Every large language model release, sourced and tracked over time.

SpaceXAI's "Opus-class" agentic flagship, released July 8, 2026 — the first Grok model trained jointly with the coding startup Cursor (Anysphere), on trillions of tokens of real Cursor usage data plus STEM tasks, research papers, and other knowledge work. Targets software engineering, agentic tasks, and knowledge work, with explicit strength in legal and finance use cases (SpaceXAI claims the top spot on the Harvey Legal Agent Benchmark). A Mixture-of-Experts model reported to be built on a ~1.5-trillion-parameter "V9" foundation. Vendor benchmarks are mixed against Anthropic's Opus 4.8 — ahead on DeepSWE 1.0 and Terminal-Bench 2.1, behind on DeepSWE 1.1 and SWE-bench Pro — but markedly more token-efficient (~15,900 output tokens on SWE-bench Pro tasks, ~4.2x fewer than Opus 4.8) and served at ~80 tokens/sec. Base pricing $2/$6 per Mtok; Cursor lists a faster variant at $4/$18. Available in Grok Build (default model), Cursor (all plans), and the SpaceXAI console; initially unavailable in the EU (expected mid-July). xAI was absorbed by SpaceX in Feb 2026 and rebranded SpaceXAI.

The general-availability release of Tencent's third-generation Hunyuan (Hunyuan 3.0), officially launched and open-sourced on July 6, 2026 after April's "Hy3 preview". A 295B-total / 21B-active Transformer MoE with an additional 3.8B multi-token-prediction (MTP) layer and a 256K-token context, offering three selectable inference modes that blend fast and slow thinking. Positioned as a leading open model for its size and cost efficiency, with standout results in coding, search, and scientific reasoning: Tencent reports it rivals flagship open models such as GLM-5.2 and DeepSeek-V4 (at 2-5x the active parameters) and matches or surpasses GPT-5.5 on several science benchmarks. Vendor-reported scores include 78.0 on SWE-bench Verified and 57.9 on SWE-bench Pro. Now Apache-2.0 licensed (the preview used Tencent's community license), with weights on Hugging Face (tencent/Hy3) and ModelScope and a free two-week API route on OpenRouter (tencent/hy3:free) through July 21, 2026. Deeply integrated into WeChat and Tencent's core products.

A deployment-optimized open-weight model from NVIDIA, released July 6, 2026 — a compressed variant of Nemotron-3-Super-120B-A12B produced with "Iterative Puzzle", a post-training compression framework that jointly prunes MoE experts, active-parameter budget, and Mamba state to boost inference efficiency while preserving accuracy. Reduces the parent from 120.7B total / 12.8B active to 75.3B total / 9.3B active, keeping the hybrid Mamba-Transformer LatentMoE architecture with Multi-Token Prediction. Delivers ~2x higher server throughput than Nemotron-3-Super on a single 8xB200 node at matched user throughput and raises sustainable 1M-token single-H100 concurrency from 1 to 8 requests. Targets collaborative agents, chatbots, RAG, complex instruction-following, and long-context reasoning across English, code, and six other languages. Shipped in BF16, FP8, and NVFP4 variants under the OpenMDW-1.1 license.

Poolside's open-weight small coding model: a 33B-total / 3B-active Mixture-of-Experts built for agentic coding and long-horizon work on a local machine, served at 256K context. An upgraded XS.2 (same architecture) that lifts SWE-bench Multilingual by 5.4 points to 63.1% and improves terminal-style tasks. Ships with open-weighted DFlash speculator (draft) models for each checkpoint that roughly double local tokens/sec, plus BF16/FP8/INT4/NVFP4 quantized checkpoints; supported in vLLM, SGLang, TensorRT-LLM, HF transformers, and Ollama (llama.cpp coming). Newly relicensed under the fully permissive OpenMDW-1.1. Available free on Hugging Face and via a free OpenRouter tier, with paid API pricing of $0.10 / $0.20 / $0.05 per 1M input / output / cache-read tokens. Its predecessor Laguna XS.2 sunsets on Poolside's API one week after launch.

Anthropic's most agentic Sonnet model yet, with performance approaching Claude Opus 4.8 at a lower price. Built for coding, tool use (browsers and terminals), and autonomous multi-step agentic work, with selectable effort levels up to xhigh. A substantial upgrade over its predecessor Sonnet 4.6 on reasoning, tool use, coding, and knowledge work, with gains shown on SWE-bench, OSWorld-Verified, BrowseComp, and Humanity's Last Exam. The default model on the Free and Pro plans and available to Max, Team, and Enterprise users; in Claude Code and via the Claude API as claude-sonnet-5. Uses an updated tokenizer (same approach as Opus 4.7). Ships with real-time cyber safeguards enabled by default. Introductory API pricing of $2/$10 per Mtok through Aug 31, 2026, then standard $3/$15.

