Accuracy and consistency in your tasks.
Let’s get to know the models, without making it a race.
We’ve covered the capabilities. Now we can go through the US, Europe, and China families, knowing each serves different purposes.
Before looking at names, let’s get the magnifying glass ready.
Public tables help with orientation, but they don’t tell the whole story. A useful comparison tests real work and adds governance: what data each model receives, where it’s processed, who approves its use, and how a version change is controlled.
Time to a usable answer.
Inference, infrastructure, and operations.
How much information it effectively processes.
Privacy, residency, lineage, and retention.
What it can view, run, approve, and verify.
A model is a way of looking.
Different representations reveal different structures.
First scale: global families.
Each lab makes different choices about speed, reasoning, openness, and price. Also, a family changes over time: the exact version under test always matters.
GPT-5.6
Multimodal family for analysis, code, and tool-using systems. Its catalog separates variants by capability, speed, and cost.
Claude Sonnet 5
Anthropic guides you on programming, tool use, and extended knowledge tasks.
Gemini 3.6 / 3.5
The Gemini family combines text, images, audio, video, reasoning, and tools within Google’s ecosystem.
Medium 3.5 / Small 4
Relevant European families when efficiency, enterprise integration, and deployment alternatives matter.
Second leg: the Chinese ecosystem.
This isn’t a footnote. China brings together labs with language, vision, audio, and agent models, plus its own industrial chain. Some families publish weights and components; others are offered via API.
Qwen 3.6
Qwen covers language, vision, audio, code, and tool integration. The official repository lets you directly review architecture, weights, and license.
DeepSeek V4
DeepSeek presented V4 Preview with context of up to one million tokens. Always distinguish the version offered via API from the published components.
Kimi K3
Moonshot presents Kimi K3 for knowledge work, programming, and task execution with agents.
GLM-5
GLM-5 is oriented to reasoning, code, and tool-using systems. Its repository documents the open version.
MiniMax M3
MiniMax maintains specialized families for generative language and media. Its catalog is broader than a single LLM.
Check available region, commercial license, data residency, support language, inference price, and the real possibility of running the model on your own infrastructure.
Let’s detour briefly into images.
ConvNets · Vision Transformers
Assign one or more categories to the entire image.
YOLO · DETR and derivatives
They locate objects and deliver their positions.
U-Net · Segment Anything
They identify the exact region each object occupies.
Meta AI · official sourceMultimodal models
They relate a scene to instructions and context.
OCR + layout understanding
They extract text, tables, and spatial relationships.
Diffusion and multimodal models
They create or edit images and video under instructions.
API or in-house model? Depends on the baggage.
Models with available weights can run on your own infrastructure. That gives more control over data and versions, but it also leaves the company in charge of security, capacity, updates, and monitoring.
Managed API
- Quick access to recent models
- Less infrastructure operations
- Vendor lock-in and policies
Self-hosted deployment
- Greater control over data and version
- Deeper personalization
- Full operational responsibility
Hybrid architecture
- Route by sensitivity and task
- Combine cost, quality, and control
- Needs common governance
Before we wrap up, we’ll put the sources on the table.
We start with primary documentation. An announcement states what its author declares; that’s why we date it, link it, and don’t confuse it with independent evidence.