mindlab-research/Macaron-V1-Tall · Hugging Face

Source: https://huggingface.co/mindlab-research/Macaron-V1-Tall

📖Blog:Introducing Macaron-V1 🚀Hosted API:Macaron API Platform 🧩Artifacts:Macaron Artifacts 🛠️Self-hosted serving:Mixture of LoRA (MoL) serving harness 📄**Technical report:**coming soon

Macaron-V1-Tall is a Mixture of LoRA (MoL) model in the Macaron-V1 family, built on Qwen3.6-35B-A3B for personal intelligence, tool use, coding workflows, and code-native Generative UI.

The model combines a Qwen3.6 MoE base with the Macaron-V1 specialist system: four LoRA specialists for chat, personal-agent tasks, coding, and GenUI, with an L0 router selecting the most suitable specialist for each new user request.

Macaron-V1-Tall is released alongside Macaron-V1-Venti as a sibling model in the Macaron-V1 family. Both models share the same product-facing specialist layout and routed serving interface while targeting different deployment and experimentation profiles.

https://huggingface.co/mindlab-research/Macaron-V1-Tall#highlightsHighlights

• A Qwen3.6-35B-A3B-based Macaron-V1 model with the full Macaron specialist system.
• Mixture of LoRA (MoL) architecture with four specialists across Chat, Agent, Coding, and GenUI.
• Built for personal-agent workflows, tool use, repository-level coding, and UI4A Generative UI.
• BF16 checkpoint with four LoRA adapters stored underloras/L0throughloras/L3.
• Supports a 262K context length according to the released checkpoint configuration.

https://huggingface.co/mindlab-research/Macaron-V1-Tall#model-overviewModel Overview

FieldValueModel nameMacaron-V1-TallOrganizationMindLab ResearchRelease familyMacaron-V1Base modelQwen3.6-35B-A3BArchitectureQwen3.6 MoE base + Mixture of LoRA (MoL) specialistsCheckpoint contentsBF16 base checkpoint + four LoRA adaptersSpecialistsL0 Chat, L1 Agent, L2 Coding, L3 GenUILoRA rank64Post-training systemMinT + MindForgePrimary domainsPersonal intelligence, tool use, coding, Generative UIContext length262KText config40 layers, 2048 hidden size, 16 attention heads, 2 KV heads, 256 experts, 8 experts per tokenPrecision / serving formatBF16 base checkpoint with routed LoRA servingLicenseMIT

https://huggingface.co/mindlab-research/Macaron-V1-Tall#mixture-of-lora-mol-architectureMixture of LoRA (MoL) Architecture

AdapterRoleDescriptionloras/L0ChatConversational and instruction-following backbone; entry point for routing.loras/L1AgentPersonal-life agent tasks, heavy tool use, long-horizon planning, and dynamic workflows.loras/L2CodingCode understanding, SWE tasks, terminal use, and repository workflows.loras/L3GenUIUI4A rendering and UI-driven action. At runtime, L0 routes each new user request to the most suitable specialist. Ongoing reasoning and tool interactions remain within the selected LoRA, while completed work can be shared across specialists through concise summaries.

https://huggingface.co/mindlab-research/Macaron-V1-Tall#evaluationEvaluation

https://huggingface.co/mindlab-research/Macaron-V1-Tall#usageUsage

https://huggingface.co/mindlab-research/Macaron-V1-Tall#hosted-apiHosted API

The hosted API is available athttps://mintcn.macaron.xin/. Use the site for current model names, authentication, pricing, and rate-limit details.

For OpenAI-compatible deployments, requests follow the standard chat-completions shape:

curl https://mintcn.macaron.xin/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <api-key>" \
  -d '{
    "model": "Macaron-V1-Tall",
    "messages": [
      {"role": "user", "content": "Create a compact dashboard UI for tracking weekly fitness goals."}
    ],
    "temperature": 0.2,
    "max_tokens": 2048
  }'

https://huggingface.co/mindlab-research/Macaron-V1-Tall#transformersTransformers

This repository contains the base checkpoint at the repository root and the Macaron LoRA specialists underloras/. Load the base checkpoint with a Transformers version that supports the Qwen3.6 / Qwen3.5 MoE architecture.

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

repo_id = "mindlab-research/Macaron-V1-Tall"

tokenizer = AutoTokenizer.from_pretrained(
    repo_id,
    trust_remote_code=True,
)

model = AutoModelForCausalLM.from_pretrained(
    repo_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
    trust_remote_code=True,
)
model.eval()

https://huggingface.co/mindlab-research/Macaron-V1-Tall#mixture-of-lora-mol-servingMixture of LoRA (MoL) Serving

For self-hosted routed serving, use theMixture of LoRA (MoL) serving harness. The harness keeps the endpoint OpenAI-compatible while adding an L0 router, server-side LoRA metadata, and same-request switching into the selected specialist.

See theMoL serving repositoryfor more details.

https://huggingface.co/mindlab-research/Macaron-V1-Tall#macaron-artifactsMacaron Artifacts

Macaron Artifactsis the companion local WebUI and plugin bundle for viewing Macaron sessions and GenUI output. It supports Claude Code, Codex, and Kimi Code, and can run against Macaron or another Anthropic-compatible endpoint.

The plugin includes thegenui\-builderskill so supported agents can produce GenUI TSX and preview the rendered artifact in the browser. See the Artifacts repository for full install, update, and provider configuration details.

https://huggingface.co/mindlab-research/Macaron-V1-Tall#licenseLicense

This repository is released under the MIT License. Users should also respect any requirements inherited from the Qwen3.6-35B-A3B base model and from dependencies used by the serving harness.

https://huggingface.co/mindlab-research/Macaron-V1-Tall#citationCitation

@misc{mindlab2026macaronv1,
  author = {{Mind Lab}},
  title = {Introducing Macaron-V1},
  year = {2026},
  howpublished = {Mind Lab: A Lab for Experiential Intelligence},
  note = {https://macaron.im/mindlab/research/introducing-macaron-v1}
}