Meituan's open-weight flagship: a 1.6-trillion-parameter Mixture-of-Experts model (~48B active per token, dynamically routed between ~33B and ~56B) with a 1M-token context, built for agentic coding. Notable as the largest Chinese model trained — for both pre-training and inference — entirely on a ~50,000-card cluster of domestic Chinese AI chips (Meituan's use of the Huawei Collective Communication Library points to Huawei Ascend hardware), and the first trillion-parameter model Meituan claims completed full-process training on home-grown compute. Vendor-reported software-engineering results: 59.5 on SWE-bench Pro (ahead of GPT-5.5's 58.6), 70.8 on Terminal-Bench 2.1, and 77.3 on SWE-bench Multilingual, with overall quality positioned as comparable to Gemini 3.1 Pro (self-reported, not yet independently verified). Open-sourced under the MIT license with weights on Hugging Face and GitHub; follows LongCat-Flash (560B, Sep 2025) and the multimodal LongCat-Next (Mar 2026).

OpenAI's GPT-5.6 series umbrella row. Officially previewed June 26, 2026 as three durable capability tiers — Sol (flagship), Terra (balanced, for everyday work), and Luna (fast and affordable) — introduced with a new `max` reasoning effort for deeper reasoning and an `ultra` mode that leverages subagents to accelerate complex work. In the GPT-5.6 naming system the number marks the generation while Sol/Terra/Luna are tiers that can advance on their own cadence. Initially a limited preview via the API and Codex for a small group of vetted partners (after U.S. government review), with general availability across ChatGPT, Codex, and the API planned in the following weeks.

Balanced, everyday-work tier of OpenAI's GPT-5.6 series, officially previewed June 26, 2026. OpenAI positions Terra as competitive with GPT-5.5 while being roughly 2x cheaper. Shares the series' new `max` reasoning effort and `ultra` subagent mode and OpenAI's GPT-5.6 safety stack. Begins as a limited preview via the API and Codex for vetted partners after U.S. government review, with broad availability planned in the following weeks. Priced at $2.50 / $15 per million input/output tokens.

Flagship tier of OpenAI's GPT-5.6 series, officially previewed June 26, 2026 — OpenAI's strongest model to date. Adds a new `max` reasoning effort for the deepest reasoning and an `ultra` mode that uses subagents to accelerate complex work. Sets a new state of the art on Terminal-Bench 2.1 (command-line, agentic coding) and shows broad gains in long-horizon biology (GeneBench v1) and cybersecurity (ExploitBench, ExploitGym), paired with OpenAI's most robust safety stack and a phased release. Begins as a limited preview via the API and Codex for a small group of vetted partners after U.S. government review, with general availability planned in the following weeks; also launching on Cerebras at up to 750 tokens/sec in July. Priced at $5 / $30 per million input/output tokens.

Fast, low-cost tier of OpenAI's GPT-5.6 series, officially previewed June 26, 2026 — the most affordable model in the family, bringing strong capability at OpenAI's lowest cost. Shares the series' capability-tier naming and GPT-5.6 safety stack. Begins as a limited preview via the API and Codex for vetted partners after U.S. government review, with broader availability planned in the following weeks. Priced at $1 / $6 per million input/output tokens.

The low-cost, low-latency tier of ByteDance's Seed 2.1 family (served as Doubao-Seed-2.1-turbo), built for large-scale production with full features and performance ByteDance positions as comparable to Seed 2.1 Pro. Shares the family's coding, long-chain agent, and multimodal-understanding focus and 256K-token context, priced for high-volume online calls. Proprietary; available via Doubao and Volcano Engine. List price ¥3 / ¥15 per million input/output tokens — roughly half the Pro tier.

ByteDance's flagship next-generation agent model (served as Doubao-Seed-2.1-pro), built for the "coding and agent era." A deep-thinking model tuned for strong demand understanding, long-horizon planning, and continuous self-repair across complex coding, long-chain agents, and multi-step engineering delivery, with a 256K-token context. ByteDance reports its core coding, agent, and multimodal capabilities are comparable to GPT-5.5, with the highest score on GDPVal, top-tier results on the Agents' Last Exam, the highest score on MobileWorld, and SOTA results across several visual and video-understanding benchmarks (CharXiv-RQ, MeasureBench, TVBench, TOMATO). Proprietary; available via Doubao and Volcano Engine. List price ¥6 / ¥30 per million input/output tokens.

Sakana AI's frontier-class orchestration model: a single ~7B language model trained to coordinate a swappable pool of external frontier LLMs (model selection, delegation, verification, and synthesis happen internally), exposed behind one OpenAI-compatible API. The Ultra tier is tuned for maximum answer quality on hard, multi-step problems and coordinates a deeper, fixed pool of expert agents. Sakana reports it stands shoulder-to-shoulder with Anthropic's Fable 5 and Mythos Preview across coding, science, and reasoning benchmarks while routing around single-vendor/export-control risk. Current model ID fugu-ultra-20260615; vendor-reported scores include 95.5 GPQA-D, 73.7 SWE-Bench Pro, 93.2 LiveCodeBench, and 50.0 Humanity's Last Exam.

