Nemotron 3.5 Bolt vs. Grok 4.7

Grok 4.7

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What is Nemotron 3.5 Bolt?

NVIDIA Nemotron 3.5 Bolt is a family of open artificial intelligence models developed to provide efficient reasoning, autonomous agent capabilities, and conversational intelligence on local computing hardware. Introduced in October 2026, the series includes Nemotron 3.5 Bolt 74B-A9B 24GB and Nemotron 3.5 Bolt E4B 4GB. The 74B-A9B variant uses a mixture-of-experts architecture containing 74 billion total parameters, with approximately 9 billion parameters activated during inference. Its native 2-bit quantization enables deployment within approximately 24GB of memory while preserving resources for other applications. The model is designed for agentic workflows that require reasoning, instruction following, tool interactions, and execution of multiple connected tasks. Developers can use Bolt 74B-A9B with local agent frameworks to conduct web research, generate software, analyze code, investigate programming errors, and perform debugging activities. NVIDIA reports strong results on agent benchmarks including PinchBench and BrowseComp, which evaluate autonomous task completion and information retrieval capabilities. The smaller Bolt E4B variant is designed for low-latency conversational AI, supporting local voice assistants, interactive game characters, and embedded interfaces. Its 4GB memory footprint makes it suitable for compatible GeForce RTX, NVIDIA Jetson, and DGX Spark systems that require efficient local inference. Running these models locally allows organizations to retain greater control over sensitive application data, reduce dependence on cloud inference, and integrate AI capabilities into existing software environments. Nemotron 3.5 Bolt 74B-A9B is available through Hugging Face with support for llama.cpp, Ollama, LM Studio, Unsloth, and vLLM, while Bolt E4B is scheduled for release on October 23, 2026.

What is Grok 4.7?

Grok 4.7 is a frontier artificial intelligence model from SpaceXAI built for demanding coding, knowledge work, and long-running agent workflows. The model uses a larger base architecture than Grok 4.6 and was trained with an extended reinforcement learning process focused on more difficult and longer-duration tasks. Its training emphasizes problems that may require hours of work, making it suitable for workflows that involve planning, execution, verification, and repeated tool use. Grok 4.7 improves self-checking behavior and long-context management so it can maintain task state more effectively across complex operations. The model also natively understands the Grok Bot harness, which improves conversational performance and general knowledge capabilities. Its use cases include software engineering, terminal tasks, document and presentation creation, legal analysis, electrical engineering, clinical reasoning, and other professional knowledge work. SpaceXAI reports benchmark gains over Grok 4.6 across coding, terminal, engineering, legal, and multi-hour office-task evaluations. Grok 4.7 includes a newly developed safeguard stack designed to strengthen jailbreak resistance and improve handling of risky cybersecurity, biological, and other dual-use requests. The company states that the model is designed to maintain strong utility for legitimate cybersecurity and research tasks while refusing more dangerous requests. Grok 4.7 is available through Grok Build, Cursor, the Grok API, coding harnesses, model routers, and supported cloud platforms, with a faster serving option also available. Pricing starts at $2 per million input tokens and $6 per million output tokens, positioning the model for developers and organizations running high-volume coding and professional AI workloads.