Tracing the evolution, architecture, licensing traps, and version selection of mainstream model families — Qwen, DeepSeek, Claude, GPT, Gemini, Llama, Mistral, GLM, Kimi — with pick guidance for agent developers.
In 2026, AI models span seven major categories and more than 20 subcategories. This introduction to the AI Model Families series maps use cases to models and models to families, with current rankings and selection advice for each use case.
DeepSeek used MLA and MoE innovations to drive inference costs to an industry low. V4 Flash activates only 13B parameters while approaching frontier-model quality and ranks first by OpenRouter usage. This guide traces V1 through V4, the R1 reasoning branch, and how to choose each version.
Qwen is the most-downloaded model family on HuggingFace, spanning sizes from 0.8B to 2.4T. In August 2026, Alibaba open-sourced a Max-tier flagship for the first time (Qwen3.8-2.4T-A95B) — but swapped the customary Apache 2.0 license for custom terms. Meanwhile the other new release, Qwen3.8-27B, runs native vision on laptop-class hardware and is the only one shipping under Apache 2.0. This post traces the family from 2023 through generation 3.8, explains how the open line and the commercial line split apart, and helps you pick the right model at each tier.
GPT is OpenAI's LLM family, from 117M parameters in 2018 to the three-tier GPT-5.6 Sol/Terra/Luna lineup in 2026, serving 1B+ users and 2M enterprise customers. GPT-5.6 Sol leads LiveBench 81.1%, Terminal-Bench 2.1 88.8%, and Artificial Analysis Coding Agent Index 80 across multiple agentic benchmarks, while OpenAI's first open-weight model GPT-OSS ships under Apache 2.0.
Gemini is Google DeepMind's native multimodal LLM family, famed for a 1M-token context window and native video/speech input plus scientific reasoning. 3.1 Pro tops GPQA Diamond 94.1% and ARC-AGI-2 77.1% to claim science-reasoning dual crowns, at $2/$12—1/6 of Claude. 3.8 Flash delivers agentic coding results close to frontier models at $0.75/$3.75 (Terminal-Bench 2.1 89.4%; DeepSWE v1.1 73.7%), with the same introductory pricing across 3.6, 3.7, and 3.8.
Llama is Meta's open-source LLM family, with the largest enterprise deployment footprint and the most mature ecosystem. Llama 4 Scout (10M context) and Maverick (17B active / 400B total MoE) are the current open multimodal benchmarks, but Meta pivoted to closed-source Muse Spark in April 2026—Llama 4 is likely the last major open Llama, and its license is not truly open (Llama 4 Community License, separate license required above 700M MAU).
Mistral is Europe's most successful AI startup, cutting through the market with a 'smaller, faster, cheaper' strategy and European data-sovereignty positioning. Mistral Large 3 is Europe's strongest commercial LLM, Small 4 is the 24B efficiency king, and Medium 3.5 is the open Modified-MIT model optimized for agentic coding. Its moat is not technical scale but the 'European compliance' card.
Claude is Anthropic's closed-source LLM family, known for Constitutional AI training, agent capabilities, and coding performance. In July 2026, Opus 5 scored 96% on SWE-bench Verified to claim the coding crown, while Fable 5 led general capability at 83% on LiveBench. Four tiers (Fable / Opus / Sonnet / Haiku) span $1–$10, making this the only family in the series with zero open weights.
GLM is Zhipu AI (Z.ai)'s open LLM family from Tsinghua's KEG Lab. GLM-5.3 (2026/08) lifts coding +50% over the previous generation, hits 84.5% on CyberGym ahead of Anthropic Mythos 5 and OpenAI GPT-5.6 Sol, and scores 60 on the Artificial Analysis Intelligence Index tied with Kimi K3 for open-source #1. The only frontier open model trained entirely on Huawei Ascend.
Kimi is Moonshot AI's LLM family, born from ultra-long context. Kimi K3 (2026/07) is the world's first open 3T-class model—2.8T params, 104B active, 1M context, scoring 60 on the Artificial Analysis Intelligence Index tied with GLM-5.3 for open-source #1. Its Kimi Delta Attention brings a 2.5× scaling efficiency gain.
Cohere is the only family that ships generation, retrieval, reranking, and multilingual as distinct products. Command A runs 256K context on two GPUs at 111B, Embed v4 does mixed image-text retrieval, Rerank v4 handles 32K semi-structured data, and Aya covers 101 languages — a four-piece stack built for RAG. This post breaks down each pillar's positioning, licensing, and selection guide.
Grok is xAI's LLM family: founded July 2023, opened with a 314B MoE under Apache 2.0 in March 2024, and two and a half years later spans Grok 4.6 (500K, $2/$6, four reasoning levels), Grok 4 Fast (2M), Imagine for image/video, and Grok Build for terminal coding — its moat is distribution (X / grok.com / Tesla / Bedrock), not single-model supremacy. This post traces Grok 1→4.6, sub-line positioning, pricing, and licensing traps.
Apple Foundation Models (AFM) is Apple's closed-ecosystem AI family. It evolved from a 3B dense model with LoRA adapters in 2024 into five models in 2026. AFM 3 Core Advanced runs a 20B IFP sparse architecture on phones while activating only 1–4B parameters; Cloud Pro runs on Google Cloud NVIDIA GPUs and is refined through Gemini distillation. There is no public API price or third-party benchmark, and access is limited to Apple's Foundation Models framework.
