Managed AI Inference & GPU Infrastructure Hosting

MiniMax-M3 is MiniMax's latest OpenAI-compatible multimodal model supporting text, image, and video input with configurable thinking (enabled, disabled, or adaptive) and optional reasoning split into reasoning_content.

Qwen3.7-Plus is Alibaba's balanced vision-language model in the Qwen 3.7 series, delivering strong multimodal perception, document intelligence, and tool-integrated reasoning at a lower cost than Qwen3.7-Max.

DeepSeek-V3.2 is DeepSeek's frontier open-source model with 685B total parameters and novel DeepSeek Sparse Attention (DSA) that reduces long-context computational cost by 50%. Trained with a scalable RL framework, it achieves performance comparable to GPT-5, earning gold-medal results at the 2025 IMO and IOI. The model includes reasoning and tool-use capabilities through large-scale agentic synthesis.

GLM-5 is Zhipu AI's February 2026 flagship — a 744B-parameter sparse MoE (40B active) with Interleaved (deep) thinking that fuses DeepSeek Sparse Attention and Multi-Token Prediction for frontier reasoning over a 200K-token window.

Kimi K2.5 is Moonshot AI's most powerful open-source model to date — a native multimodal agentic model built through continual pretraining on 15 trillion mixed visual and text tokens atop Kimi-K2-Base. With 1T total parameters (32B active), it seamlessly integrates vision, language, and advanced agentic capabilities including an Agent Swarm paradigm that coordinates up to 100 parallel sub-agents, reducing execution time by 4.5x on parallelizable tasks.

Introducing gpt-oss-120B, OpenAI's flagship open-weight model in the gpt-oss series, built for advanced reasoning, large-scale agentic workloads, and enterprise-grade automation. With 120B parameters and a highly optimized Mixture-of-Experts (MoE) architecture, it activates 12B parameters during inference, delivering exceptional intelligence while maintaining competitive latency. Designed for complex reasoning, multi-task agents, and long-horizon planning, gpt-oss-120B brings frontier-level capability to commercial and self-hosted deployments.

Nemotron 3 Nano 30B-A3B is NVIDIA's flagship open reasoning model, featuring a revolutionary hybrid Mamba-Transformer Mixture-of-Experts architecture. With 31.6B total parameters but only 3.2B active per forward pass, it delivers up to 3.3× higher throughput than comparable models while achieving state-of-the-art accuracy on reasoning, coding, and agentic benchmarks. The model supports up to 1M token context length and features configurable reasoning depth with thinking budget control.

Llama 3.3 70B Instruct is a 70B-parameter open-weight large language model from Meta, optimized for instruction following, complex reasoning, and multi-turn conversations.It is well suited for enterprise use cases such as advanced chat assistants, code reasoning, and long-document analysis with large context windows.