Sakana AI's orchestration model: a single language model that delivers a full multi-agent system behind one OpenAI-compatible API, dynamically routing tasks across a swappable pool of frontier LLMs (including recursive calls to itself). The base tier balances strong performance with low latency as an everyday default for coding, code review, and chat, and lets teams opt specific agents out of the pool for data/privacy/compliance needs. Released alongside Fugu Ultra on June 22, 2026; vendor-reported scores include 95.5 GPQA-D, 92.9 LiveCodeBench, and category-leading SciCode and long-context results.

A speculative Z.ai frontier model tracked after Z.ai founder Jie Tang responded to Elon Musk's prediction of a Chinese Fable 5-class model by saying it would not take that long. Name, architecture, weights, and launch timing remain unconfirmed.

Moonshot's open coding-focused agentic model built on K2.6, with native vision/video input, forced thinking mode, and stronger long-horizon software-engineering performance.

Z.ai's latest open flagship for long-horizon coding, agentic engineering, and million-token workflows, adding IndexShare sparse-attention reuse over GLM-5.1.

Native multimodal MiniMax model with a one-million-token context, sparse attention, and agentic coding/cowork positioning.

An open-weight text-diffusion model built on the Gemma 4 26B-A4B MoE backbone (25.2B total / 3.8B active). Denoises text in parallel 256-token blocks for up to ~4x faster generation (1,000+ tok/s on an H100), with a 256K context and text, image, and video input. Apache-2.0.

The public, guardrailed sibling of Claude Mythos 5 and Anthropic's most capable widely released model, built for long-horizon agentic work, coding, vision, and knowledge workflows. Launched June 9, 2026 across the Claude API, AWS, and Microsoft Foundry, then suspended three days later under a U.S. export-control directive. Anthropic says those controls were lifted June 30 and Fable 5 was restored globally on July 1 across Claude Platform, Claude.ai, Claude Code, and Claude Cowork, with cloud partner access being re-enabled. Its safeguards route flagged cybersecurity, biology/chemistry, and distillation requests to Claude Opus 4.8.

Cohere's first developer-focused model and the first in its North family of code agents. A 30B-total / 3B-active MoE for agentic coding with a 256K context and up to 64K output, sized to run locally for enterprise coding agents. Apache-2.0.

Unisound's new-generation, general-purpose "native agentic" large model, built for task execution: it can autonomously decompose and advance complex real-world workflows of 100+ steps rather than single-turn Q&A. Unisound frames it around "high intelligence density x high token value" and reports ~25% lower thinking-token consumption. Available via the Unisound Token Hub.

NVIDIA's largest Nemotron 3 open-weight hybrid Mamba-Transformer MoE, tuned for agentic reasoning, coding, planning, and tool calling.

Multimodal sibling of Qwen3.7-Max that adds vision input and GUI grounding for screen perception, browser automation, and hybrid GUI+CLI agent workflows. 1M-token context; closed-weights and API-only. Previewed at the May 2026 Alibaba Cloud Summit and reached general availability in June 2026 at a low price point ($0.40/$1.60 per 1M tokens).

A dense 12B member of the Gemma 4 family with a unified, encoder-free multimodal architecture: vision and audio are projected straight into the LLM backbone. First medium-size Gemma to natively ingest audio; runs on a 16GB laptop. 256K context, Apache-2.0.

Microsoft's first in-house frontier reasoning model, unveiled at Build 2026. A sparse MoE (~35B active, 256K context) trained entirely on commercially licensed data without third-party distillation. Microsoft reports 97.0% on AIME 2025 and coding parity with Claude Opus 4.6 on SWE-bench Pro.

An inference-efficient agentic coding model from Microsoft (~5B active parameters), trained from the ground up on clean, traceable, enterprise-grade data without third-party distillation. Rolling out in GitHub Copilot; Microsoft reports a +16-point SWE-bench Pro lead over Claude Haiku 4.5.

StepFun's high-efficiency multimodal sparse-MoE successor to Step-3.5-Flash: a ~196B-total / ~11B-active vision-language model with native image and video understanding, a 256K context, and selectable reasoning tiers (high/medium/low). Tuned for coding agents and search workflows.

Anthropic's most capable model, with strengthened agentic and long-running task performance.

Open-weight agentic model from MiniMax focused on real-world software engineering, office tasks, tool use, and self-improving training workflows.

