Agents-A1-Q4_K_M-GGUF

This repository contains the GGUF quantized version of Agents-A1, a 35B Mixture-of-Experts (MoE) agentic model developed by InternScience. Quantization has been performed using the Q4_K_M method to optimize performance and reduce memory consumption while preserving agentic reasoning capabilities.


Provided Files

File Name Size Quantization Method Description
Agents-A1-Q4_K_M.gguf 21.2 GB Q4_K_M Medium 4-bit quantization. Recommended balance between size, speed, and accuracy.

About Agents-A1

Agents‑A1 is a 35B Mixture‑of‑Experts agentic model built to scale heterogeneous agentic abilities across multiple domains including Long‑horizon Search, Engineering, Scientific Research, Instruction Following, and Tool-calling.

Key Highlights

  • Agentic Reasoning: Excels at decomposing complex tasks into executable sub-steps, planning ahead, and adapting its strategy based on intermediate results.
  • Tool Use: Natively supports function calling and tool integration, enabling seamless interaction with APIs, code interpreters, search engines, and external tools.
  • Scientific and Professional Reasoning: Handles tool-integrated scientific reasoning and professional knowledge question answering.
  • Instruction Following: Precisely follows detailed, multi-constraint instructions across diverse domains.

Performance Overview

Despite operating in the ~35B model class, Agents-A1 delivers highly competitive performance against frontier-scale systems such as GPT-5.5, DeepSeek-V4-pro, and Kimi-K2.6. It achieves overall SOTA results on several challenging benchmarks, including Seal-0 (56.4), HiPhO (46.4), FrontierScience-Olympiad (79.0), FrontierScience-Research (40.0), IFBench (80.6), and IFEval (94.8).


Deployment & Usage

You can run this GGUF model using popular inference engines like llama.cpp or Ollama.

Option 1: Using llama.cpp

To run inference via the command line with llama.cpp, download the file and use the following command structure:

./llama-cli \
  --model Agents-A1-Q4_K_M.gguf \
  --prompt "<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n<|im_start|>user\nHello, who are you?<|im_end|>\n<|im_start|>assistant\n" \
  --ctx-size 8192 \
  --threads 8
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