AIAny
AI Model2026
Icon for item

XYZ-Aquila-mini

An open-weight, Qwen-derived thinking model optimized for agentic deep web search and long-horizon planning. Provides Qwen-compatible reasoning and tool-call formats for English/Chinese browsing, multi-source evidence aggregation, source verification, and recovery from failed environment interactions.

Introduction

Why this matters

Agentic search—where an LLM must plan multi-step web investigations, verify sources, and recover from failed environment interactions—exposes gaps in models that only generate text. This release supplies a post-trained checkpoint that embeds a reasoning and tool-call surface designed to plug into a surrounding agent harness, enabling reproducible search workflows and stateful tool use at large context lengths.

Key Capabilities
  • Qwen-compatible thinking/checkpoint: post-trained from Qwen3.6-35B-A3B to preserve Qwen-style reasoning and function-call formats so it interoperates with existing Qwen tool parsers. This means you can use the model with Qwen-aware endpoints and tooling with minimal adapter work.
  • Agentic search skills: optimized for long-horizon planning, focused web browsing in English and Chinese, multi-source evidence aggregation, and explicit source verification steps rather than single-shot retrieval. The checkpoint is tuned for iterative, tool-driven research workflows.
  • Harness-first deployment: the model is released as a “thinking model” rather than a full agent; concrete tool implementations, replayable context management, and evaluation pipelines are provided by the open-source AxisAgentic harness and companion data (XYZ-Aquila-SFT), not the checkpoint alone.
  • High-context readiness and deployment notes: evaluation and examples assume a large context window (up to 256K) and common deployment with SGLang. Practical deployment examples show tensor-parallel setups and function-calling interfaces for controlled tool usage.
Who it fits (and tradeoffs)

Great fit if you need an open-weight model tuned specifically for structured, tool-driven web research workflows, bilingual browsing (EN/ZH), and reproducible agent evaluation with an external harness. Look elsewhere if you need an out-of-the-box conversational product, a plug-and-play multimodal model, or a tiny footprint: the intended use assumes integration with the AxisAgentic/sglang tooling, increased memory (large context/tensor parallelism), and operational scaffolding for safe tool use.

Where it fits

Positioned for AI teams building reproducible search agents and benchmarked agentic workflows: not a complete application, but a drop-in checkpoint to be combined with the AxisAgentic harness, search/scrape/python tool implementations, and the provided SFT data for agentic evaluation and deployment.

More Items

Hugging Face
AI Model2026

Provides a 2‑bit quantized build of Qwen3.6‑35B‑A3B for local serving via an OpenAI‑compatible HTTP API. Key features: 12.3 GB on disk, eschamoe mixed 2/3‑bit expert quantization with int8 dense layers, runs on a single 16–24 GB NVIDIA GPU and ships with Escha SGLang and ZML runtimes.

Hugging Face
AI Model2026

An open-weight LLM checkpoint post-trained for agentic deep search: Qwen-compatible reasoning and tool-call formats optimized for web browsing, multi-source evidence aggregation, long-horizon planning and recovery from failed interactions; typically paired with the AxisAgentic harness.

Hugging Face
AI Model2026

Generates text from text, image, or audio inputs using a native multimodal, Mixture-of-Experts autoregressive transformer (276B total / 12B active) with up to 1M-token context; targeted at conversational, agentic, coding and multimodal applications.