Alibaba's proprietary flagship in the Qwen3.7 "Agent Frontier" line — a text-only sparse-MoE model with a 1M-token context, tuned for long-horizon agentic, coding, and reasoning workloads. Parameter count is undisclosed; access is API-only via Alibaba Cloud Model Studio / DashScope (and aggregators such as OpenRouter).

Announced at Google I/O 2026; emphasizes deep multimodal reasoning over a 2M-token context. Recent reporting says the broad launch slipped from June toward July while testers continue using it in Google Antigravity and LMArena.

Google's fast, cost-efficient Gemini 3.5 tier, unveiled at I/O 2026. Multimodal over a 1M-token context and tuned for agentic and coding workflows; Google says it beats Gemini 3.1 Pro on coding and tool-use while running ~4x faster.

Dense 27B that punches far above its weight on agentic coding — easy to self-host on a single GPU node.

Baidu's flagship ERNIE 5.1, derived from ERNIE 5.0 by extracting an optimal sub-network from its elastic sub-model matrix — compressing total parameters to ~1/3 and active parameters to ~1/2 of ERNIE 5.0 while reaching leading performance at only ~6% of the pre-training compute of comparable models. A Mixture-of-Experts model trained with a disaggregated fully-asynchronous RL stack and a multi-teacher on-policy-distillation pipeline, tuned for agentic execution, reasoning, world knowledge, and creative writing. Vendor-reported results: 99.6 on AIME26 (with tools, second only to Gemini 3.1 Pro), GPQA and MMLU-Pro approaching leading closed models, surpassing DeepSeek-V4-Pro on τ³-bench and SpreadsheetBench-Verified, and ranking 1st among Chinese models / 4th globally (score 1223) on the LMArena Search Arena. Proprietary; served via ERNIE Bot, Baidu AI Studio, and the Qianfan platform.

OpenAI's limited-preview cybersecurity model for vetted defenders in Trusted Access for Cyber. It is tuned for more permissive authorized security workflows such as vulnerability triage, patch validation, malware analysis, red teaming, and controlled exploit validation, but is not generally available.

OpenAI's May 2026 GPT-5.5 release: a stronger frontier workhorse positioned for deep reasoning, coding, multimodal analysis, and long-context agent workflows. OpenAI lists an 800K-token input context and 128K-token output limit, with API pricing at $3 / $20 per million input/output tokens.

xAI's agentic flagship with a 1M-token context and aggressive API pricing.

Efficient V4 companion model with 284B total / 13B active parameters and the same one-million-token context window.

Preview-series sparse MoE flagship with a one-million-token context window and 1.6T total / 49B active parameters.

Tencent's third-generation Hunyuan, rebuilt from scratch in ~90 days and open-sourced as the "Hy3 preview". A 295B-total / 21B-active Transformer MoE (80 layers, 192 experts with top-8 routing, plus a 3.8B multi-token-prediction layer) with a 256K-token context, positioned as a leading open reasoning-and-agent model for its size with strong cost efficiency. Vendor-reported results: 74.4 on SWE-bench Verified, 54.4 on Terminal-Bench 2.0, and 70.2 on WideSearch, with strong STEM-olympiad performance. Open weights on GitHub and Hugging Face under Tencent's community license.

Tencent Hunyuan open-weight fine-grained MoE model with 80B total parameters and 13B active parameters, optimized for agentic tool use.

Xiaomi's open-weight flagship: a 1.02T-parameter Mixture-of-Experts model with ~42B active parameters, a hybrid-attention architecture, and a 1M-token context window. Tuned for frontier-class agentic coding and long-horizon tasks (sustaining 1000+ tool calls with a proper harness). Open-sourced under the MIT license with weights and tokenizer on Hugging Face.

Xiaomi's open-weight sparse-MoE model: ~310B total parameters with ~15B active, trained on ~48T tokens, with a 1M-token context window. Shipped alongside the larger MiMo-V2.5-Pro under the MIT license.

Z.ai agentic-engineering follow-up to GLM-5, with stronger coding performance and better long-horizon tool-use behavior.

Meta's new frontier model behind Meta AI for U.S. users, identified in reporting as the public release of the former Avocado effort and positioned to compete with Gemini, GPT, and Claude on multimodal assistant tasks.

The restricted sibling of Claude Fable 5, sharing the same underlying Mythos-class model with fewer safeguards for vetted defensive-security and research use. Anthropic disclosed Mythos Preview on April 7, 2026, upgraded approved Project Glasswing users to Mythos 5 on June 9, suspended access under a U.S. export-control directive on June 12, and restored limited access for approved U.S. organizations on July 1 while it continues expanding the trusted-access program.

Google DeepMind's Gemma 4 advanced-reasoning open model for personal computers, part of the April 2026 Gemma 4 family.

Z.ai's native-multimodal vision agent: the first GLM model designed from the start as a multimodal agent, taking image, video, and text input and producing agent-oriented output (tool calling, task decomposition, and GUI interaction). Served via API with a ~203K-token context.

