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Language and foundation models compared by capability, context, licensing, deployment and best-fit workloads.
Browse every catalogued llm models profile, then use the evidence and freshness details to judge how much decision context is currently available.
AFM-4.5B is a 4.5B-parameter open-source instruction-tuned LLM by Arcee.ai featuring a transformer decoder-only design with grouped query attention and ReLU^2 activation. Trained on 8 trillion tokens and deployable from cloud to edge…
Agents-A1 is a 35B Mixture-of-Experts agentic model from InternScience with 3B active parameters and a 262K context window. Open-sourced in Hugging Face Transformers format with native tool-use, function calling, and agentic reasoning…
Agents-A1-4B is a 4B-parameter dense transformer agentic model from InternScience (Shanghai AI Lab) with a 262K context window. It supports function/tool calling, agentic reasoning, and strong performance on BrowseComp, GAIA, and related…
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Apodex-1.1-mini is an open-source reasoning-first LLM from Apodex AI, released under Apache 2.0. It offers a 262,144-token context window, native function calling, multi-agent coordination, and built-in Statement Review verification for…
百川大模型系列API，支持搜索增强+企业知识库，实现互联网实时信息+企业完整知识的融合，并能最多支持192k上下文窗口，解决大部分定制化场景。
Use the profiles as a shortlist, then confirm the fit against your workflow and current provider documentation.
Filter by the use case, access model and pricing approach your team actually needs.
Review capabilities, integrations, limitations and deployment requirements side by side.
Check source links and freshness dates, then validate important details with the provider.
