[cbangera2]

Stacked on #114 (uses its eval script). Verdict up front: TanStack ships no dedicated NIM package — NIM is OpenAI-compatible, so it rides our existing transport with zero adapter changes.

App

• New nvidia-nim provider preset (https://integrate.api.nvidia.com/v1, default nvidia/llama-3.1-nemotron-70b-instruct — verified present in the live NIM catalog; the first pick, llama-3.3-nemotron-super-49b, is no longer listed, so don't use it).
• Desktop keychain scope extended (assistant.nvidia-nim); hosted-consent + HTTPS-native guards apply unchanged (no panel changes needed).
• Needs a build.nvidia.com key (free prototyping tier); works today, unverified live (no key on hand).

Eval

• --base-url= / --api-key= / --all-models (implied off-OpenRouter): same 7 finance cases against any OpenAI-compatible base. Key resolution prefers NVIDIA_* names on non-OpenRouter bases; OpenRouter attribution headers are gated to OpenRouter.
• Verified: NIM catalog lists live (81 models, 16 nemotron) via --list-only --match=nemotron.

To benchmark once you have a key

NVIDIA_API_KEY=nvapi-... node evals/free-models.eval.mjs --base-url=https://integrate.api.nvidia.com/v1 --match=nemotron --limit=5

Checks

• pnpm format:check / lint / typecheck green; full unit suite 1116 passed.

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