Model ID
inclusionAI/Ling-3.1-flash-1019
Capabilities
Ling 3.1 Flash 1019
Ling 3.1 Flash 1019 is a post-trained update of Ling 3.1 Flash, a hybrid-linear Mixture-of-Experts model for real-world agents, scientific reasoning, and coding. The model carries 560B total parameters and 25B active in a 72-layer stack with 4,096 hidden size, 64 attention heads, and 64 KV heads. Its 63 Kimi Delta Attention layers are interleaved with 9 gated MLA layers, and the sparse blocks select 8 of 512 routed experts alongside a shared expert. It supports a 1M-token context and includes a Multi-Token Prediction layer for agentic workloads.
About this model
Ling 3.1 Flash 1019 is a post-trained update of Ling 3.1 Flash, a hybrid-linear Mixture-of-Experts model for real-world agents, scientific reasoning, and coding. The model carries 560B total parameters and 25B active in a 72-layer stack with 4,096 hidden size, 64 attention heads, and 64 KV heads. Its 63 Kimi Delta Attention layers are interleaved with 9 gated MLA layers, and the sparse blocks select 8 of 512 routed experts alongside a shared expert. It supports a 1M-token context and includes a Multi-Token Prediction layer for agentic workloads.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (inclusionAI/Ling-3.1-flash-1019). Released under MIT.
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 · SGLang. 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