Moonshot's open native multimodal agentic model for long-horizon coding, visual interface generation, and autonomous tool orchestration.

Dense 128B open-weight model with a 256k context and strong coding performance for its size.

Open-weight hybrid Mamba-Transformer MoE designed for collaborative agents and high-volume enterprise workflows.

StepFun's Apache-licensed sparse MoE model for fast agentic execution, coding, math, browsing, and tool-use workflows.

Historical rumor/codename row retained for provenance. Recent reporting identifies the public productized model as Muse Spark, now tracked separately in the catalog.

Apache-licensed Indian-context MoE from Sarvam AI, optimized for reasoning, coding, agentic tasks, and 22 Indian languages.

Workhorse GPT-5 release with a dedicated Thinking mode; widely deployed across ChatGPT and the API.

The flagship of Alibaba's small dense Qwen3.5 models. Independent analysis (Artificial Analysis) rated it the most intelligent model under 10B parameters at launch — roughly double the score of the next-closest sub-10B models — and the most intelligent multimodal model under 15B, leading peers on MMMU-Pro (~69%). A dense 9B with native vision, a 262K-token context, and the Qwen3.5 family's unified hybrid thinking / non-thinking mode. Native weights are BF16; in 4-bit it needs ~6GB, within reach of consumer laptops. High intelligence comes with heavy reasoning token usage (~260M output tokens to run the Intelligence Index).

A dense 4B in Alibaba's small Qwen3.5 family, rated by Artificial Analysis as the most intelligent model under 5B parameters at launch — outscoring several 7B–9B peers despite roughly half the parameters. Native vision, a 262K-token context, and the family's hybrid thinking / non-thinking mode; Apache-2.0 licensed. Scores ~65% on MMMU-Pro multimodal reasoning and runs in ~3GB at 4-bit, suitable for lightweight on-device agents.

A dense 2B Qwen3.5 model built for high-throughput, low-latency edge and on-device use. Despite its size it matches a 7B-class peer on Artificial Analysis's Intelligence Index. Apache-2.0, with native vision, a 262K-token context, and the family's hybrid thinking / non-thinking mode; runs in under 2GB at 4-bit, fitting laptops and smartphones.

The smallest Qwen3.5 model — a dense 0.8B designed for the most constrained on-device deployments, operating in non-thinking (instruct) mode by default. Apache-2.0, with native vision, a 262K-token context, and the family's hybrid thinking / non-thinking mode; needs roughly 2GB of VRAM and runs under 2GB at 4-bit, targeting smartphones and embedded hardware. Notable for a sub-1B model, it still scores ~26% on MMMU-Pro multimodal reasoning.

Native vision-language MoE supporting 201 languages with a 1M-token context.

Generally available multimodal flagship with native tool use and a 2M-token context.

Z.ai flagship for complex systems engineering and long-horizon agentic tasks, scaling the GLM line to 744B total / 40B active parameters.

Introduced genuinely autonomous multi-file coding and stronger computer use.

OpenAI's February 2026 Codex update, optimized for agentic software engineering in ChatGPT, Codex, and the API. GPT-5.3-Codex improves code quality, patch reliability, repository-scale reasoning, and long-running autonomous coding workflows while keeping the 400K-token input context and 128K-token output limit of the Codex line.

Apache-licensed Qwen3-Next coding-agent model with 80B total / 3B active parameters, 256K context, and long-horizon tool-use training.

Open multimodal Kimi model that adds native visual agentic intelligence, instant and thinking modes, and agent-swarm workflows on top of the K2 base.

Coding-focused GLM release with improved multilingual agentic coding, terminal tasks, tool use, and interface generation.

OpenAI's December 2025 Codex model for agentic coding, released after GPT-5.2 with stronger repository understanding, code generation, and tool-use behavior for software engineering agents. The API model is listed with a 400K-token input context, 128K-token output limit, and $1.25 / $10 per million input/output tokens.

Ai2's fully open thinking model with public weights, code, data, checkpoints, and training details across the OLMo 3 pipeline.

Efficient Nemotron 3 MoE checkpoint for agentic reasoning and coding, activating about 3B parameters while supporting 1M-token contexts.

OpenAI's December 2025 GPT-5.2 general model release, positioned as a stronger default for reasoning, coding, vision, instruction following, and long-context analysis. OpenAI lists a 400K-token input context, 128K-token output limit, and $2 / $12 per million input/output tokens.

Open 106B-class vision-language model with native multimodal function calling for visual agents.

Mistral's largest open-weight MoE, aimed at frontier reasoning while remaining self-hostable.

Reasoning-first agent model that adds DeepSeek Sparse Attention and thinking directly inside tool-use workflows.

High-compute reasoning variant of V3.2, positioned for olympiad-level math, programming, and other deep reasoning tasks.

