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[next-mdx-remote-client] error compiling MDX: Could not parse expression with acorn More information: https://mdxjs.com/docs/troubleshooting-mdx
Runs a full 27B-class Qwen3.6-derived LLM in a ~7.2 GB ternary/2‑bit format for on-device or single‑GPU text generation, retaining ~95% of FP16 performance and supporting a 262K‑token context. Designed for laptop/GPU deployment; exceeds typical phone memory limits.
[next-mdx-remote-client] error compiling MDX: Could not parse expression with acorn More information: https://mdxjs.com/docs/troubleshooting-mdx
GGUF-quantized, refusal-removed build of Qwen3.8-Flash-Next for llama.cpp that provides multimodal (image+text), reasoning and tool-calling capabilities; released for security research and red-teaming under the Apache-2.0 license.
A dynamically quantized GGUF build of Ornith-1.5-35B optimized for agentic code-fixing and multi-turn conversations: targets 4-bit/≈22GB deployments, includes a vision projector, a custom importance matrix and a concise chat template.
Open-weights LLM fine-tuned for phone-based voice agents that prioritizes low latency and reliable tool/function calling. Based on NVIDIA Nemotron 3 Nano (30B total, 3.5B active), supports very long contexts (262,144 tokens) and recommends temperature=0 with thinking disabled for deployment.