diff --git a/src/lib/inference/local.ts b/src/lib/inference/local.ts
index 4e1db6238cf..c4deff5f1c8 100644
--- a/src/lib/inference/local.ts
+++ b/src/lib/inference/local.ts
@@ -175,8 +175,10 @@ export interface GpuInfo {
    * `true` for integrated/iGPU class devices whose token-generation throughput
    * is too low to clear agent-loop timeouts on 30B-class models, even when
    * advertised memory ostensibly fits. Populated for Jetson (Tegra/Thor/Orin)
-   * platforms. Drives the `computeIntensive` exclusion in the bootstrap-model
-   * selector so compute-constrained hosts are not steered onto 30B+ tags.
+   * platforms and the Windows-ARM N1X integrated GPU (the JMJWOA-Generic
+   * placeholder that clears the bounded Docker CUDA proof). Drives the
+   * `computeIntensive` exclusion in the bootstrap-model selector so
+   * compute-constrained hosts are not steered onto 30B+ tags.
    */
   computeConstrained?: boolean;
 }
diff --git a/src/lib/inference/nim-igpu-compute-constrained.test.ts b/src/lib/inference/nim-igpu-compute-constrained.test.ts
new file mode 100644
index 00000000000..d1d2b07326b
--- /dev/null
+++ b/src/lib/inference/nim-igpu-compute-constrained.test.ts
@@ -0,0 +1,193 @@
+// SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+// SPDX-License-Identifier: Apache-2.0
+
+import { createRequire } from "module";
+import type { Mock } from "vitest";
+import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
+
+// Import source directly so tests cannot pass against a stale build.
+import "./nim";
+import { fittableOllamaModelTags, largestFittableOllamaModelTag } from "./ollama-model-registry";
+
+const require = createRequire(import.meta.url);
+const NIM_DIST_PATH = require.resolve("./nim");
+const RUNNER_PATH = require.resolve("../runner");
+const fs = require("fs");
+
+// Route the firmware reads detectGpu makes without branching in the test body.
+function withFirmwareModel(model: string, fn: () => void): void {
+  const orig = fs.readFileSync;
+  const overrides: Record<string, string> = {
+    "/sys/class/dmi/id/product_name": model,
+    "/sys/firmware/devicetree/base/model": "",
+  };
+  fs.readFileSync = (p: string, ...args: unknown[]) =>
+    p in overrides ? overrides[p] : orig(p, ...args);
+  try {
+    fn();
+  } finally {
+    fs.readFileSync = orig;
+  }
+}
+
+// Jetson/Tegra firmware: no DMI product_name, a devicetree model, and the
+// /dev/nvhost-gpu node present. Kept branch-free via a lookup table.
+function withJetsonFirmware(model: string, fn: () => void): void {
+  const origRead = fs.readFileSync;
+  const origExists = fs.existsSync;
+  const readers: Record<string, () => string> = {
+    "/sys/class/dmi/id/product_name": () => {
+      throw new Error("ENOENT");
+    },
+    "/sys/firmware/devicetree/base/model": () => model,
+  };
+  fs.readFileSync = (p: string, ...args: unknown[]) =>
+    p in readers ? readers[p]() : origRead(p, ...args);
+  fs.existsSync = (p: string) => p === "/dev/nvhost-gpu" || origExists(p);
+  try {
+    fn();
+  } finally {
+    fs.readFileSync = origRead;
+    fs.existsSync = origExists;
+  }
+}
+
+function loadNimWithMockedRunner(runCapture: Mock) {
+  const runner = require(RUNNER_PATH);
+  const originalRun = runner.run;
+  const originalRunCapture = runner.runCapture;
+
+  delete require.cache[NIM_DIST_PATH];
+  runner.run = vi.fn();
+  runner.runCapture = runCapture;
+  const nimModule = require(NIM_DIST_PATH);
+
+  return {
+    nimModule,
+    restore() {
+      delete require.cache[NIM_DIST_PATH];
+      runner.run = originalRun;
+      runner.runCapture = originalRunCapture;
+    },
+  };
+}
+
+// Answer the `name,memory.total` nvidia-smi query with a fixed row set; every
+// other command yields "" (a linear predicate, no branching).
+function nvidiaSmiRunner(smiOutput: string): Mock {
+  return vi.fn((cmd: string | string[]) =>
+    Array.isArray(cmd) &&
+    cmd[0] === "nvidia-smi" &&
+    cmd.some((a: string) => a.includes("name,memory.total"))
+      ? smiOutput
+      : "",
+  );
+}
+
+// Jetson path has no nvidia-smi; memory comes from `free -m`.
+function freeMemoryRunner(freeOutput: string): Mock {
+  return vi.fn((cmd: string | string[]) => {
+    const argv = Array.isArray(cmd) ? cmd : [];
+    return `${argv[0] ?? ""} ${argv[1] ?? ""}`.trim() === "free -m" ? freeOutput : "";
+  });
+}
+
+// #3707: the Windows-ARM N1X iGPU (the denylisted JMJWOA-Generic placeholder
+// that clears the bounded Docker CUDA proof) is memory-shared like Jetson and
+// cannot serve a computeIntensive model in-loop, so detectGpu tags it
+// computeConstrained and the Ollama bootstrap-model selector skips the
+// computeIntensive 30B/35B entries. A genuine discrete NVIDIA GPU never reaches
+// that path and must stay untagged.