Liquid AI hybrid model for efficient CPU/GPU/NPU local deployment, using short convolutions plus attention blocks.

Open K2 reasoning-agent variant that interleaves step-by-step thinking with tool calls and supports stable 200-300 step tool-use trajectories.

MIT-licensed hybrid linear-attention model using Kimi Delta Attention, built for million-token contexts with much lower KV-cache usage.

Anthropic's fast, low-cost Claude 4.5 model, released in October 2025 for latency-sensitive coding, tool-use, and customer-facing agent workloads. Anthropic positions it as bringing near-Sonnet capability to the Haiku tier at substantially lower cost and higher speed.

Agentic reasoning and coding upgrade over GLM-4.5, expanding the text context window from 128K to 200K tokens.

Experimental checkpoint that introduced DeepSeek Sparse Attention as an efficiency bridge between V3.1-Terminus and V3.2.

Anthropic's September 2025 Sonnet release, positioned as its strongest model for coding, agents, and computer-use workflows at launch. Proprietary API model with text, vision, and code capabilities, 200K context, and Sonnet-tier list pricing.

Stability update to V3.1 focused on language consistency, code-agent reliability, and search-agent behavior.

September 2025 K2 update with stronger agentic coding, better frontend generation, and a doubled 256K context window.

Google's open multimodal model: 128k context, 140+ languages, runs on a single GPU.

Hybrid thinking/non-thinking release that upgraded tool calling, long-context training, and agent task performance.

ByteDance Seed's Apache-licensed long-context reasoning and agent model, with controllable thinking budgets and a native 512K context.

Rumored successor to DeepSeek R1. Reports say development and launch timing were affected by hardware constraints around Huawei Ascend training and Nvidia availability; final specs, license, and release date remain unconfirmed.

Vision-language GLM based on GLM-4.5-Air, covering image, video, document, grounding, and GUI-agent tasks.

Rumored next major Grok model. Elon Musk said after GPT-5's launch that Grok 5 would arrive before the end of 2025, but no broad public Grok 5 release is logged in this catalog yet.

Smaller gpt-oss reasoning model optimized for local inference on systems with about 16GB of memory.

OpenAI's larger open-weight reasoning model, a 117B-total / 5.1B-active MoE with 128K context for local and self-hosted deployment.

Anthropic's August 2025 Opus point release, focused on stronger coding, reasoning, and agentic reliability over Claude Opus 4. Proprietary API model with text, vision, and code capabilities.

Google's enhanced Gemini 2.5 reasoning mode for harder math, science, coding, and multimodal analysis. Previewed at Google I/O 2025 and later made available to Gemini app subscribers, Deep Think uses more deliberative reasoning for complex prompts.

A hybrid attention + state-space-model (SSM) design that matches 70B-class models with fewer parameters.

Open agentic, reasoning, and coding foundation model that marked Z.ai international rebrand and MIT-licensed GLM push.

Compact GLM-4.5 companion with 106B total / 12B active parameters for efficient agentic reasoning and coding.

Google's lowest-latency, lowest-cost Gemini 2.5 tier, designed for summarization, classification, extraction, routing, and other high-volume production tasks. Proprietary API model with a 1M-token context and multimodal support.

Alibaba Qwen's large open coding-agent model: a 480B-total / 35B-active MoE released under Apache-2.0, tuned for code generation, repository-level software engineering, tool calling, and long-horizon agent workflows with a 256K-token native context.

LG AI Research's unified model with non-reasoning and reasoning modes, agentic tool use, and English, Korean, and Spanish support.

Original open K2 post-trained model: a 1T-parameter MoE optimized for coding, reasoning, and tool-using agentic workflows.

xAI's fourth-generation Grok line, preceding the later 4.x API updates already tracked in the catalog.

Hugging Face's fully open 3B multilingual long-context model with optional reasoning mode and 128K context.

Baidu's open ERNIE 4.5 language MoE, part of a 10-variant Apache-licensed model family built with heterogeneous multimodal MoE training.

Baidu's largest ERNIE 4.5 vision-language MoE, supporting text, image, and video inputs with thinking and non-thinking modes.

Updated MIT-licensed Kimi-VL reasoning model with better multimodal reasoning, video understanding, high-resolution perception, and lower thinking-token use.

MIT-licensed coding LLM trained with repository-level reinforcement learning for software issue resolution.

Google's faster, lower-cost Gemini 2.5 model for high-throughput multimodal and agentic workloads. It brought Gemini 2.5's reasoning improvements to a production Flash tier with a 1M-token context and broad text, image, audio, video, and coding support.

Open Apache-licensed hybrid-attention reasoning model with 456B total / 45.9B active parameters and a native 1M-token context.

Mistral's first dedicated reasoning model family, released in Small open-weight and Medium enterprise/API tiers.

