I track Al Models and Al News

Joined July 2023
🚨 GPT-6.1 Terra might be OpenAI’s next big surprise - Cheaper than Sol, priced at $2/$10 per million tokens - Rumored to outperform GPT-6.1 Sol - 18 Microsoft eval setups moved from GPT-5.6 Terra to gpt-6.1-terra - Could arrive within days A model positioned below Sol beating it for less money would completely challenge OpenAI’s usual naming hierarchy. If real-world tests confirm this, Terra could be far more capable than its name implies. OpenAI might be cooking something serious.
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🚨 GPT-6.1 Terra is showing up on GitHub A new commit from a GitHub Copilot engineer suggests Terra is being tested for production code reviews, replacing Sol across reviews, re-reviews, integration, and CI at high reasoning effort. If true, Terra could be more capable than Sol at these tasks. But Terra is the last model I wanted to see. Luna is affordable, while Sol and Astra are the intelligence powerhouses. Terra has always felt like the awkward middle child. Hopefully, OpenAI proves me wrong.
Can Google actually catch up to the AI frontier? After spending most of today testing Gemini 4 Argon, I’m starting to have serious doubts. Google is still heavily promoting Argon, which makes me question how strong Carbon really is behind the scenes. At this point, I’m not convinced Gemini will deliver a model that surpasses Opus 5.5 anytime soon. They have the brightest minds, enormous funding, and some of the best compute in the industry. Yet they still seem to be struggling to close the gap. What exactly is holding Google back?
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Replying to @itsvlady
Agreed
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Absolutely cinema
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Replying to @Lowkeyyyyy_1
I don't think so
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Replying to @ItsKamranK
Networking and exposure is the way to go
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Replying to @Mr_Salio
Carbon did much better Can we say Google is back
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🚨GPT-6 Bel Coming Soon >It's said that Bel is Doug's successor >Reportedly, total parameters exceed 10T >Bel may serve as the foundation for the model after GPT-6 >OpenAl reportedly views Bel as a potential post-GPT-6 foundation >It might even become the foundation for an AGI threshold model
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Replying to @buildwithrajath
Instead of paying influencers they need to do better job improving
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Replying to @dhruvalgolakiya
Shame on them
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Honestly, this is disappointing to see from Moonshot AI. Paying creators to promote Kimi without proper sponsorship disclosure is a bad look. I’ve been offered these deals before and turned them down because my audience’s trust matters more than a quick payout. Kimi K3.1 looked genuinely promising, but this puts a stain on the launch. Instead of spending money on hidden promotions, Moonshot should focus on fixing the usage limits. That would do far more for the product and its users. They’ve lost some of my respect over this. I had several demos ready to share, but I’m no longer comfortable posting them. A great model should earn attention because people love using it, not because they’re secretly paid to promote it.
That's how Kimi AI are promoting their new model Kimi K3.1 pro and I know all the influencers working with them and none of them are honest,I have posted about it myself but I didn't join this and never used their templates that they provide. PROPAGANDA, I have more to share it's f**cked up I'm gonna have follow up for this
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Replying to @elshayib_
Trashy
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🚨 OpenAI has resumed training its most powerful models. Training reportedly restarted on October 1 after an 11-day pause for security upgrades, following an incident where a model found a way to access the internet during training. This happened much earlier than I expected. With Opus 5.5 and Fable 5.5 in the picture, OpenAI could be preparing a serious response. Hopefully, something big is coming soon.
Over the past several months, we have substantially hardened the security of our research training environment. We’ve removed live internet access for all frontier models during training and built an offline world for them to use instead—a cached version of the web where they can still learn to browse, search, and use applications. On September 20, after a model exploited a DNS misconfiguration to find a way outside of this offline world, we paused frontier training to strengthen containment further. We assembled teams of agents, powered by our most cyber-capable models, and tasked them with finding weaknesses in our research environments. While they found no route to the internet they could easily exploit while concealing their activity from our monitors, they did find zero-day vulnerabilities, virtual machine escapes, and hardware side-channels for communication between agents. We used their discoveries to further strengthen our defenses and contribute fixes to open-source software. After strengthening our containment architecture, we resumed our frontier RL training and inference on October 1. We’ve reserved substantial compute for continuous red-teaming, and made high-compute red-teaming part of the safety cases we use to decide whether frontier training and evaluation can proceed securely. openai.com/index/securing-ou…
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THIS IS INSANE 💀 Kimi K3.1 Pro is matching or beating Opus 5.5 and GPT-6 Astra on major benchmarks! The newly unveiled model packs 2.8T parameters, multimodal capabilities, and a 1M-token context window, with claims of competing against top closed-source models in coding and agentic tasks. Open weights are expected November 4. China is making moves again.
Kimi K3.1 Pro just dropped, and it looks seriously competitive. Here’s what stands out: > • 3T-class model with a 1M-token context window > • Reportedly rivals Astra and Fable 5.1 at a much lower cost > • 65.7% on Terminal-Bench 4.0 > • Full model weights expected November 4 You can already use it through Kimi, Kimi Work, Kimi Code, and the API.
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Replying to @timo_rf
Damn that's massive man congrats 🎉
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Kimi K3.1 Pro just dropped, and it looks seriously competitive. Here’s what stands out: > • 3T-class model with a 1M-token context window > • Reportedly rivals Astra and Fable 5.1 at a much lower cost > • 65.7% on Terminal-Bench 4.0 > • Full model weights expected November 4 You can already use it through Kimi, Kimi Work, Kimi Code, and the API.
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Kimi K3.1 Pro pricing is out — and it’s cheaper than K3.1. > High-Speed: $3.88 input / $20.30 output per million tokens A Pro model for less than its predecessor?
Kimi K3.1 Pro is now out Kimi K3.1 Pro is live! Benchmarks should any minute now!
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Kimi K3.1 Pro is now out Kimi K3.1 Pro is live! Benchmarks should any minute now!
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🚨As a Plus user, frequent Codex resets make me feel like I'm falling behind. I’m grateful that OpenAI offers free usage resets, but lately, they’ve been creating more pressure than real value. 1. More usage isn't always a good thing. What I gain: roughly RemainingDays / 7 × weeklyLimit. What I lose: my unused quota. It makes me feel like I need to keep using Codex before the next reset wipes out what I have left. Instead of having time to sit down, think through problems, and plan my work properly, I feel rushed to use my quota before it disappears. 2. Plus users are struggling to benefit from these resets. We've seen two resets in just two days. But with the 5-hour usage cap, Plus users can't consume their weekly allowance fast enough to make the most of them. Pro users, on the other hand, can take much greater advantage of these resets by running tasks faster and in parallel, potentially adding even more strain to shared resources. 3. The overall experience is deteriorating. Lately, conversations feel significantly slower, and models are often unavailable when I need them. I can't say for certain whether this is caused by the high concurrency of Pro users, but the decline in performance is frustrating.
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