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Wafer의 파비콘

Wafer

다음이 제공하는 모델 찾아보기: Wafer (서비스 약관)

10 모델

OpenRouter에서 처리된 토큰

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

    DeepSeek 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.

    제공: deepseek2026년 9월 10일1.05M contextUS$0.09/M 입력 토큰US$0.99/M 출력 토큰
  • z-ai의 파비콘
    Z.ai: GLM 5.3 FlashGLM 5.3 Flash

    GLM-5.3-Flash is a native multimodal model from Z.ai. It is suited for efficient coding and long-horizon agent tasks. Its hybrid sparse and linear attention architecture maintains accurate long-context behavior while reducing compute overhead.

    제공: z-ai2026년 8월 26일1.05M contextUS$0.09/M 입력 토큰US$0.50/M 출력 토큰
  • z-ai의 파비콘
    Z.ai: GLM 5.3GLM 5.3

    GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves on GLM-5.2 in coding and in the balance between performance and token efficiency. Reasoning is always on and cannot be disabled. Reasoning efforts low, high, and max are supported; max is the default.

    제공: z-ai2026년 8월 18일1.05M contextUS$0.079/M 입력 토큰US$4.80/M 출력 토큰
  • qwen의 파비콘
    Qwen: Qwen3.8 27BQwen3.8 27B

    Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be enabled or disabled.

    제공: qwen2026년 8월 14일262K contextUS$0.04/M 입력 토큰US$2.30/M 출력 토큰
  • deepseek의 파비콘
    DeepSeek: DeepSeek V4 Pro 0813DeepSeek V4 Pro 0813

    DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.

    제공: deepseek2026년 8월 12일1.05M contextUS$0.25/M 입력 토큰US$5/M 출력 토큰
  • nvidia의 파비콘
    NVIDIA: Nemotron 3.5 LightningNemotron 3.5 Lightning

    NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that benefit from domain-specific customization.

    제공: nvidia2026년 8월 11일1M contextUS$0.035/M 입력 토큰US$0.13/M 출력 토큰
  • deepseek의 파비콘
    DeepSeek: DeepSeek V4 Flash 0731DeepSeek V4 Flash 0731

    DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total. This re-post-trained revision is suited for coding, reasoning, and agent workflows. This is the GA release of DeepSeek V4 Flash.

    제공: deepseek2026년 7월 31일1.05M contextUS$0.13/M 입력 토큰US$0.23/M 출력 토큰
  • moonshotai의 파비콘
    MoonshotAI: Kimi K3Kimi K3

    Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at navigating large repositories, using tools, debugging, and iterating against images, logs, tests, and runtime feedback. Its architecture uses KDA and Attention Residuals for computational efficiency.

    제공: moonshotai2026년 7월 16일1.05M contextUS$0.78/M 입력 토큰US$24/M 출력 토큰
  • z-ai의 파비콘
    Z.ai: GLM 5.2GLM 5.2

    GLM 5.2 is a large-scale reasoning model from Z.ai. It supports text input and output with a 1M-token context window, and is suited for long-horizon agent workflows, project-level software engineering, and complex multi-step automation. Reasoning efforts high and xhigh are supported; xhigh maps to max reasoning. It is particularly strong at coding and tool use across long-running tasks, able to maintain engineering context and follow standards consistently through a full development workflow, from requirements to multi-platform deployment, in a single task.

    제공: z-ai2026년 6월 16일1.05M contextUS$0.06/M 입력 토큰US$7/M 출력 토큰
  • deepseek의 파비콘
    DeepSeek: DeepSeek V4 Flash 0423DeepSeek V4 Flash 0423

    DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B activated parameters, supporting a 1M-token context window. It is designed for fast inference and high-throughput workloads, while maintaining strong reasoning and coding performance. The model includes hybrid attention for efficient long-context processing. Reasoning efforts high and xhigh are supported; xhigh maps to max reasoning. It is well suited for applications such as coding assistants, chat systems, and agent workflows where responsiveness and cost efficiency are important.

    제공: deepseek2026년 4월 24일1.05M contextUS$0.37/M 입력 토큰US$0.17/M 출력 토큰