Surpem/Supertron2-24B
Supertron2-24B by Surpem is a 24 billion parameter instruction-tuned causal language model, built upon mistralai/Devstral-Small-2-24B-Instruct-2512, with a 32768 token context length. It is specifically designed for practical coding assistance, structured reasoning, mathematical problem-solving, and scientific explanations. This model excels at multi-step instruction following and general chat, making it a versatile tool for developers and researchers.
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Supertron2-24B: Instruction-Tuned for Coding and Reasoning
Supertron2-24B is a 24 billion parameter instruction-tuned language model developed by Surpem, based on the mistralai/Devstral-Small-2-24B-Instruct-2512 architecture. It is engineered to provide robust assistance across various technical and general tasks, emphasizing practical application and structured problem-solving.
Key Capabilities
- Coding: Assists with writing, explaining, debugging, and reviewing code, including implementation planning and error analysis.
- Reasoning: Capable of handling multi-step questions, comparing options, following complex instructions, and generating concise answers.
- Math & Science: Excels at arithmetic, algebra, word problems, and providing step-by-step mathematical explanations. It can also clarify scientific concepts and aid in STEM-related writing.
- General Chat: Supports writing, brainstorming, summarization, planning, and answering everyday questions.
Intended Use Cases
- Coding assistance and software engineering reasoning.
- Mathematical and scientific problem-solving and explanations.
- General instruction following, chat, and content generation (writing, summarization, brainstorming).
- Research and technical assistance.
Hardware Requirements
- bfloat16: Minimum 48 GB VRAM, recommended 80 GB+.
- 4-bit quantized: Minimum 16 GB VRAM, recommended 24 GB+.
Users should be aware that the model may produce errors or outdated information and should not be used as the sole source for critical decisions.