AI Model Categories refer to the systematic classification of artificial intelligence systems based on their architecture, function, and capabilities. They group models by their design approach—such as neural networks, decision trees, or generative models—which dictates how they process data and solve tasks. This categorization helps researchers and developers compare methods, choose the right tool for specific problems, and understand the field's technological landscape.
1. Text (Language-Only) Models
These models accept text input and produce text output. They focus on natural language understanding and generation.
Actively Used
GPT-4.1 / GPT-5.x family – General-purpose language models used in production systems.
Claude 3 (Sonnet, Opus) – Widely used for reasoning-heavy and enterprise workloads.
Gemini 2.x / 3.x – Google’s flagship language and multimodal models.
LLaMA 3 / LLaMA 4 – Popular open-weight models for self-hosted and research use.
Largely Obsolete / Legacy
GPT-3 / GPT-3.5 – Superseded by newer generations; rarely used in new systems.
Original GPT-4 (2023) – Replaced by GPT-4o and GPT-4.1 variants.
2. Vision Models
These models analyze images without direct language generation capabilities.
Actively Used
YOLO (v8+) – Real-time object detection in production pipelines.
Modern ViT-based backbones – Used internally within multimodal systems.
Largely Obsolete / Legacy
ResNet (standalone usage) – Mostly retained for academic reference.
3. Vision–Language Models (VLMs)
These models jointly understand images and text.
Actively Used
GPT-4.1 Vision / GPT-4o – Image understanding with natural language reasoning.
LLaVA (newer versions) – Open-source visual QA and chat.
Qwen-VL / Gemini Vision – Production-grade multimodal understanding.
Largely Obsolete / Legacy
Early CLIP-only pipelines – Replaced by integrated multimodal models.
4. Audio / Speech Models
These models process spoken audio.
Actively Used
Whisper (maintained variants) – Speech-to-text across many languages.
Modern TTS stacks – WaveNet-derived and neural TTS systems.
Largely Obsolete / Legacy
DeepSpeech – Superseded by newer speech recognition models.
5. Multimodal Models
These models support multiple modalities but may treat them as separate pipelines.
Actively Used
GPT-4o / GPT-4.1 – Text and image inputs with unified reasoning.
Gemini 3 – Text, image, audio, and long-context support.
Claude 3 – Multimodal reasoning with strong safety guarantees.
Largely Obsolete / Legacy
Early multimodal GPT-4 previews – Replaced by native omni models.
6. Omni Models
Unified models that seamlessly work across modalities.
Actively Used
GPT-4o – Native handling of text, image, and audio.
Gemini Omni – End-to-end multimodal interaction.
Qwen Omni – Open-source omni-style conversational model.
Largely Obsolete / Legacy
None (category is relatively new).
7. Code Models
These models are optimized for programming languages.
Actively Used
GPT-4.1 / GPT-5 Code – Code generation, refactoring, and reasoning.
Code LLaMA – Open-source coding assistant.
DeepSeek Code – Strong code reasoning and generation.
Largely Obsolete / Legacy
Early Codex models – Superseded by newer code-specialized LLMs.
8. Embedding Models
These models convert content into numerical vectors.
Actively Used
text-embedding-3-large – High-quality semantic embeddings.
Instructor – Task-aware embeddings.
Largely Obsolete / Legacy
Older sentence transformers – Used mainly in legacy systems.
9. Reranking Models
These models score and reorder retrieved documents.
Actively Used
Cohere Rerank – Production search relevance.
Cross-encoder MiniLM – Lightweight reranking.
Largely Obsolete / Legacy
Classic BM25-only ranking – Insufficient alone for modern RAG.
10. Reasoning Models
These models focus on structured, multi-step reasoning.
Actively Used
OpenAI o-series – Advanced multi-step reasoning.
Claude 3 Opus – Long-form analytical reasoning.
DeepSeek R1 – Explicit reasoning optimization.
Largely Obsolete / Legacy
None (reasoning specialization is expanding).
11. Tool-Calling / Agentic Models
These models are designed to invoke tools and APIs.
Actively Used
GPT-4.1 / GPT-5 – Native function and tool calling.
Claude 3 – Structured agent workflows.
Largely Obsolete / Legacy
Prompt-only tool chaining – Replaced by native tool APIs.
12. Fine-Tuned / Domain-Specific Models
These models are adapted for specific industries or tasks.
Actively Used
Medical, legal, finance-tuned models – Compliance and domain accuracy.
Largely Obsolete / Legacy
Static rule-based NLP systems – Replaced by fine-tuned LLMs.
13. Generative Image Models
These models generate images from prompts.
Actively Used
DALL·E 3 – High-quality image generation.
Stable Diffusion XL – Open image synthesis.
Midjourney – Creative and artistic generation.
Largely Obsolete / Legacy
Early GAN-based image generators – Lower quality and controllability.
14. Video Models
These models understand or generate video.
Actively Used
Sora – Text-to-video generation.
Runway Gen-2 – Video generation and editing.
Largely Obsolete / Legacy
Rule-based video synthesis – Rarely used today.
15. Hybrid RAG Models
These models are designed to work closely with retrieval systems.
Actively Used
LLMs combined with vector databases – Enterprise knowledge systems.
LangChain / LangGraph RAG – Orchestrated retrieval workflows.
Largely Obsolete / Legacy
Pure long-prompt stuffing – Inefficient and brittle.
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