Search Results for "multi tool"
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16 projects for "multi tool" with 2 filters applied:
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MiMo-V2-Flash
MiMo-V2-Flash: Efficient Reasoning, Coding, and Agentic Foundation
...It uses an MoE setup where a very large total parameter count is available, but only a smaller subset is activated per token, which helps balance capability with runtime efficiency. The project positions the model for workflows that require tool use, multi-step planning, and higher throughput, rather than only single-turn chat. Architecturally, it highlights attention and prediction choices aimed at accelerating generation while preserving instruction-following quality in complex prompts. The repository typically serves as a launch point for running the model, understanding its intended use cases, and reproducing or extending its evaluation on reasoning and agent-style tasks. ... -
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GLM-4.6V
GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning
...Its architecture supports a very large context window (on the order of 128K tokens during training), which lets it handle complex multimodal inputs like long documents, multi-page reports, or video transcripts, while maintaining coherence across extended content. In benchmarks and internal evaluations, GLM-4.6V achieves state-of-the-art (SoTA) performance among models of comparable parameter scale on multimodal reasoning. -
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GLM-4.7
Advanced language and coding AI model
GLM-4.7 is an advanced agent-oriented large language model designed as a high-performance coding and reasoning partner. It delivers significant gains over GLM-4.6 in multilingual agentic coding, terminal-based workflows, and real-world developer benchmarks such as SWE-bench and Terminal Bench 2.0. The model introduces stronger “thinking before acting” behavior, improving stability and accuracy in complex agent frameworks like Claude Code, Cline, and Roo Code. GLM-4.7 also advances “vibe... -
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IQuest-Coder-V1 Model Family
New family of code large language models (LLMs)
...IQuest-Coder-V1 delivers state-of-the-art performance on multiple coding benchmarks, demonstrating strong results in competitive programming, tool use, and agentic code generation. -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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MiniMax-M2
MiniMax-M2, a model built for Max coding & agentic workflows
MiniMax-M2 is an open-weight large language model designed specifically for high-end coding and agentic workflows while staying compact and efficient. It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real... -
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Stable Diffusion WebUI Forge
Stable Diffusion WebUI Forge is a platform on top of Stable Diffusion
Stable Diffusion WebUI Forge is a performance- and feature-oriented fork of the popular AUTOMATIC1111 interface that experiments with new backends, memory optimizations, and UX improvements. It targets heavy users and researchers who push large models, control nets, and high-resolution pipelines where default settings can become bottlenecks. The fork typically introduces toggles for scheduler behavior, attention implementations, caching, and precision modes to reach better speed or quality... -
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Nemotron 3 Super
Open language model developed by NVIDIA as part of Nemotron-3 family
...Its architecture combines Transformer attention layers with Mamba state-space components to balance long-context reasoning, memory efficiency, and high-quality language generation. The model is optimized for building AI agents that must perform complex tasks such as planning, tool usage, coding assistance, and multi-step reasoning. -
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MiMo-V2.5-Pro
Flagship MoE model for long-context agents and complex coding
...It features approximately 1.02 trillion total parameters with 42B activated per inference, balancing extreme capability with efficient execution. The model supports a 1 million token context window, enabling it to maintain coherence across long workflows involving thousands of tool calls and multi-step reasoning chains. Architecturally, it uses a hybrid attention system combining Sliding Window Attention and Global Attention to significantly reduce memory usage while preserving long-context performance. It also integrates multi-token prediction modules that accelerate inference and improve reinforcement learning efficiency. ... -
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Devstral 2
Agentic 123B coding model optimized for large-scale engineering
Devstral 2 is a large-scale agentic language model purpose-built for software engineering tasks, excelling at codebase exploration, multi-file editing, and tool-driven automation. With 123B parameters and FP8 instruct tuning, it delivers strong instruction following for chat-based workflows, coding assistants, and autonomous developer agents. The model demonstrates outstanding performance on SWE-bench, validating its effectiveness in real-world engineering scenarios. -
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Hunyuan-A13B-Instruct
Efficient 13B MoE language model with long context and reasoning modes
...While the total model includes 80 billion parameters, only 13 billion are active per forward pass, making it highly efficient while maintaining strong performance across benchmarks. It supports up to 256K context tokens, advanced reasoning (CoT) abilities, and agent-based workflows with tool parsing. The model offers both fast and slow thinking modes, letting users trade off speed for deeper reasoning. It excels in mathematics, science, coding, and multi-turn conversation tasks, rivaling or outperforming larger models in several areas. Deployment is supported via TensorRT-LLM, vLLM, and SGLang, with Docker images and integration guides provided. ... -
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MiMo-V2.5
Omnimodal AI model for agents, coding, and long-context tasks
MiMo-V2.5 is a native omnimodal large language model developed by Xiaomi, designed for advanced agentic workflows, multimodal reasoning, and long-context processing. Built on a Mixture-of-Experts architecture with approximately 309B total parameters and around 15B activated per inference, it balances high capability with efficient execution. The model natively processes text, images, video, and audio within a unified system, enabling cross-modal understanding and complex task execution in a... -
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MiniMax-M2.7
Self-evolving AI model for agents, coding, and complex workflows
MiniMax-M2.7 is a large-scale open-weight language model designed for advanced agent-based workflows, professional software engineering, and complex productivity tasks. With 229B parameters, it introduces a self-evolution framework in which the model actively improves its own capabilities by updating memory, generating skills, and iterating through reinforcement learning experiments. This process enables it to autonomously refine systems, achieving measurable performance gains such as a 30%... -
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Devstral Small 2
Lightweight 24B agentic coding model with vision and long context
Devstral Small 2 is a compact agentic language model designed for software engineering workflows, excelling at tool usage, codebase exploration, and multi-file editing. With 24B parameters and FP8 instruct tuning, it delivers strong instruction following while remaining lightweight enough for local and on-device deployment. The model achieves competitive performance on SWE-bench, validating its effectiveness for real-world coding and automation tasks. -
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Qwen2.5-VL-3B-Instruct
Qwen2.5-VL-3B-Instruct: Multimodal model for chat, vision & video
Qwen2.5-VL-3B-Instruct is a 3.75 billion parameter multimodal model by Qwen, designed to handle complex vision-language tasks in both image and video formats. As part of the Qwen2.5 series, it supports image-text-to-text generation with capabilities like chart reading, object localization, and structured data extraction. The model can serve as an intelligent visual agent capable of interacting with digital interfaces and understanding long-form videos by dynamically sampling resolution and... -
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DeepSeek-V4-Pro
Flagship MoE model for advanced reasoning, coding, and agents
...It also supports advanced reasoning modes and tool-based workflows, enabling autonomous task execution. -
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DeepSeek-V3.2
High-efficiency reasoning and agentic intelligence model
...The model was notably used in competitive AI challenges such as the 2025 International Mathematical Olympiad (IMO) and IOI, achieving top-tier results. DeepSeek-V3.2 also features a large-scale agentic task synthesis pipeline, which generates training data to enhance tool-use intelligence and multi-step reasoning. It introduces a new “thinking with tools” chat template, allowing it to reason and decide when to invoke specific tools during problem solving.
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