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Favicon für NextBit

NextBit

Modelle durchsuchen, bereitgestellt von NextBit (Nutzungsbedingungen)

7 Modelle

Auf OpenRouter verarbeitete Token

  • Favicon für z-ai
    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.

    von z-ai26. Aug. 20261,05M Kontext0,12 $/M Eingabe Token0,45 $/M Ausgabe Token
  • Favicon für google
    Google: Gemma 4 26B A4B Gemma 4 26B A4B
    15% off

    Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at a fraction of the compute cost. Supports multimodal input including text, images, and video (up to 60s at 1fps). Features a 256K token context window, native function calling, configurable thinking/reasoning mode, and structured output support. Released under Apache 2.0.

    von google3. Apr. 2026262K Kontext0,0765 $/M Eingabe Token0,255 $/M Ausgabe Token
  • Favicon für google
    Google: Gemma 4 31BGemma 4 31B

    Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function calling, and multilingual support across 140+ languages. Strong on coding, reasoning, and document understanding tasks. Apache 2.0 license.

    von google2. Apr. 2026262K Kontext0,15 $/M Eingabe Token0,40 $/M Ausgabe Token
  • Favicon für qwen
    Qwen: Qwen3 14BQwen3 14B

    Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for tasks like math, programming, and logical inference, and a "non-thinking" mode for general-purpose conversation. The model is fine-tuned for instruction-following, agent tool use, creative writing, and multilingual tasks across 100+ languages and dialects. It natively handles 32K token contexts and can extend to 131K tokens using YaRN-based scaling.

    von qwen28. Apr. 2025132K Kontext0,10 $/M Eingabe Token0,22 $/M Ausgabe Token
  • Favicon für google
    Google: Gemma 3 12BGemma 3 12B

    Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 12B is the second largest in the family of Gemma 3 models after Gemma 3 27B

    von google13. März 2025131K Kontext0,075 $/M Eingabe Token0,15 $/M Ausgabe Token
  • Favicon für google
    Google: Gemma 3 27BGemma 3 27B

    Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities, including structured outputs and function calling. Gemma 3 27B is Google's latest open source model, successor to Gemma 2

    von google12. März 2025131K Kontext0,08 $/M Eingabe Token0,35 $/M Ausgabe Token
  • Favicon für google
    Google: Gemma 2 27BGemma 2 27B

    Gemma 2 27B by Google is an open model built from the same research and technology used to create the Gemini models. Gemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning. See the launch announcement for more details. Usage of Gemma is subject to Google's Gemma Terms of Use.

    von google13. Juli 20248K Kontext0,65 $/M Eingabe Token0,65 $/M Ausgabe Token