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StepFun의 파비콘

StepFun

다음 제공업체의 모델 둘러보기: StepFun (서비스 약관)

3 모델

OpenRouter에서 처리된 토큰

  • deepseek의 파비콘
    DeepSeek: DeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017

    DeepSeek V4.1 Flash 1017 is the October 17, 2026 snapshot of DeepSeek V4.1 Flash, served by DeepSeek under the deepseek-flash API model name. V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters on input and 16B on output from a 552B-parameter backbone, an asymmetric split that keeps per-token compute low relative to the model's total size. Image understanding is native to the architecture, with visual and text embeddings trained jointly from the start of pre-training rather than added afterward as in the earlier experimental V4 Flash Vision Exp. It is suited for coding, terminal, and computer-use agents, along with long-horizon tasks that must run to completion across many steps and long-context analysis. Compressed KV caching cuts cache memory to roughly a quarter of the previous Flash generation, significantly reducing costs on agentic workloads. DeepSeek positions it as the cost-efficient tier of the V4.1 family and reports that it exceeds V4 Pro on performance, speed, and task completion time.

    제작: deepseek2026년 10월 17일1.05M 컨텍스트US$0.195/M 입력 토큰US$0.78/M 출력 토큰
  • stepfun의 파비콘
    StepFun: Step 5 PreviewStep 5 Preview

    Step 5 Preview is StepFun's flagship model for agentic work, built on a sparse Mixture-of-Experts architecture (27B active / 600B total parameters). It performs strongly in software engineering and professional knowledge work, with particular strength in finance. It is designed for extended tasks that span large codebases and documents, using tools and refining results over multiple steps.

    제작: stepfun2026년 10월 8일1M 컨텍스트US$1/M 입력 토큰US$2.70/M 출력 토큰
  • stepfun의 파비콘
    StepFun: Step 3.7 FlashStep 3.7 Flash

    Step 3.7 Flash is StepFun's latest high-efficiency multimodal Mixture-of-Experts model. It pairs a 196B-parameter language backbone with a vision encoder for native image and video understanding, activating roughly 11B parameters per token. The model supports a 256K context window and exposes selectable reasoning levels (high/medium/low), letting callers trade off speed, cost, and depth of reasoning. Designed for coding, agentic workflows, structured outputs, and long-context productivity tasks.

    제작: stepfun2026년 5월 28일256K 컨텍스트US$0.20/M 입력 토큰US$1.15/M 출력 토큰