+describe("detectGpu computeConstrained tagging (#3707)", () => {
+  // detectGpu applies an ARM64-Linux kernel-interface trust gate; pin
+  // /proc/driver/nvidia present so genuine discrete GPUs are trusted on the
+  // arm64 runner (matches the detectGpu suite default).
+  let savedExistsSync: typeof fs.existsSync;
+  beforeEach(() => {
+    savedExistsSync = fs.existsSync;
+    fs.existsSync = (p: string) => (p === "/proc/driver/nvidia" ? true : savedExistsSync(p));
+  });
+  afterEach(() => {
+    fs.existsSync = savedExistsSync;
+  });
+
+  it("marks the proof-passed N1X iGPU computeConstrained", () => {
+    const { nimModule, restore } = loadNimWithMockedRunner(
+      nvidiaSmiRunner("JMJWOA-Generic-GPU, 65471, 65000\n"),
+    );
+    const proveArm64WslDockerDesktopGpu = vi.fn(() => ({
+      passed: true,
+      timedOut: false,
+      exitCode: 0,
+      diagnostic: "",
+    }));
+    try {
+      withFirmwareModel("Microsoft Corporation Virtual Machine", () => {
+        expect(nimModule.detectGpu({ proveArm64WslDockerDesktopGpu })).toMatchObject({
+          type: "nvidia",
+          name: "JMJWOA-Generic-GPU",
+          wslDockerDesktopGpuProofPassed: true,
+          computeConstrained: true,
+        });
+      });
+    } finally {
+      restore();
+    }
+  });
+
+  it("excludes the computeIntensive Ollama defaults for the proof-passed N1X iGPU", () => {
+    const { nimModule, restore } = loadNimWithMockedRunner(
+      nvidiaSmiRunner("JMJWOA-Generic-GPU, 65471, 65000\n"),
+    );
+    const proveArm64WslDockerDesktopGpu = vi.fn(() => ({
+      passed: true,
+      timedOut: false,
+      exitCode: 0,
+      diagnostic: "",
+    }));
+    try {
+      withFirmwareModel("Microsoft Corporation Virtual Machine", () => {
+        const gpu = nimModule.detectGpu({ proveArm64WslDockerDesktopGpu });
+        const fittable = fittableOllamaModelTags(gpu);
+        expect(fittable).not.toContain("qwen3.6:35b");
+        expect(fittable).not.toContain("nemotron-3-nano:30b");
+        expect(largestFittableOllamaModelTag(gpu)).toBe("qwen3.5:9b");
+      });
+    } finally {
+      restore();
+    }
+  });
+
+  it("marks a Jetson/Tegra GPU computeConstrained", () => {
+    const free =
+      "              total        used        free      shared  buff/cache   available\n" +
+      "Mem:          65536        4096       50000         512       10928       60000\n" +
+      "Swap:             0           0           0";
+    const { nimModule, restore } = loadNimWithMockedRunner(freeMemoryRunner(free));
+    try {
+      withJetsonFirmware("NVIDIA Jetson AGX Orin\0", () => {
+        expect(nimModule.detectGpu()).toMatchObject({
+          type: "nvidia",
+          platform: "jetson",
+          computeConstrained: true,
+        });
+      });
+    } finally {
+      restore();
+    }
+  });
+
+  it("leaves a genuine discrete NVIDIA GPU unconstrained", () => {
+    const { nimModule, restore } = loadNimWithMockedRunner(
+      nvidiaSmiRunner("NVIDIA H100 80GB HBM3, 81920, 81000\n"),
+    );
+    try {
+      const gpu = nimModule.detectGpu();
+      expect(gpu).toMatchObject({ type: "nvidia", name: "NVIDIA H100 80GB HBM3" });
+      expect(gpu).not.toHaveProperty("computeConstrained");
+      expect(gpu).not.toHaveProperty("wslDockerDesktopGpuProofPassed");
+    } finally {
+      restore();
+    }
+  });
+});
diff --git a/src/lib/inference/nim.ts b/src/lib/inference/nim.ts
index 0767c3ebc5e..5be3d0d902c 100644
--- a/src/lib/inference/nim.ts
+++ b/src/lib/inference/nim.ts
@@ -510,7 +510,12 @@ export function detectGpu(deps: DetectGpuDeps = {}): GpuDetection | null {
           nimCapable: canRunNimWithMemory(totalMemoryMB),
           platform,
           spark: platform === "spark",
-          ...(platform === "jetson" ? { computeConstrained: true } : {}),
+          // The proof-passed Windows-ARM N1X iGPU is memory-shared like Jetson
+          // and cannot serve a computeIntensive model in-loop, so tag it
+          // computeConstrained to exclude those Ollama bootstrap models (#3707).
+          ...(platform === "jetson" || wslDockerDesktopGpuProofPassed
+            ? { computeConstrained: true }
+            : {}),
           ...(wslDockerDesktopGpuProofPassed ? { wslDockerDesktopGpuProofPassed: true } : {}),
         };
       }