The large AI labs (Anthropic, OpenAI, Grok, Gemini, etc) are constantly releasing new versions and improvements.

People on social media often advocate for one specific model claiming that it performs tasks better than others.

OpenAI just dropped GPT-5.6, their largest model yet, and we're teaming up with them to get it into makers' hands.

Here's the deal:
- Build something with Sol, Terra, or Luna
- Schedule your launch on Product Hunt for July 23

- The top products walk away with $10k in OpenAI credits

OpenAI just dropped GPT-5.6, their largest model yet, and we're teaming up with them to get it into makers' hands.

Here's the deal:
- Build something with Sol, Terra, or Luna
- Schedule your launch on Product Hunt for July 23

- The top products walk away with $10k in OpenAI credits

OpenAI just dropped GPT-5.6, their largest model yet, and we're teaming up with them to get it into makers' hands.

Here's the deal:
- Build something with Sol, Terra, or Luna
- Schedule your launch on Product Hunt for July 23

- The top products walk away with $10k in OpenAI credits

We're taking part in the GPT-6 Astra Challenge with OpenAI right now, which got me thinking about this.

New models drop constantly. Some people test everything immediately, others stick with what works until there's a real reason to switch.

In a notable shift in the AI landscape, Apple and Google have announced a multi-year collaboration under which Apple s next generation of Apple Foundation Models will be based on Google s Gemini models and cloud technology.

According to the joint statement, these models will help power upcoming Apple Intelligence features, including a more personalized Siri, expected later this year.

Over 400 products launched for OpenAI Day. Five walked away with $10K in OpenAI credits, all built on GPT-5.6.

Teable 3.0 Point it at any system, migrate the data, get working AI workflows and custom apps out the other end.

Over 400 products launched for OpenAI Day. Five walked away with $10K in OpenAI credits, all built on GPT-5.6.

Teable 3.0 Point it at any system, migrate the data, get working AI workflows and custom apps out the other end.

Over 400 products launched for OpenAI Day. Five walked away with $10K in OpenAI credits, all built on GPT-5.6.

Teable 3.0 Point it at any system, migrate the data, get working AI workflows and custom apps out the other end.

Yesterday, Meta announced that they have released a new collection of AI models, Llama 4, in its Llama family.

(It consists of Llama 4 Scout, Llama 4 Maverick, and Llama 4 Behemoth.)

Historically, Open AI with its ChatGPT has been on the market for the longest period.

New AI models pop up every week. Some developer tools like @Cursor, @Zed, and @Kilo Code let you choose between different models, while more opinionated products like @Amp and @Tonkotsu default to 1 model.

Curious what the community recommends for coding tasks? Any preferences?

Anthropic released Claude Fable 5 today, and it's a bit different from the usual model bump.

It's not a bigger Opus - it's a new tier above Opus, built on the same underlying model as Mythos, the one Anthropic had locked behind a government cybersecurity program since April.

Here s its own version of what it does:

Raycast keeps adding new models every week.

I use @Anthropic's Claude 3.7 Sonnet when coding and @OpenAI's o3-mini when speed matters. Curious what works best for the community.
Over to you! What model are you using and why?

Edit 2025-07-30: Raycast just introduced Auto Models. "Let AI choose the best model for the job at hand." Join the discussion here 

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There's a lot of options for models these days. I've been using Claude 3.7 but I'm curious what's been working well for others. What model are you using and why?

Is the thinking version of @Claude by Anthropic worth the extra credit spend? Does @DeepSeek work well enough to save some credits? Is it worth trying any of the @ChatGPT by OpenAI models?

There's a lot of options for models these days. I've been using Claude 3.7 but I'm curious what's been working well for others. What model are you using and why?

Is the thinking version of @Claude by Anthropic worth the extra credit spend? Does @DeepSeek work well enough to save some credits? Is it worth trying any of the @ChatGPT by OpenAI models?

One of the biggest pain points in AI chatbots has been their forgetfulness having to repeat the same context over and over again. AI memory aims to solve this by allowing models like ChatGPT and the newly launched Gemini to retain past interactions.

But how well do these memory features work? Which AI ChatGPT or Gemini handles memory better? And more importantly, does AI memory provide more value in personal use or enterprise settings?

On their livestream today, OpenAI just released a bunch of new tools for reliably building and using AI agents. From what I can tell, this is what's new-

New APIs:

• Responses API - a new multi-modal API that builds on chat completions to allow for the next-generation of tool calling, starting with the new tools announced today.

I ve been testing the 'Free Tier' limits of the 2026 AI landscape. While everyone swears by Claude 3.7 or GPT-5.2, I m trying to find the 'Golden Ratio' for makers on a zero-budget.

My current findings for the Office Bee MVP:

• The Brain: Gemini 3.1 Pro (via AI Studio) seems to have the highest 'Reasoning-per-Dollar' (free) for deep R&D.

• The Frontend: v0 (Free Tier) for shadcn/ui components.

• The Glue: Bolt.new for the initial scaffold.

The Challenge: Most 'free' models hallucinate complex state management in full-stack architectures.