CometAPI

GPT-5.2 vs Gemini 3 Pro: which is better in 2026?

As of December 15, 2025 the public facts show Google’s Gemini 3 Pro (preview) and OpenAI’s GPT-5.2 both set new frontiers in reasoning, multimodality and long-context work — but they take different engineering routes (Gemini → sparse MoE + huge context; GPT-5.2 → dense/“routing” designs, compaction and x-high reasoning modes) and therefore trade off peak benchmark wins vs. engineering predictability, tooling, and ecosystem. Which is “better” depends on your primary need: extreme-context, multimodal agentic applications lean toward Gemini 3 Pro; stable enterprise developer tooling, predictable costs and immediate API availability favor GPT-5.2.

How to use CometAPI in Raycast — a practical guide

Raycast’s AI features now let you plug in any OpenAI-compatible provider via a providers.yaml custom provider. CometAPI is a gateway API that exposes hundreds of models behind an OpenAI-style REST surface — so you can point Raycast at https://api.cometapi.com/v1, add your CometAPI key, and use CometAPI models inside Raycast AI (chat, commands, extensions).

How to create video using Sora-2's audio tool

Sora 2 — OpenAI’s second-generation text-to-video model — didn't only push visual realism forward: it treats audio as a first-class citizen. For creators, marketers, educators, and indie filmmakers who want short, emotionally engaging AI videos, Sora 2 collapses what used to be a multi-step audio/video pipeline into a single, promptable workflow.

Dec 13, 2025

What is Mistral Large 3? an in-depth explainer

Mistral Large 3 is the newest “frontier” model family released by Mistral AI in early December 2025. It’s an open-weight, production-oriented, multimodal foundation model built around a **granular sparse Mixture-of-Experts (MoE)** design and intended to deliver “frontier” reasoning, long-context understanding, and vision + text capabilities while keeping inference practical through sparsity and modern quantization. Mistral Large 3 as having **675 billion total parameters** with **~41 billion active parameters** at inference and a **256k token** context window in its default configuration — a combination designed to push both capability and scale without forcing every inference to touch all parameters.

What is GPT-5.2? An insight of 5 major updates in GPT-5.2!

GPT-5.2 is OpenAI’s December 2025 point release in the GPT-5 family: a flagship multimodal model family (text + vision + tools) tuned for professional knowledge work, long-context reasoning, agentic tool use, and software engineering. OpenAI positions GPT-5.2 as the most capable GPT-5 series model to date and says it was developed with an emphasis on reliable multi-step reasoning, handling very large documents, and improved safety/ policy compliance; the release includes three user-facing variants — Instant, Thinking, and Pro.

Is Free Gemini 2.5 Pro API fried? Changes to the free quota in 2025

Google has sharply tightened the free tier for the Gemini API: Gemini 2.5 Pro has been removed from the free tier and Gemini 2.5 Flash’s daily free requests were cut dramatically (reports: ~250 → ~20/day). That doesn’t mean the model is permanently “dead” for experimentation — but it does mean free access has been effectively gutted for many real-world use cases.

How to change gemini cli directory

Gemini CLI has rapidly become a go-to terminal interface for interacting with Google’s Gemini models. But as teams scale, or when you work across drives or restrictive environments (containers, company-managed laptops, Cloud Shell, Windows systems), you’ll quickly bump into a practical question: where does Gemini store its files, and how can you change which directories Gemini reads and writes?

How to Run Mistral 3 Locally

Mistral 3 is the headline release of Mistral AI’s late-2025 model family. It brings a mix of compact, fast models geared for local/edge deployment and a very large sparse flagship that pushes state-of-the-art scale and context length. This article explains what Mistral 3 is, how it’s built, why you might want to run it locally, and three practical ways to run it on your machine or private server — from the “click-to-run” convenience of Ollama to production GPU serving with vLLM/TGI, to tiny-device CPU inference using GGUF + llama.cpp.

imagen%C2%A04