Showing 7 open source projects for "complex function plotter"

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  • 1
    GLM-4

    GLM-4

    GLM-4 series: Open Multilingual Multimodal Chat LMs

    ...The GLM-4-32B-0414 models are trained on ~15T high-quality data (including substantial synthetic reasoning data), then post-trained with preference alignment, rejection sampling, and reinforcement learning to improve instruction following, coding, function calling, and agent-style behaviors. The GLM-Z1-32B-0414 line adds deeper mathematical, coding, and logical reasoning via extended reinforcement learning and pairwise ranking feedback, while GLM-Z1-Rumination-32B-0414 introduces a “rumination” mode that performs longer, tool-using deep research for complex, open-ended tasks. A lightweight GLM-Z1-9B-0414 brings many of these techniques to a smaller model, targeting strong reasoning under tight resource budgets.
    Downloads: 13 This Week
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  • 2
    GLM-4-32B-0414

    GLM-4-32B-0414

    Open Multilingual Multimodal Chat LMs

    GLM-4-32B-0414 is a powerful open-source large language model featuring 32 billion parameters, designed to deliver performance comparable to leading models like OpenAI’s GPT series. It supports multilingual and multimodal chat capabilities with an extensive 32K token context length, making it ideal for dialogue, reasoning, and complex task completion. The model is pre-trained on 15 trillion tokens of high-quality data, including substantial synthetic reasoning datasets, and further enhanced with reinforcement learning and human preference alignment for improved instruction-following and function calling. Variants like GLM-Z1-32B-0414 offer deep reasoning and advanced mathematical problem-solving, while GLM-Z1-Rumination-32B-0414 specializes in long-form, complex research-style writing using scaled reinforcement learning and external search tools. ...
    Downloads: 0 This Week
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  • 3
    Mistral Medium 3.5

    Mistral Medium 3.5

    Dense 128B multimodal model for reasoning, coding, vision, and agents

    ...The model accepts both text and images while generating text, using a vision encoder trained from scratch to accommodate variable image sizes and aspect ratios. Reasoning effort can be configured per request, allowing users to switch between fast direct responses and higher-compute reasoning for complex problems and agents. It includes native function calling, structured JSON output, strong system-prompt adherence, and multilingual support across dozens of languages. Mistral positions it as the successor to Medium 3.1, Magistral, and Devstral 2, consolidating their specialized capabilities into one general-purpose model.
    Downloads: 0 This Week
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  • 4
    Nex-N2-Pro

    Nex-N2-Pro

    Large agentic model for coding, tools, research, and execution

    Nex-N2-Pro is Nex AGI’s larger open-source agentic model, built for real-world productivity, coding, deep research, tool calling, and long-horizon terminal execution. It uses the Nex-N2 “Agentic Thinking” framework, which connects requirement understanding, planning, implementation, environmental feedback, debugging, evaluation, and iteration into a single closed loop. The model is built on Qwen3.5-397B-A17B and is designed as the high-quality counterpart to Nex-N2-mini, trading higher...
    Downloads: 0 This Week
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  • 5
    Ministral 3 14B Reasoning 2512

    Ministral 3 14B Reasoning 2512

    High-precision 14B multimodal model built for advanced reasoning tasks

    ...It pairs a 13.5B-parameter language model with a 0.4B vision encoder, enabling strong multimodal reasoning across both text and images. This version is specifically post-trained for reasoning tasks, making it highly effective for math, coding, STEM workloads, and complex multi-step problem-solving. Despite its scale, the model is engineered for practical deployment and can run locally on 32GB of VRAM in BF16 or under 24GB when quantized. It maintains robust system-prompt adherence, supports dozens of languages, and provides native function calling with clean JSON output for agentic workflows. The model's architecture also delivers a 256k context window, unlocking large-document analysis and long-form reasoning.
    Downloads: 0 This Week
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  • 6
    gpt-oss-120b

    gpt-oss-120b

    OpenAI’s open-weight 120B model optimized for reasoning and tooling

    ...The model supports function calling, web browsing, and code execution, streamlining intelligent agent development.
    Downloads: 0 This Week
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  • 7
    Mistral Large 3 675B Instruct 2512

    Mistral Large 3 675B Instruct 2512

    Frontier-scale 675B multimodal instruct MoE model for enterprise AIMis

    Mistral Large 3 675B Instruct 2512 is a state-of-the-art multimodal granular Mixture-of-Experts model featuring 675B total parameters and 41B active parameters, trained from scratch on 3,000 H200 GPUs. As the instruct-tuned FP8 variant, it is optimized for reliable instruction following, agentic workflows, production-grade assistants, and long-context enterprise tasks. It incorporates a massive 673B-parameter language MoE backbone and a 2.5B-parameter vision encoder, enabling rich multimodal...
    Downloads: 0 This Week
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