모델
0G 네트워크에서 사용 가능한 AI 모델 탐색
A 35B hybrid MoE model enhanced with per-token reward guidance. At each decoding step, a 4B Value Model scores candidate tokens and steers generation toward higher-quality outputs, with improvements in harmlessness, helpfulness, and honesty.
Frontier natively-multimodal model on MiniMax Sparse Attention (MSA); agentic coding, native tool use, and long-horizon tasks. 1M context, thinking on by default.
0G.AI in-house model optimized for agentic coding and tool use; thinking enabled by default.
Anthropic Claude Fable 5; text and image input, text output, with a 1M-token context window. Extended thinking and tool use supported.
Anthropic Claude Opus 4.8; text and image input, text output, with a 1M-token context window. Extended thinking and tool use supported.
Fast, cost-efficient model in the GPT-5.6 family, optimized for high-volume, cost-sensitive workloads: responsive chat, classification, extraction, lightweight coding, and agentic workflows at lower latency and cost. Text and image input, text output, 1M-token context.
Flagship of the GPT-5.6 series, built for advanced reasoning, complex coding, and agentic workflows: multi-step software engineering, long-horizon problem solving, and autonomous tool use. Text and image input, text output, 1M-token context.
Balanced model in the GPT-5.6 family, tuned for workloads that need strong reasoning, coding, and agentic capability at lower cost than the flagship tier. Text and image input, text output, 1M-token context.
Alibaba flagship with native function calling and web search; 1M context.
Alibaba flagship with hybrid linear attention and sparse MoE; 1M context, 119 languages.
Alibaba multimodal model with vision and video understanding; native function calling, 1M context.
Next-generation model purpose-built for coding and agent workflows; 744B foundation.
Zhipu AI flagship purpose-built for long-horizon tasks; 744B foundation, 200K context.
Zhipu AI next-generation open-source flagship purpose-built for long-horizon tasks; 1M lossless context. Strong coding and engineering: autonomous task decomposition, architecture design, full-stack development, integration testing, and multi-platform deployment.
Moonshot AI coding model for agentic coding and tool use; multimodal input (text, image, video), thinking always on. 256K context.
DeepSeek flagship for agentic coding, multi-step workflows, and complex reasoning; 1M context, up to 384K output.
Lightweight MoE (284B total / 13B active) with native 1M context; low-latency, low-cost.
Multilingual automatic speech recognition (ASR); transcription and translation.
Asynchronous text-to-image model with Base64 output. Generates at most 2 images per request — requesting more (n > 2) returns 2 images, not an error.
Anthropic Claude Sonnet 5; text and image input, text output, with a 1M-token context window. Extended thinking and tool use supported.