驱动 AnyInt 网络的精选模型目录。

ERNIE 5.1 is a high-efficiency flagship foundation model released by Baidu in May 2026. It is designed to deliver superior reasoning, creativity, and agentic capabilities while significantly reducing training costs by 94% compared to similar models

GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering, and complex multi-step automation. Reasoning efforts high and xhigh are supported; xhigh maps to max reasoning. It is particularly strong at coding and tool use across long-running tasks, able to maintain engineering context and follow standards consistently through a full development workflow, from requirements to multi-platform deployment, in a single task.

GLM 5.3 is Z.ai's large-scale reasoning model for complex software engineering and long-horizon agent tasks. It improves on GLM 5.2 in coding capability and performance per token while retaining a million-token-class text context window. Reasoning is always enabled and supports low, high, and max effort levels, with max as the default. The model supports function calling, tool choice, structured JSON outputs, prompt caching, and streaming. This AnyInt deployment is served through Baidu Qianfan and ModRouter with a 1,179,648-token context window and up to 131,072 output tokens.

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 can convert prompts and visual inputs into production-ready interfaces. Its agent swarm architecture scales to hundreds of parallel sub-agents for autonomous task decomposition - delivering documents, websites, and spreadsheets in a single run without human oversight.

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 that reduces training and inference cost while preserving quality in long-context scenarios. A scalable reinforcement learning post-training framework further improves reasoning, with reported performance in the GPT-5 class, and the model has demonstrated gold-medal results on the 2025 IMO and IOI. V3.2 also uses a large-scale agentic task synthesis pipeline to better integrate reasoning into tool-use settings, boosting compliance and generalization in interactive environments.

GLM-5 is Z.ai’s flagship open-source foundation model engineered for complex systems design and long-horizon agent workflows. Built for expert developers, it delivers production-grade performance on large-scale programming tasks, rivaling leading closed-source models. With advanced agentic planning, deep backend reasoning, and iterative self-correction, GLM-5 moves beyond code generation to full-system construction and autonomous execution.

GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interactions, GLM-5.1 can work independently and continuously on a single task for more than 8 hours, autonomously planning, executing, and improving itself throughout the process, ultimately delivering complete, engineering-grade results.

HappyHorse 1.0 is a video generation model currently ranked #1 on the Artificial Analysis Text-to-Video Leaderboard. EvoLink is preparing unified API access with per-second billing.

MiniMax M2.1 - AI model

MiniMax M2.5 - AI model

Qwen-Image-2.0 Full-Version series integrates image generation and image editing capabilities. It offers more professional text rendering, support for 1K-token instructions, more refined realistic textures, detailed depiction of photorealistic scenes, and stronger semantic instruction-following capabilities. The full-version model delivers the strongest text rendering capability and realistic texture quality within the 2.0 series.

The Qwen series image generation model features outstanding text rendering capabilities and performs exceptionally well in complex text rendering, as well as various generation and editing tasks.

Qwen's Enhanced Large Visual Language Model. Significantly upgraded for detailed recognition capabilities and text recognition abilities, supporting ultra-high pixel resolutions up to millions of pixels and extreme aspect ratios for image input. It delivers significant performance across a broad range of visual tasks.

Qwen3-Max is an updated release built on the Qwen3 series, offering major improvements in reasoning, instruction following, multilingual support, and long-tail knowledge coverage compared to the January 2025 version. It delivers higher accuracy in math, coding, logic, and science tasks, follows complex instructions in Chinese and English more reliably, reduces hallucinations, and produces higher-quality responses for open-ended Q&A, writing, and conversation. The model supports over 100 languages with stronger translation and commonsense reasoning, and is optimized for retrieval-augmented generation (RAG) and tool calling, though it does not include a dedicated “thinking” mode.

Alibaba Cloud Qwen3.8 Max with a 1M-token context window, hybrid reasoning, function calling, built-in tools, structured output, and context caching.

Text Embedding V4 - AI model

Alibaba's most advanced video generation model, supporting over 10 visual creation capabilities in a unified system. Wan 2.6 generates 1080p video at 24fps from text, images, reference videos, or audio, with native audio-visual synchronization and precise lip-sync. Key features include reference-to-video (insert a character's appearance and voice into new scenes), multi-shot storytelling from simple prompts, synchronized sound effects and music, and support for 16:9, 9:16, and 1:1 aspect ratios with clips up to 15 seconds.

ByteDance: Seedance 2.0 支持 文本、图像、音频、视频 输入、视频 输出，可通过 OpenAI 协议调用。