Модели

8 канонических LLM-моделей от всех провайдеров

Показаны модели 1–8 из 8

MiniMax M3

Китай

MiniMax's frontier open-weight model with 1M-token context window, native multimodality (text, image, video), and strong coding capabilities. Built on MiniMax Sparse Attention (MSA) architecture, achieving 59% on SWE-Bench Pro with significantly improved efficiency at long context.

Контекст
1.0M
Добавлена
июнь 2026 г.

Yi-Lightning

Китай

01.AI's flagship large language model with enhanced Mixture-of-Experts architecture. Ranked 6th on Chatbot Arena with particularly strong results in Chinese, Math, Coding, and Hard Prompts categories. Features advanced expert segmentation and optimized KV-caching.

Контекст
131K
Добавлена
май 2026 г.

Qwen 3.7 Max

Китай

Alibaba's flagship proprietary model engineered for advanced agentic coding, complex reasoning, and long-horizon task execution. Ranked

Контекст
131K
Добавлена
май 2026 г.

Qwen 3.7 Plus

Китай

Alibaba's multimodal variant in the Qwen 3.7 family, optimized for vision understanding and multimodal tasks. Ranked

Контекст
131K
Добавлена
май 2026 г.

Qwen 3.6 Plus

Китай

Alibaba's proprietary flagship model in the Qwen 3.6 family, targeting enterprise AI workflows with stronger agentic coding capability, visual coding support, and end-to-end enterprise engineering features.

Контекст
131K
Добавлена
апр. 2026 г.

GLM-5.1

Китай

Zhipu AI's latest bilingual model with strong Chinese and English capabilities. Features improved reasoning, coding, and tool use with competitive performance on academic benchmarks.

Контекст
131K
Добавлена
март 2026 г.

MiniMax M2.7

Китай

MiniMax's latest large language model with strong multilingual and multimodal capabilities. Competitive pricing with high-quality text generation and improved reasoning performance.

Контекст
200K
Добавлена
март 2026 г.

Kimi K2.6

Китай

Moonshot AI's latest model with ultra-long context window support, strong reasoning capabilities, and excellent performance on complex multi-step tasks. Known for reliable long-document understanding.

Контекст
1.0M
Добавлена
март 2026 г.