Model ID
stepfun-ai/Step-3.5-Flash
Capabilities
Step 3.5 Flash
Step 3.5 Flash is a sparse Mixture-of-Experts (MoE) language model built for fast reasoning, coding, and agentic workflows. It has 196B total parameters with about 11B activated per token, using a 45-layer transformer with 4,096 hidden size and 64 attention heads. The architecture includes 288 experts per layer with top-8 routing and a shared expert, along with a hybrid attention pattern combining sliding window and full attention in a 3:1 ratio. It supports a 256K context window and integrates Multi-Token Prediction for high-throughput generation.
About this model
Step 3.5 Flash is a sparse Mixture-of-Experts (MoE) language model built for fast reasoning, coding, and agentic workflows. It has 196B total parameters with about 11B activated per token, using a 45-layer transformer with 4,096 hidden size and 64 attention heads. The architecture includes 288 experts per layer with top-8 routing and a shared expert, along with a hybrid attention pattern combining sliding window and full attention in a 3:1 ratio. It supports a 256K context window and integrates Multi-Token Prediction for high-throughput generation.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (stepfun-ai/Step-3.5-Flash). Released under Apache 2.0. Further reading: Paper · Blog
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Hardware
MI325X
2,048 GB
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on MI325X · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
AMD Instinct MI325X
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