Open-weight 24B reasoning model from Mistral's Magistral family, popular for local reasoning experiments.

Major R1 reasoning update with stronger math, programming, general logic, function calling, and reduced hallucinations.

First Claude 4 Opus model, positioned for long-running agentic and coding work before the 4.x point releases.

ByteDance Seed reasoning model focused on long-horizon thinking and problem solving.

Sarvam's medium-scale open model for multilingual Indian-language chat, reasoning, and translation tasks.

Mistral and All Hands AI's open coding-agent model, released as a 24B Apache-2.0 research preview for software engineering tasks. Devstral is optimized for repository navigation, issue resolution, and agentic coding and is available via Hugging Face and Mistral's API.

Google's mobile-first Gemma 3n model variant, built with a MatFormer-style architecture for efficient on-device multimodal inference. The E4B variant has roughly 4B effective parameters, supports text, vision, audio, and video-oriented use cases, and is released under Gemma terms.

Mistral's May 2025 enterprise workhorse model, positioned as a high-performance, lower-cost alternative to larger proprietary systems for coding, STEM, enterprise search, and multilingual workloads. Mistral lists API pricing at $0.40 / $2 per million input/output tokens and offers hosted and enterprise deployment paths.

Phi-4 reasoning-specialized model family for math, science, and chain-of-thought style tasks.

Granite 3.3 text update for enterprise chat, RAG, and instruction-following workflows.

Largest open Qwen3 MoE, introducing hybrid thinking/non-thinking modes and 119-language coverage.

Open audio foundation model for audio understanding, generation, speech recognition, audio QA, captioning, and speech conversation.

Efficient MIT-licensed vision-language MoE for OCR, image/video understanding, long documents, and OS-style agent tasks.

Reasoning model released alongside o4-mini with tool use, image reasoning, and stronger agentic problem solving.

API model family focused on coding, instruction following, and one-million-token long-context work.

Meta's flagship open-weight MoE; highest MMLU among open models at release.

Efficient open-weight MoE designed for very long context on modest hardware.

Meta's announced but unreleased Llama 4 teacher model: a multimodal MoE with 288B active parameters and nearly 2T total parameters. Meta says it was still training when Scout and Maverick shipped and that those released models were distilled from Behemoth.

Open Llama Nemotron reasoning model from NVIDIA's 2025 Nemotron family.

Local omni-modal Qwen model that supports text, image, audio, video, and speech generation in a 7B package.

Post-R1 V3 update with improved reasoning, front-end coding, Chinese writing, search, and function calling.

Reasoning-focused Gemini 2.5 model that made thinking a core part of Google's flagship model line.

Apache-licensed Small update adding vision and a 128K context window to the efficient 24B line.

Baidu's reasoning model released alongside ERNIE 4.5 before the open ERNIE 4.5 weights.

A fully open model — weights, data, and training code all public — and the first such to beat GPT-3.5 / GPT-4o mini.

Enterprise-grade model tuned for RAG, tool use, and multilingual business workloads.

Granite 3.2 update with reasoning controls and multimodal/document-oriented Granite variants.

Anthropic's first hybrid-reasoning Sonnet. Shut down May 11, 2026 as the 4.x line matured.

MIT-licensed 16B/3B-active MoE trained with Moonshot's scalable Muon optimizer experiments.

Nous reasoning-oriented Hermes model trained to combine concise answers with optional deep reasoning traces.

xAI's third-generation model family, introduced with stronger reasoning, search, and coding modes.

Popular local assistant model tuned for coding, math, function calling, and agentic workflows.

A latency-optimized 24B dense model under Apache-2.0 — a popular local-deployment workhorse.

Proprietary MoE flagship for the Qwen2.5 generation, released through Qwen Chat and Alibaba Cloud APIs.

Vision-language Qwen2.5 model for image, document, video, and agentic visual grounding tasks.

Doubao 1.5 Pro update positioned for stronger multimodal, reasoning, and agentic work in Volcano Engine.

Breakout open reasoning model trained with large-scale reinforcement learning and released with weights under MIT.

Moonshot's multimodal reinforcement-learning reasoning model, reported as matching OpenAI o1 on math, coding, and multimodal reasoning.

Open MiniMax generation with MiniMax-Text-01 and MiniMax-VL-01 long-context models.

The 671B/37B-active MoE release that made DeepSeek a central open-model lab before the R1 breakthrough.

Second-generation StepFun foundation model line with larger-scale multimodal and reasoning ambitions.

IBM's enterprise-focused open model with a 128k context, Apache-2.0 licensed.

UAE's TII open model designed to run on light infrastructure, including laptops.

Cohere's smallest, fastest R-series model, tuned for RAG and tool use on modest hardware.

A 14B dense model that rivals far larger ones on math and reasoning, under a permissive MIT license.

