Model ID
poolside/Laguna-S-2.1
Capabilities
Laguna S 2.1
Laguna S 2.1 is a Mixture-of-Experts language model designed for agentic coding, reasoning, and long-horizon workflows. It features 118B total parameters with approximately 8B activated per token, using a 48-layer architecture with 3,072 hidden size and 48 attention heads. The model activates 10 experts per token across 256 routed experts alongside a shared expert, combining hybrid sliding window and full attention with grouped-query attention and per-head gating. Supporting up to a 1M token context window, it is optimized for large-scale coding, tool use, and long-context reasoning.
About this model
Laguna S 2.1 is a Mixture-of-Experts language model designed for agentic coding, reasoning, and long-horizon workflows. It features 118B total parameters with approximately 8B activated per token, using a 48-layer architecture with 3,072 hidden size and 48 attention heads. The model activates 10 experts per token across 256 routed experts alongside a shared expert, combining hybrid sliding window and full attention with grouped-query attention and per-head gating. Supporting up to a 1M token context window, it is optimized for large-scale coding, tool use, and long-context reasoning.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (poolside/Laguna-S-2.1). Released under OpenMDW-1.1. Further reading: Blog
Deploy Private Inference Endpoint
Choose your hardware and inference engine to get deployment commands and performance benchmarks tailored to your infrastructure
Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
Access Restricted
Enter your email to get access to this content
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
Unlock Next-Generation AI Power on Vultr Cloud GPU