Model Releases
Step-3.5-Flash: The Open-Source Reasoning King
StepFun unveils Step-3.5-Flash, a 196B MoE model delivering frontier reasoning at 350 tokens per second with open weights.
February 1, 2026
Model ReleaseStep-3.5-Flash
Introduction
StepFun has officially released Step-3.5-Flash, marking a significant milestone in open-source reasoning capabilities for the modern AI ecosystem. Scheduled for release on February 1, 2026, this model challenges the dominance of closed proprietary systems by offering frontier-level intelligence without the exorbitant licensing fees typically associated with high-end models.
Developers are now able to access a 196 billion parameter MoE architecture that prioritizes efficiency and speed for enterprise deployment. This release signifies a major shift towards democratizing high-performance AI, allowing smaller teams to build complex agents that previously required massive enterprise budgets to maintain.
The combination of open weights and optimized inference makes it a game-changer for the industry. By bridging the gap between cost and capability, Step-3.5-Flash sets a new standard for what open-source models can achieve in terms of raw reasoning power and throughput.
Key Features & Architecture
The architecture of Step-3.5-Flash is built around a sparse Mixture of Experts design, ensuring computational efficiency during heavy workloads. It utilizes a proprietary 3-way Multi-Token Prediction strategy, which significantly accelerates generation while maintaining high coherence across long contexts.
The model activates only 11 billion parameters per token, reducing memory footprint during inference and lowering hardware requirements for local deployment. This sparse activation allows the model to scale effectively on consumer-grade GPUs without sacrificing performance.
Additionally, the system supports a massive context window, enabling the processing of entire codebases or long-form documents in a single pass. This capability is crucial for enterprise applications that require deep understanding of complex, multi-file environments.
- 196B Total Parameters (MoE)
- 11B Active Parameters
- 3-way Multi-Token Prediction enabled
- Context window optimized for long documents
- Native support for multimodal inputs
Performance & Benchmarks
Performance metrics indicate that Step-3.5-Flash outperforms previous versions in both reasoning and coding tasks on standard industry benchmarks. It achieves a score of 89.2 on MMLU-Pro, surpassing many closed-source models in the same tier and proving its reasoning depth.
HumanEval scores hit 94.5%, demonstrating superior code generation capabilities for software engineers using the API. The model also excels in mathematical reasoning, achieving a 91.0% score on GSM8K, which is critical for specialized AI agents.