Model ID
IFM/K2-Horizon-375B-A23B
Capabilities
K2 Horizon 375B A23B
K2 Horizon 375B A23B is a sparse Mixture-of-Experts model designed for agentic workflows, tool use, terminal tasks, reasoning, coding, and long-horizon inference. It features 375B total parameters with 23B activated per token, using a 61-layer architecture with 6,144 hidden size, 48 attention heads, and 8 KV heads. The architecture employs 192 routed experts, 8 activated per token, and 1 shared expert, with 1,792-dimensional MoE feed-forward layers and SiLU activation. Supporting a native 512K-token context, it uses BF16 computation for efficient high-capability long-context inference.
About this model
K2 Horizon 375B A23B is a sparse Mixture-of-Experts model designed for agentic workflows, tool use, terminal tasks, reasoning, coding, and long-horizon inference. It features 375B total parameters with 23B activated per token, using a 61-layer architecture with 6,144 hidden size, 48 attention heads, and 8 KV heads. The architecture employs 192 routed experts, 8 activated per token, and 1 shared expert, with 1,792-dimensional MoE feed-forward layers and SiLU activation. Supporting a native 512K-token context, it uses BF16 computation for efficient high-capability long-context inference.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (IFM/K2-Horizon-375B-A23B). Released under Apache 2.0. Further reading: Blog
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Requires vllm/vllm-openai:nightly or any standard vLLM image v0.30.0+ to support this model configuration.
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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