Grok 4.5
Grok 4.5 is SpaceXSI’s advanced AI model built for coding, agentic tasks, engineering work, and knowledge-intensive productivity. The model is trained on coding, science, engineering, and math data, with reinforcement learning focused on multi-step software engineering and technical workflows. It is designed to handle real-world development tasks such as debugging, Rust and C/C++ work, terminal tasks, long-running agentic rollouts, and end-to-end app creation from a single prompt. Grok 4.5 is also built for fast serving, token efficiency, and lower-cost execution, with pricing based on input and output token usage. Beyond coding, the model supports business productivity tasks in Grok Build, including Excel modeling, PowerPoint diagram creation, Word writing, and research-assisted office workflows. Available through Grok Build, Cursor, and the SpaceXSI API console, Grok 4.5 gives developers and teams a high-performance model for building software, automating work, and more.
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Grok 4.7
Grok 4.7 is a frontier AI model from SpaceXSI designed for coding, professional knowledge work, and longer-running agentic tasks. The model uses a larger base architecture than Grok 4.6 and was trained with an extended reinforcement learning process focused on difficult tasks that can take many hours to complete. Grok 4.7 improves self-verification, long-context management, conversational performance, and general knowledge work while adding native understanding of the Grok Bot harness. It is designed for software engineering, terminal-based work, document creation, presentations, legal tasks, electrical engineering, clinical reasoning, and other professional workflows. The model also introduces a new safeguard stack focused on jailbreak resistance, risky cybersecurity requests, and other dual-use domains while preserving utility for legitimate work. Grok 4.7 is available through Grok Build, Cursor, the Grok API, third-party coding harnesses, model routers, and cloud platforms.
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Nemotron 3 Ultra
Nemotron 3 Nano is a compact, open large language model in NVIDIA’s Nemotron 3 family, designed for efficient agentic reasoning, conversational AI, and coding tasks. It uses a hybrid Mixture-of-Experts Mamba-Transformer architecture that activates only a small subset of parameters per token, enabling low-latency inference while maintaining strong accuracy and reasoning performance. It has approximately 31.6 billion total parameters with around 3.2 billion active (3.6 billion including embeddings), allowing it to achieve higher accuracy than previous Nemotron 2 Nano while using less computation per forward pass. Nemotron 3 Nano supports long-context processing of up to one million tokens, enabling it to handle large documents, multi-step workflows, and extended reasoning chains in a single pass. It is designed for high-throughput, real-time execution, excelling in multi-turn conversations, tool calling, and agent-based workflows where tasks require planning, reasoning, and more.
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Claude Sonnet 5.5
Claude Sonnet 5.5 is Anthropic’s mid-tier Claude 5.5 model designed for fast, well-scoped everyday work, coding, and professional document creation. Anthropic says it runs more than 30% faster than Claude Sonnet 5 and typically costs up to 30% less per task while keeping the same base token pricing. The model shows major gains in agentic coding, with a 70.6% score on Terminal-Bench 4.0 and stronger performance on FrontierCode and CursorBench than its predecessor. Sonnet 5.5 also performs strongly on knowledge work, computer use, chart understanding, and long-horizon tasks, in some cases approaching Claude Opus 5.5 at higher effort settings. Anthropic positions it as especially useful for debugging, routine coding, collaboration, and producing polished documents, slides, spreadsheets, and user interfaces. Claude Sonnet 5.5 is available across Anthropic’s platforms as well as AWS, Google Cloud, and Microsoft Azure.
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