Featherless.ai

Kimi K2.5 is an open-source multimodal model developed by Moonshot AI and released in January 2026. It uses a Mixture-of-Experts architecture with 1 trillion total parameters and approximately 32 billion active at inference time, trained on roughly 15 trillion mixed visual and text tokens. Unlike models that add vision as a secondary capability, Kimi K2.5 was trained natively on both image and text data, enabling integrated understanding of charts, documents, video, and code.

Kimi K2.6 is an open-source, native multimodal agentic model that advances practical capabilities in long-horizon coding, coding-driven design, proactive autonomous execution, and swarm-based task orchestration.

Llama 4 Maverick is a multimodal mixture-of-experts model developed by Meta, released in early 2025. It has 17 billion active parameters drawn from a pool of 400 billion total parameters across 128 experts, and supports both text and image inputs. The model handles 12 languages and offers a 130,000-token context window, making it suited for long-document and multilingual tasks.

Llama 4 Scout is a multimodal AI model developed by Meta, released in early 2025 as part of the Llama 4 model family. It uses a Mixture of Experts (MoE) architecture with 17 billion active parameters, 16 experts, and 109 billion total parameters, processing both text and image inputs through a unified model backbone. The model supports a 130,000-token context window and is available under Meta's Llama 4 Community License.

Compare DeepSeek V4 Flash and Kimi K2.6 across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus reasoning-heavy tasks.

Compare DeepSeek V4 Pro and Kimi K2.6 across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus reasoning-heavy tasks.

Compare Gemini 2.5 Flash Lite and Kimi K2.6 across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus reasoning-heavy tasks.

Compare Gemini 2.5 Flash and Kimi K2.6 across pricing, context window, capabilities, benchmarks, and API access to choose the better fit for long-context workloads versus reasoning-heavy tasks.