DeepReinforce's Ornith 1.5 family, trained with self-improvement RL: the 397B flagship scores 86.0 on SWE-bench Verified, matching Claude Opus 4.8; the 35B-A3B activates only 3B parameters per token yet leads every coding benchmark in its class; the 9B runs on phones. MIT-licensed, fully open-source.
MiniMax started as a consumer chat app company, then M2.5 scored 80.2% on SWE-bench Verified at 1/10-1/20 the cost of Claude Opus; M3 (456B total / 45.9B active) became the first open-weight model to clear 59% on SWE-bench Pro, with 1M context powered by their novel Sparse Attention mechanism.
Nous Research doesn't pretrain — they fine-tune and do RL. Hermes 4 scores 96.3% on MATH-500, NousCoder-14B improves Qwen3-14B's coding ability by 7% using only 24K training samples. But the real moat is Hermes Agent: 236K GitHub stars, #19 globally, 3,000 contributors.
FLUX is Black Forest Labs' image-model family. The Stable Diffusion team launched it in August 2024 with a 12B rectified-flow transformer. Two years later it spans klein 4B ($0.014 and the only current Apache-2.0 model) / 9B, pro ($0.03), flex ($0.05), max ($0.07 with live web grounding), and open-weight 32B dev. FLUX 3 extends Self-Flow to video, synchronized audio, and robot actions. This guide covers the FLUX.1-to-FLUX 3 evolution, three-tier licensing, and model selection.
Speech models split into two lines. Whisper led ASR: its MIT-licensed 1.55B model drove transcription cost toward zero in September 2022; after v2, v3, and turbo cut the decoder from 32 layers to four, OpenAI moved to closed gpt-4o-transcribe. In TTS, ElevenLabs grew to an $11B valuation and $500M ARR, while Kokoro (82M, Apache-2.0) and Chatterbox preserved self-hosting. Speech-to-speech Realtime APIs are now rewriting live conversation.
Sora's February 2024 preview shocked the industry, but the landscape reversed in two and a half years: OpenAI closed the consumer Sora app in April 2026 and scheduled its API for retirement on September 24; Veo 3.1 became the narrative default with native audio and Flow; Kling 3.0 became a unified multimodal model with $240M annualized revenue; and Runway Gen-4.5 briefly led Artificial Analysis in a November 2025 snapshot while defending the professional market through enterprise workflows. This guide compares four families by generation, specifications, pricing, and use case.
Thinking Machines Lab (founded 2025 by Mira Murati, $2B seed at a $12B valuation) released Inkling in July 2026 under Apache 2.0 (975B total / 41B active params, 1M context, native multimodality, controllable thinking effort) plus a smaller Inkling-Small (276B / 12B), paired with the Tinker fine-tuning platform—turning customizability itself into the product.
Ling separates execution, Ring handles deep reasoning, and Ming covers multimodal tasks; the family prioritizes intelligence per unit of compute, so selection starts with workload, deployment budget, and modality.
Laguna is Poolside's agentic coding model family: XS 2.1 packs 33B-A3B into a 36GB Mac, while S 2.1 brings 118B-A8B with 1M context to 70.2% on Terminal-Bench 2.1 and 40.4% on DeepSWE, both open under OpenMDW-1.1.
Nex-N2.5 is Nex AGI's open agentic model family: mini scores 82.9 on OSWorld-G at 35B-A3B, Pro tops Claude Opus 5 with 87.4 at 397B-A17B, and Max leads the whole official table on BrowseComp with 92.6 at 1.6T, all open under Apache-2.0.
Muse Spark is Meta's closed-source agentic model line: version 1.3 combines a 1M-token context, multimodal inputs, and long-horizon tool loops. Standard pricing is $1.25/$4.25 per 1M input/output tokens, while Contributor drops to $0.10/$0.20 in exchange for training rights. It is not the next Llama; it is a separate product line built around models, APIs, and coding agents.
Gemma is Google's open-weights family paired with the closed-source Gemini flagship; Gemma 4 (E2B / E4B / 26B-MoE / 31B) released in April 2026 switched its license from Google Gemma Terms of Use to Apache 2.0 — the single most important change in this article.
pplx-embed is the embedding family Perplexity has been releasing since February 2026, in three lines: v1 single-vector (0.6B/4B, API at $0.004/$0.03 per 1M tokens), context embeddings (v1 plus a 9B v2 preview), and v2-late multi-vector (0.6B/9B, searches PDF page images directly). They solve different problems; v2 does not replace v1.
Apodex is a reasoning-first Mixture-of-Experts model family built by the Apodex team for complex long-horizon research, forecasting, and verifiable reasoning tasks. An agent runtime supplies file, data, code, and tool execution; the core API accepts text only.
Cohere's North series marks its first agentic coding model family. North Mini Code (30B total / 3B active sparse MoE) is purpose-built for code generation and automated development, with 256K context and free access via OpenRouter as `north-mini-code:free`.
OpenRouter lists long context, image input, and tools for Dots3-Note Preview; verified weight access and licensing remain necessary for self-hosting.
LFM2.5-2.6B is an on-device hybrid reasoning model; checkpoint and OpenRouter context limits differ, with license and data terms to check before deployment.
LongCat-Flash and LongCat-2.0 are Meituan open-weight MoE models. This guide explains dynamic compute, LSA, long context, tool use, and the difference between model specifications and hosted endpoints.
Nemotron covers text reasoning, multimodal understanding, and safety classification. Ultra, Super, Lightning, Nano Omni, and Content Safety differ in architecture, context, and licensing; model specifications and API limits must be checked separately.