Inkling vs. GPT-4o

Inkling is an open-weights multimodal AI model from Thinking Machines built to support customization, agentic workflows, coding, reasoning, vision, audio, and enterprise AI use cases. The model is a Mixture-of-Experts transformer with 975 billion total parameters, 41 billion active parameters, 256 routed experts per MoE layer, and six routed experts active per token. It supports context windows up to 1 million tokens and was pretrained on 45 trillion tokens across text, images, audio, and video. Inkling is designed as a broad foundation model rather than a narrowly optimized benchmark model, giving it balanced capabilities across reasoning, coding, factuality, instruction following, vision, audio, tool use, and safety. Its controllable thinking effort lets developers adjust how much computation and generated reasoning the model uses, helping teams balance quality, latency, and cost for different production needs. The model can run agentic coding tasks, use tools, create web apps, generate polished multi-page artifacts, reason over long contexts, and work through iterative refinement loops. For multimodal tasks, Inkling can process images, answer questions about visual content, transcribe and reason over audio, follow spoken instructions, and combine visual reasoning with code-based tools such as Python. Thinking Machines trained Inkling for calibration, instruction following, factual reliability, refusal behavior, and safety across multiple modalities, including evaluations for dangerous capabilities and human-AI threat vectors. Inkling is available on Tinker for fine-tuning, with 64K and 256K context options, an Inkling Playground for testing, cookbook recipes, and support for multimodal post-training workflows. Its full weights are available on Hugging Face, and deployment support is available through APIs and infrastructure partners such as TogetherAI, Fireworks, Modal, Databricks, Baseten, SGLang, vLLM, llama.cpp, and transformers.

GPT-4o, with the "o" symbolizing "omni," marks a notable leap forward in human-computer interaction by supporting a variety of input types, including text, audio, images, and video, and generating outputs in these same formats. It boasts the ability to swiftly process audio inputs, achieving response times as quick as 232 milliseconds, with an average of 320 milliseconds, closely mirroring the natural flow of human conversations. In terms of overall performance, it retains the effectiveness of GPT-4 Turbo for English text and programming tasks, while significantly improving its proficiency in processing text in other languages, all while functioning at a much quicker rate and at a cost that is 50% less through the API. Moreover, GPT-4o demonstrates exceptional skills in understanding both visual and auditory data, outpacing the abilities of earlier models and establishing itself as a formidable asset for multi-modal interactions. This groundbreaking model not only enhances communication efficiency but also expands the potential for diverse applications across various industries. As technology continues to evolve, the implications of such advancements could reshape the future of user interaction in multifaceted ways.