Model ID
mindlab-research/Macaron-V1-Venti
Capabilities
Macaron V1 Venti
Macaron V1 Venti is a 753B parameter Mixture of LoRA (MoL) flagship model built on a 744B GLM-5.2 base with four 1B-parameter specialists for chat, personal-agent tasks, coding, and Generative UI. It uses a 78-layer architecture with a 6,144 hidden size and 64 attention heads, incorporating sparse MoE layers with 256 routed experts and 1 shared expert, activating 8 routed experts per token. The model integrates IndexShare sparse attention and multi-token prediction, while supporting a 1M-token context window for long-horizon agentic workflows, coding, tool use, and Generative UI.
About this model
Macaron V1 Venti is a 753B parameter Mixture of LoRA (MoL) flagship model built on a 744B GLM-5.2 base with four 1B-parameter specialists for chat, personal-agent tasks, coding, and Generative UI. It uses a 78-layer architecture with a 6,144 hidden size and 64 attention heads, incorporating sparse MoE layers with 256 routed experts and 1 shared expert, activating 8 routed experts per token. The model integrates IndexShare sparse attention and multi-token prediction, while supporting a 1M-token context window for long-horizon agentic workflows, coding, tool use, and Generative UI.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (mindlab-research/Macaron-V1-Venti). Released under MIT. Further reading: Blog
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on B200 · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
NVIDIA HGX B200
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