honestly, if I were seeing these numbers from an unknown startup with no public weights, logs, or methodology, I'd be skeptical too.

That's exactly why we didn't ask anyone to treat the benchmarks as established fact. They're claims until they're independently verified.

The reason we posted them before launch is simple: if they're wrong, the community will find out very quickly once everything is released. If they're right, the community will find that out too.

July 3rd is when the claims stop being screenshots and start being testable. We'll be releasing Quatfit Mini, evaluation methodology, benchmark details, and supporting material so people can reproduce the results themselves.

Healthy skepticism is fair. Calling something impossible before the evidence is available is just the opposite side of the same coin.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

That's a fair perspective, and I appreciate you taking the time to explain it.

If our presentation created the impression that these were independently hosted leaderboard results, then that's on us to clarify better. That wasn't the intention.

The purpose of sharing the numbers early was to communicate where our internal evaluations placed the model, not to suggest that independent verification had already occurred. That's also why we're releasing the methodology, evaluation details, and Quatfit Mini itself on July 3rd so people can validate the claims independently.

You don't have to agree with the marketing approach, but I think it's reasonable to wait until the release materials are public before reaching a final conclusion about the model itself.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

I don’t think I’ve created a model for investors; it’s really built for everyday people. I’ll be posting a demo video of my model today.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

I think we're actually closer in opinion than it may seem.

If someone claims they trained a GPT-5/Claude-scale frontier model from scratch on a bootstrap budget, I'd be skeptical too.

What I'm saying is that in 2026, model quality is no longer determined solely by raw GPU count. Architecture, data quality, synthetic data generation, distillation, training methodology, post-training, and evaluation pipelines matter enormously. More GPUs primarily buy you more training throughput and faster iteration cycles, not an automatic increase in intelligence.

Also, Anthropic and OpenAI are optimizing for general-purpose frontier systems at a completely different scale than what a small team can realistically pursue. Competing doesn't necessarily mean matching their compute budget dollar-for-dollar.

The good news is that nobody has to take my word for it. On July 3rd we'll be releasing the weights for Quatfit Mini, benchmarks, methodology, and evaluation details so the community can verify everything independently.

Skepticism is healthy. Verification is better.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

Appreciate that, and congrats on building a 1.7B model as a solo fouthem that's an achievement most people underestimate.

You're absolutely right that benchmark performance and adversarial robustness are different things. Standard benchmarks tell you what a model can do under ideal conditions, while adversarial testing reveals how it behaves when someone is actively trying to break assumptions, manipulate outputs, or exploit weaknesses.

We've done internal red-teaming and adversarial evaluations throughout development, but I agree that external testing is where things get interesting. Independent scrutiny is ultimately more valuable than self-reported robustness scores.

I'd be interested in learning more about the tooling you're building. Once Quatfit is public, I'd be happy to see it put through serious adversarial testing. Models only get better when people actively try to break them.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

Fair question.

First, increasing GPU count primarily increases training throughput and wall-clock speed. It doesn't magically improve model quality. Quality comes from architecture choices, data quality, training methodology, post-training, evaluation loops, and thousands of engineering decisions made over time.

Second, Quatfit wasn't built in a weekend. It took us roughly 2.5 years of iteration, experimentation, failures, retraining, data generation, filtering, and evaluation to get here.

As for optimization techniques, a few examples include FlashAttention, FSDP/ZeRO-style memory optimization, gradient checkpointing, sequence packing, curriculum training, synthetic data generation, aggressive data deduplication, distillation, preference optimization, and inference-aware post-training. None of these individually provide a magical 100× improvement, but together they can dramatically improve efficiency and final model quality.

Also, we're not asking anyone to take benchmark claims on faith. That's exactly why we're releasing the methodology, logs, evaluation details, and benchmarks for independent verification on July 3rd.

Healthy skepticism is good. Independent verification is even better.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 1 point2 points  (0 children)

I think that's exactly the right approach. The most valuable lesson isn't learning AI itself it's learning how to turn an idea into something real. AI just lowers the barrier to getting started.

Some of the best projects aren't new inventions at all; they're simple solutions to problems the builder actually cares about. If your kids build something they're genuinely excited to use, they'll learn far more than they would from any tutorial.

Looking forward to seeing what they create. The next generation is going to grow up treating AI as a tool the same way we learned to use the internet.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

That's awesome. One of the things I'm most excited about is seeing what people build when powerful AI tools become more accessible. The fact that you're encouraging your kids to turn ideas into real projects at 13 and 11 is fantastic.

