Models

DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters on input and 16B on...

Tencent: Hy4 preview is a mixture-of-experts model from Tencent, with 49B active parameters out of 770B total. It is designed for coding agents, complex tool-use workflows, and productivity tasks that...

Native multimodal GLM model for efficient coding and long-horizon agent tasks

Dense 27B vision-language model for coding, agent tasks, and image and video understanding

Flagship GLM model for long-horizon coding, agents, and complex project delivery

Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at...

Hy3 is a 295B-parameter Mixture-of-Experts model from Tencent (21B active, 192 experts with top-8 routing) built for reasoning, agentic workflows, and real-world production use. It supports a configurable reasoning effort:...

Open flagship GLM for long-horizon coding agents and million-token context work

Lower-latency Kimi Code variant for interactive edits and coding-agent loops

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...

NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it...

MiniMax multimodal model for long-context coding, perception, and agent planning

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...

DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and...

MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro....

MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...

Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and...

Open multimodal Qwen MoE for local agents that need vision, audio, and code

Strong GLM coding model for agentic engineering, terminals, and repository generation

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

Open MiniMax flagship for coding agents, office automation, and complex environments

Low-latency M2.7 variant for interactive coding plans and agent loops

Qwen instruction model for multilingual chat, reasoning, and tool use

Large open Qwen multimodal MoE for visual agents and long technical tasks

High-speed MiniMax model for low-latency coding and agent workflows

General GLM flagship for coding, analysis, and tool-heavy engineering workflows

Prior MiniMax coding model for agent workflows, office edits, and automation

Open-weight Qwen coding model for agents, repository edits, and multi-turn tool use

Budget GLM lane for fast coding help, routing, and everyday automation

Efficient GLM model for fast reasoning, coding, and agent workflows

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed...

Earlier MiniMax agent model for practical coding and productivity tasks

Mature GLM model for dependable coding, reasoning, and structured agent tasks

Mistral's coding-agent model for repository work, terminal tasks, and software fixes

GLM vision model for visual reasoning, documents, and multimodal agents

Mistral's largest general model for enterprise agents, coding, and multilingual reasoning

DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-of-Experts (MoE) architecture introduced in...

Efficient open MiniMax model built for coding agents and tool-heavy workflows

Late GLM-4 workhorse for coding agents, reasoning, and structured tasks

Qwen vision-language instruct model for visual reasoning, documents, and agent tasks

Qwen vision-language thinking model for visual reasoning, documents, and agent tasks

Qwen instruction model for multilingual chat, reasoning, and tool use

Efficient Qwen thinking model for local reasoning, math, and coding agents

GLM vision model for visual reasoning, documents, and multimodal agents

gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...

Lighter GLM-4.5 variant for fast coding assistance and cheaper agents

Hybrid-reasoning GLM release that made the 4.5 line broadly useful