Модели

12 канонических LLM-моделей от всех провайдеров

Показаны модели 1–12 из 12

Gemma 4 12B

Соединенные Штаты

Google's medium-size open-weight model with 12 billion parameters from the Gemma 4 family. Encoder-free unified multimodal architecture that natively processes text, image, audio, and video inputs without dedicated encoders. Features a 256K context window and supports 140+ languages. First medium-sized model capable of natively ingesting audio. Suitable for local deployment on GPUs with 16GB VRAM.

Контекст
262K
Добавлена
июнь 2026 г.

MiniCPM-V 4.6

Китай

Ultra-efficient multimodal language model from OpenBMB built on SigLIP2-400M and Qwen3.5-0.8B (~1B parameters). Supports single-image, multi-image, and video understanding with mixed 4x/16x visual token compression. Designed for edge deployment on iOS, Android, and HarmonyOS.

Контекст
256K
Добавлена
май 2026 г.

Qwen 3.6 27B

Китай

Alibaba's dense 27B parameter model that outperforms its own 397B MoE predecessor on agentic coding benchmarks. Strong multilingual and reasoning capabilities released under Apache 2.0.

Контекст
131K
Добавлена
апр. 2026 г.

Qwen 3.6 35B-A3B

Китай

Alibaba's efficient Mixture-of-Experts model with 35B total parameters and 3B active per token. Frontier-level agentic coding performance with 73.4% on SWE-bench Verified and 92.7 on AIME 2026. Released under Apache 2.0.

Контекст
131K
Добавлена
апр. 2026 г.

Gemma 4 31B

Соединенные Штаты

Google's flagship open-weight dense model with 31 billion parameters from the Gemma 4 family. All parameters active per forward pass with top-tier performance on reasoning benchmarks including AIME 2026 and MMLU Pro. Supports vision and extended 256K context window.

Контекст
262K
Добавлена
апр. 2026 г.

Gemma 4 31B

Соединенные Штаты

Google's flagship open-weight dense model with 31B parameters. All parameters active per forward pass. Ranks among top open models with strong performance on AIME 2026 (89.2%) and MMLU Pro (85.2%). Supports vision and extended context.

Контекст
262K
Добавлена
апр. 2026 г.

Gemma 4 26B

Соединенные Штаты

Google's high-performance open-weight dense model with 26 billion parameters from the Gemma 4 family. Supports multimodal inputs including text and images with a 256K extended context window. Strong reasoning and code generation capabilities with all parameters active per forward pass.

Контекст
262K
Добавлена
апр. 2026 г.

Mistral Large 3

Франция

Mistral AI's largest open-weight model with 41B active parameters (675B total MoE). State-of-the-art general-purpose multimodal model with 256K context window and powerful agentic capabilities. Released under Apache 2.0.

Контекст
256K
Добавлена
дек. 2025 г.

Gemma 3 12B

Соединенные Штаты

Google's mid-size open-weight model with 12 billion parameters from the Gemma 3 family. Supports multimodal inputs including text and images with a 128K context window. Strong performance on reasoning and code generation tasks at moderate compute cost.

Контекст
131K
Добавлена
март 2025 г.

Gemma 3 4B

Соединенные Штаты

Google's compact open-weight model with 4 billion parameters from the Gemma 3 family. Supports multimodal inputs including text and images with a 128K context window. Balances efficiency and capability for vision and language tasks.

Контекст
131K
Добавлена
март 2025 г.

Gemma 3 27B

Соединенные Штаты

Google's largest open-weight model in the Gemma 3 family with 27 billion parameters. Supports multimodal inputs including text and images with a 128K context window. Delivers strong performance across reasoning, code generation, and vision tasks, competitive with larger proprietary models.

Контекст
131K
Добавлена
март 2025 г.

Mistral Small 3.1

Франция

Mistral AI's Small 3.1 model with 24B parameters offering efficient multimodal capabilities including vision, function calling, and code generation with a large 128K context window.

Контекст
128K
Добавлена
март 2025 г.