MiniMax-M3 is MiniMax’s frontier multimodal coding and agentic model, built on the MiniMax Sparse Attention (MSA) architecture. It supports up to a 1M-token context window and accepts image and video inputs. The model is designed for code generation, agentic workflows, tool use, long-context understanding, and multi-step reasoning, showing strong performance on benchmarks such as SWE-Bench Pro, Terminal-Bench 2.1, and MCP Atlas....

DeepSeek-V4-Pro is DeepSeek's flagship open-source MoE model with 1.6T total parameters and 49B activated, purpose-built for frontier-level reasoning, coding, and agentic tasks. Supporting a 1M-token context window and three reasoning effort modes up to Think Max, it achieves top-tier performance on coding benchmarks such as LiveCodeBench and Codeforces — rivaling leading closed-source models — and is released under the MIT License....

DeepSeek-V4-Flash is DeepSeek's latest open-source MoE model featuring 284B total parameters with only 13B activated during inference, delivering high-speed generation without sacrificing capability. With native support for a 1M-token context window and three switchable reasoning modes — Non-Think, Think High, and Think Max — it offers flexible intelligence scaling from everyday tasks to complex reasoning, all under the MIT License....

Kimi K2.6 is an open-source, native multimodal agentic model by Moonshot AI, achieving open-source state-of-the-art on benchmarks including HLE with tools, SWE-Bench Pro, and BrowseComp. Built on a MoE architecture with 1T total parameters and 32B activated, the model supports a 256K-token context window and multimodal inputs (image and video) via its MoonViT vision encoder. K2.6 is optimized for agentic workloads: it sustains 4,000+ tool calls over 12+ hours of continuous execution, scales to 300 parallel sub-agents × 4,000 steps per run to produce 100+ files from a single prompt, and supports both Thinking and Instant inference modes with function calling and multi-turn Preserve Thinking...