First Gemini 2.0 release, built for native multimodal input/output, tool use, and agentic product integrations.

EXAONE 3.5 32B open-weight model for bilingual reasoning, coding, and long-context tasks.

Late-2024 70B Llama update delivering much of the 405B instruction-following quality at lower serving cost.

General release of OpenAI's o1 reasoning model with stronger deliberative reasoning and multimodal ChatGPT integration.

AWS-native multimodal model with a 300k context; size and architecture undisclosed.

Lower-cost multimodal Nova understanding model for text, image, and video inputs.

Qwen's first public reasoning-preview model, aimed at math, coding, and deliberate problem solving.

Ai2's post-trained open instruction model line, scaling the Tulu recipe to Llama 3.1 405B.

Reasoning-preview model exposed in DeepSeek Chat ahead of the open DeepSeek-R1 release.

Code-specialized Qwen2.5 model family, with the 32B checkpoint as the flagship open coding model.

Tencent's 389B total / 52B active open-weight Transformer MoE, released with a 256K pretraining context and 128K instruct context.

Compact on-device model family trained on 11T tokens, popular for lightweight local chat and experimentation.

Fast, lower-cost Claude 3.5 model for latency-sensitive coding, tool-use, and customer-facing workloads.

Sarvam's 2B open model trained for ten major Indian languages.

Apache-licensed Granite 3.0 text model, part of IBM's push toward enterprise-friendly open models.

01.AI's MoE API model that reached the global top-10 on Chatbot Arena, strong in Chinese, math, and coding.

Small Mistral model line optimized for edge and low-latency workloads.

NVIDIA-tuned Llama 3.1 70B instruction model optimized with Nemotron reward and alignment recipes.

First Llama family release with native vision models, alongside smaller edge-oriented 1B and 3B text models.

Open multimodal model family trained for strong image understanding, pointing, and visual grounding.

Broad Qwen2.5 foundation-model update spanning general, coding, math, and multimodal descendants.

Mistral's first open multimodal model, adding image understanding to a Mistral text backbone.

OpenAI's first public reasoning-model preview, optimized to spend more inference time on hard math, coding, and science tasks.

01.AI's compact code model trained for repository-scale programming and code completion tasks.

Unified DeepSeek V2 generation combining general-chat and coding strengths before the V3 series.

Tencent's faster, lower-cost Hunyuan update before the open Hunyuan-Large model card.

Fully open sparse MoE model with 7B total and about 1B active parameters.

Israel's AI21 hybrid Mamba-Transformer MoE, with a 256k context and strong long-document throughput.

Phi-3.5 mixture-of-experts model, scaling Microsoft's small-model line while preserving efficient active parameters.

Large Hermes 3 instruction-tuned model built on Meta's Llama 3.1 405B.

Second-generation Grok release with Grok-2 and Grok-2 mini for chat, coding, reasoning, and image-enabled product experiences.

LG's first open-weight EXAONE model, a compact bilingual instruction model for Korean and English.

8B vision-language model for local image, multi-image, OCR, and video understanding, with llama.cpp and Ollama support.

Meta's first frontier-scale open Llama model, with 405B parameters, 128K context, multilingual support, and tool-use improvements.

Apache-licensed 12B model co-developed with NVIDIA, including a 128K context window and strong multilingual tokenization.

Second-generation Gemma model, improving open-weight quality and efficiency at 9B and 27B sizes.

Major Sonnet upgrade that became Anthropic's default high-intelligence workhorse for coding, writing, and visual reasoning.

Open code-focused MoE built from DeepSeek-V2, expanding programming-language coverage and coding benchmark performance.

NVIDIA's large open model family for synthetic data generation and reward modeling.

Qwen2's largest dense model, introducing stronger multilingual support, coding/math gains, and long-context variants.

Open GLM-4 9B model family, covering chat, long-context, and code-oriented variants.

Mistral's first code-specialized model, trained for code generation, fill-in-the-middle, and multi-language programming tasks.

Open multilingual research model covering 23 languages, released by Cohere For AI.

ByteDance's commercial Doubao foundation model line for text, code, and assistant workloads.

The 2024 omni-modal model that defined a generation of assistants. Deprecated in Feb 2026 and fully retired across ChatGPT on April 3, 2026.

Yi 1.5 update with stronger instruction following, coding, math, and multilingual performance.

Falcon 2 generation, including text and vision-language 11B models under a permissive TII license.

DeepSeek's first major MoE general model with Multi-head Latent Attention and low-cost API positioning.

Apache-2.0 code model from IBM's Granite Code family, used for local code generation and enterprise coding assistants.

Larger Titan text model for enterprise RAG, summarization, and agent workflows in Amazon Bedrock.

Apache-2.0 enterprise LLM with 480B total / 17B active parameters, optimized for SQL, code, and instruction following.