NVIDIA H200 Rig Spurs Model Hunt

The real question here is not “what fits” but “what can a dev team actually use well” when the box is this large. For a shared coding playground, the smartest move looks like a two-tier stack: one frontier model for hard asks and one smaller, fast model for autocomplete and cheap agent loops.

• –Qwen3.5 397B-A17B is the thread’s obvious raw-capability pick; at 4-bit, dual H200s give it enough room for long context while still chasing the highest ceiling.
• –MiniMax M2.5, Step 3.5 Flash, and Kimi K2.5 show up as the more interesting coding/agent contenders, because they optimize for tool use and workflow value, not just chat quality.
• –vLLM or SGLang makes more sense than Ollama on hardware like this once you care about multi-user serving, latency under load, and longer contexts.
• –If the goal is IDE support for several developers, a single giant model is less useful than a routed setup with one premium coder and one fast model for completion, review, and lightweight agent tasks.
• –The H200 itself is doing exactly what it was built for here: turning “local LLM” from hobbyist experiment into an internal platform decision.