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Favicon for Darkbloom

Darkbloom

Browse models provided by Darkbloom (Terms of Service)

3 models

Tokens processed on OpenRouter

  • Favicon for qwen
    Qwen: Qwen3.6 35B A3BQwen3.6 35B A3B

    Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated DeltaNet linear attention with standard gated attention layers, enabling efficient inference at a fraction of the compute cost. The model supports a 262K token native context window (extensible to 1M via YaRN) and accepts text, image, and video inputs. It includes integrated thinking mode with reasoning traces preserved across multi-turn conversations, function calling, and structured output. Released under the Apache 2.0 license.

    by qwenApr 27, 2026262K context$0.08/M input tokens$0.75/M output tokens
  • Favicon for google
    Google: Gemma 4 26B A4B Gemma 4 26B A4B Free variant

    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.

    by googleApr 3, 2026262K context$0/M input tokens$0/M output tokens
  • Favicon for openai
    OpenAI: gpt-oss-20bgpt-oss-20bFree variant

    gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for lower-latency inference and deployability on consumer or single-GPU hardware. The model is trained in OpenAI’s Harmony response format and supports reasoning level configuration, fine-tuning, and agentic capabilities including function calling, tool use, and structured outputs.

    by openaiAug 5, 2025131K context$0/M input tokens$0/M output tokens