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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 instruction-tuned decoder-only transformer by Arcee.ai, trained on 8 trillion tokens with emphasis on math and code. Apache-2.0 licensed with open weights for cloud-to-edge deployment.
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 a reasoning-first model from Apodex AI designed for complex, long-horizon research tasks and end-to-end agentic execution. It handles papers, datasets, spreadsheets, images, and code, with built-in Statement Review…
BLOOM is a 176B-parameter open-access multilingual autoregressive Large Language Model released July 2022 under the RAIL License v1.0, supporting 46 natural languages and 13 programming languages with a 2048-token context window.
Use the profiles as a shortlist, then confirm the fit against your workflow and current provider documentation.
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Review capabilities, integrations, limitations and deployment requirements side by side.
Check source links and freshness dates, then validate important details with the provider.
