QwQ-32B API is part of the Qwen series, is an innovative medium-sized reasoning model that excels in tackling complex tasks where conventional instruction-tuned models may fall short. Its impressive performance, especially in difficult scenarios, places it alongside leading-edge models like DeepSeek-R1 and o1-mini.
Model Type: Chat
OpenAI’s GPT-5.1 Instant is the low-latency variant of the newly released GPT-5.1 family (announced November 12, 2025). It’s designed to deliver the “most-used” ChatGPT experience with faster turn-taking, warmer conversational tone defaults, improved instruction following, and a built-in adaptive-reasoning capability that decides when to reply immediately and when to spend extra compute to “think” through […]
Model Type: Chat
Qwen-Image-Edit is the editing branch of the Qwen image family developed by the Qwen team (Alibaba / QwenLM ecosystem). It is built on a 20-billion-parameter MMDiT backbone and explicitly extends Qwen-Image’s advanced text-rendering capabilities into robust image-editing workflows. The model is intended for tasks where editing fidelity matters — e.g., directly changing text on signs, […]
Model Type: Image
Qwen-Image is an image-generation and image-editing foundation model in the Qwen family designed for high-fidelity text rendering, precise editing, and general text-to-image generation.
Model Type: Image Generation
On November 12, 2025, OpenAI rolled out GPT-5.1, a focused upgrade to the GPT-5 family that emphasizes conversational quality, instruction-following, and adaptive reasoning. The release reorganizes the GPT-5 lineup around two primary production variants — GPT-5.1 Instant and GPT-5.1 Thinking — and keeps the automatic routing layer (often described as Auto) that chooses the best […]
AI image generation has exploded from novelty to core creative tooling in under three years. Two names you’ll see everywhere right now are Nano Banana (Google’s Gemini 2.5 Flash Image family, popularly nicknamed “Nano Banana”) and Midjourney. They target overlapping users — designers, marketers, agencies, developers — but come from different technical and business philosophies. […]
OpenAI recently announced several updates, including the release of the GPT-5-Codex-Mini model, improvements to the rate limit for multi-user hierarchies, and optimizations to model processing efficiency. OpenAI’s GPT-5-Codex-Mini is a newly announced, developer-focused variant of GPT-5-Codex: a smaller, cost-and-throughput-optimized model intended to deliver most of the coding assistance of GPT-5-Codex but at much lower cost […]
Announced and rolled out in October 2025, Hailuo 2.3 is a next-generation text-to-video (T2V) and image-to-video (I2V) model from the team behind Hailuo AI (MiniMax / Hailuo.ai) that pushes motion realism, prompt fidelity and production speed well past the bar set by prior models. What is Hailuo 2.3 and why does it matter? Hailuo 2.3 […]
gpt-image-1-mini is a cost-optimized, multimodal image model from OpenAI that accepts text and image inputs and produces image outputs. It is positioned as a smaller, cheaper sibling to OpenAI’s full GPT-Image-1 family — designed for high-throughput production use where cost and latency are important constraints. The model is intended for tasks such as text-to-image generation, image editing / inpainting, and workflows that incorporate reference imagery.
Model Type: Image
Kimi K2 Thinking is the newest agentic reasoning variant in the Kimi K2 family: a large, mixture-of-experts (MoE) model tuned to do sustained, step-by-step reasoning and to call external tools reliably across long multi-step workflows.In this guide I pull together the latest public information, explains what Kimi K2 Thinking is, how it compares with contemporary […]
By the end of 2025, the competition in AI models will intensify. The upcoming releases of GPT 5.1 and Gemini 3.0 Pro are undoubtedly a major focus. The looming releases are both a signal of competition and a marketing tactic for companies to preemptively seize market share. Gemini 3.0 has released code signals on Vertex: […]