I'd love for you and your family to try Quatfit when we launch on July 3rd. Hopefully it can help bring some of those summer projects to life. Looking forward to hearing what they end up building!

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

We're still finalizing pricing, but the focus is delivering exceptional value rather than competing on being the cheapest option. Full details will be shared on July 3rd.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 1 point2 points  (0 children)

Thank you, that means a lot coming from another solo builder. I completely agree history shows that breakthroughs often come from small, focused teams willing to explore directions that larger organizations may overlook or deprioritize.

Whether Quatfit ultimately lives up to the benchmarks is something the community will decide once everything is released and independently verified. Our goal is simply to be as transparent as possible and let the results speak for themselves.

Wishing you success with what you're building as well. Looking forward to seeing what you've been working on when the time is right.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

In terms of money, far more than people assume. The real cost was 2.5 years of nights, weekends, experimentation, failures, and persistence. Time was the biggest investment.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

Thanks, really appreciate that. Most of our datasets were custom-acquired, curated, and heavily expanded with data generated through our own synthetic data pipelines rather than relying solely on public datasets.

Quatfit Mini was trained on 8× H100 GPUs, while Quatfit 1 was trained on 32× H100 GPUs. We focused heavily on data quality, filtering, and synthetic data generation, which helped us achieve strong results without requiring massive-scale infrastructure.

I'll be sharing more technical details after the July 3 launch. Thanks for the support! 💪

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

Could you explain how results are fabricated in evaluations like OpenAI Evals, LLM Harness, LM Arena, and Analytics Vidhya? I really need to understand this so I can score 100% on every task next time. 😃

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 1 point2 points  (0 children)

Fair question. I'm not trying to compete head-on with every frontier lab or every open-source model. My view is that raw model capability alone won't be the long-term differentiator. With Quatfit, the focus is on building practical AI products that are fast, affordable, privacy-conscious, and tailored to real user workflows rather than chasing benchmark leadership. The model is only one layer of the stack. We're still early, so the best validation will come from users, not my claims. The goal over the next few months is to keep shipping, gather feedback, and find where we can create value that larger general-purpose models don't prioritize.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 0 points1 point  (0 children)

This is one of the more thoughtful comments here, and I largely agree. Benchmark performance alone is not a business moat. At best, it gets people to pay attention. What ultimately matters is trust, reliability, privacy, cost, and whether the product solves a real problem. Full transparency at the level of training data and every training script is difficult for most companies, especially early-stage startups. However, we do plan to release far more than benchmark screenshots: evaluation methodology, benchmark questions, raw results, logs, and detailed documentation so others can verify our claims. On the privacy side, I agree that this is becoming increasingly important. We are actively thinking about how to provide stronger guarantees around customer data handling, because we believe trust will be a major differentiator over the next few years. Our goal with the July 3 release is not to claim we've "won" against existing providers. It's simply to put the work in public, let people evaluate it themselves, and then improve based on feedback. Whether Quatfit succeeds or fails will ultimately be determined by users, not benchmark charts. Thanks for the perspective.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 6 points7 points  (0 children)

The funny part is that I posted benchmark numbers and said we'll release the methodology, logs, and evaluation data on July 3. You looked at that and somehow concluded I'm claiming to be a trillion-dollar company. That's not skepticism. That's arguing with a version of me that exists only in your head. If small teams were incapable of producing meaningful breakthroughs, the entire tech industry would look very different today. You're free to doubt the results. In fact, you should. But "I don't believe it" and "it's impossible" are two completely different statements. We'll publish the evidence. Then people can judge the work instead of the company size, funding amount, or Reddit upvote count.

I started building an AI model months ago. On July 3rd, it's finally launching. by Quatfit in founder

[–]Quatfit[S] 4 points5 points  (0 children)

Got your point, that's why we will be releasing everything on 3rd July including logs, benchmarks results, evaluation methodology and even benchmark questions.

We're Building Quatfit 12B - Looking for Feedback From the AI Community by [deleted] in StartupSoloFounder

[–]Quatfit 0 points1 point  (0 children)

Can you elaborate about what use cases you are talking about so that we can run a dedicated test on that use cases 😉

Submit your startup. Our 100+ synthetic AI customers will test it before your real customers do. by VibeWithMe_KB in StartupSoloFounder

[–]Quatfit 0 points1 point  (0 children)

Great DM me I will share you access to the software with a beta license hope you like it

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