{
 "query": {
  "task": "VLM"
 },
 "task": "VLM",
 "size_class": "LLM ≤4B",
 "batch": "1",
 "mixed": false,
 "mixed_warning": null,
 "groups": [
  {
   "size": "LLM ≤4B",
   "batch": "1",
   "platforms": 3,
   "rows": 3
  },
  {
   "size": "LLM ≤4B",
   "batch": "8",
   "platforms": 1,
   "rows": 1
  },
  {
   "size": "LLM 5–14B",
   "batch": "1",
   "platforms": 1,
   "rows": 2
  },
  {
   "size": "LLM 5–14B",
   "batch": "8",
   "platforms": 1,
   "rows": 2
  },
  {
   "size": "unknown",
   "batch": "1",
   "platforms": 2,
   "rows": 11
  }
 ],
 "notes": [],
 "count": 3,
 "results": [
  {
   "platform": "Axelera Metis Edge 130p PCIe card (16GB)",
   "platform_url": "/platform/axelera-metis-edge-130p-pcie-card-16gb.html",
   "perf": 7.17,
   "perf_unit": "tok/s",
   "metric": "generation_throughput",
   "model": "lfm2_5_vl_3b",
   "precision": "not stated",
   "stack": "Voyager SDK model_axscript.llm",
   "size_class": "LLM ≤4B",
   "batch": "1",
   "like_for_like": true,
   "differs": [],
   "confidence": "C",
   "confidence_label": "C – community/review",
   "power_w": null,
   "power_label": "no power published",
   "power_kind": "unknown",
   "perf_per_w": null,
   "date": "2026-10-15 (page last edited)",
   "older_than_18_months": false,
   "superseded": false,
   "power_basis": "unknown",
   "price_usd": null,
   "price_label": "unknown",
   "price_date": null,
   "price_launch_usd": null,
   "edge": true,
   "date_basis": "page-edited",
   "form_factor": "edge accelerator card",
   "vendor": "Axelera AI",
   "source": {
    "name": "Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)",
    "url": "https://github.com/axelera-ai-hub/voyager-sdk/blob/latest/docs/reference/models/model-zoo.md",
    "date": null
   },
   "power_source": null,
   "price_source": null,
   "fit": {
    "perf": null,
    "power": null,
    "budget": null
   },
   "meets_all": true,
   "unknowns": 0,
   "eligible": true,
   "headroom": null,
   "rank_score": 0.1,
   "unknown_badges": [
    "power unknown",
    "perf/W unknown",
    "price unknown"
   ],
   "evidence_tier": 1
  },
  {
   "platform": "Axelera Metis Embedded 113m M.2 card",
   "platform_url": "/platform/axelera-metis-embedded-113m-m-2-card.html",
   "perf": 7.16,
   "perf_unit": "tok/s",
   "metric": "generation_throughput",
   "model": "lfm2_5_vl_3b",
   "precision": "not stated",
   "stack": "Voyager SDK model_axscript.llm",
   "size_class": "LLM ≤4B",
   "batch": "1",
   "like_for_like": true,
   "differs": [],
   "confidence": "C",
   "confidence_label": "C – community/review",
   "power_w": null,
   "power_label": "no power published",
   "power_kind": "unknown",
   "perf_per_w": null,
   "date": "2026-10-15 (page last edited)",
   "older_than_18_months": false,
   "superseded": false,
   "power_basis": "unknown",
   "price_usd": null,
   "price_label": "unknown",
   "price_date": null,
   "price_launch_usd": null,
   "edge": true,
   "date_basis": "page-edited",
   "form_factor": "edge accelerator card",
   "vendor": "Axelera AI",
   "source": {
    "name": "Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md)",
    "url": "https://github.com/axelera-ai-hub/voyager-sdk/blob/latest/docs/reference/models/model-zoo.md",
    "date": null
   },
   "power_source": null,
   "price_source": null,
   "fit": {
    "perf": null,
    "power": null,
    "budget": null
   },
   "meets_all": true,
   "unknowns": 0,
   "eligible": true,
   "headroom": null,
   "rank_score": 0.0999,
   "unknown_badges": [
    "power unknown",
    "perf/W unknown",
    "price unknown"
   ],
   "evidence_tier": 1
  },
  {
   "platform": "NVIDIA Jetson AGX Thor",
   "platform_url": "/platform/nvidia-jetson-agx-thor.html",
   "perf": 71.7,
   "perf_unit": "tok/s",
   "metric": "tok/s gen, concurrency 1",
   "model": "Qwen2.5-VL 3B",
   "precision": "n/s on page",
   "stack": "NVIDIA (vLLM/TensorRT-LLM per page)",
   "size_class": "LLM ≤4B",
   "batch": "1",
   "like_for_like": true,
   "differs": [],
   "confidence": "D",
   "confidence_label": "D – vendor-published",
   "power_w": 130,
   "power_label": "platform spec envelope (not measured with this result)",
   "power_kind": "spec",
   "perf_per_w": 0.5515,
   "date": "on or before 2025-11-08",
   "older_than_18_months": false,
   "superseded": false,
   "power_basis": "spec: NVIDIA marketplace power 40-130 W (max 130 W)",
   "price_usd": 5499,
   "price_label": "NVIDIA marketplace list price (US), Jetson AGX Thor Developer Kit, 2026-10-16",
   "price_date": "2026-10-16",
   "price_launch_usd": 3499,
   "edge": true,
   "date_basis": "first-seen",
   "form_factor": "edge module",
   "vendor": "NVIDIA",
   "source": {
    "name": "NVIDIA Jetson Benchmarks",
    "url": "https://developer.nvidia.com/embedded/jetson-benchmarks",
    "date": null
   },
   "power_source": "https://marketplace.nvidia.com/en-us/enterprise/robotics-edge/jetson-thor-developer-kit/",
   "price_source": "https://marketplace.nvidia.com/en-us/enterprise/robotics-edge/jetson-thor-developer-kit/",
   "fit": {
    "perf": null,
    "power": null,
    "budget": null
   },
   "meets_all": true,
   "unknowns": 0,
   "eligible": true,
   "headroom": null,
   "rank_score": 1,
   "unknown_badges": [],
   "evidence_tier": 0
  }
 ],
 "no_data": null,
 "legend": "Confidence: A audited MLPerf closed, B documented third-party, C community, D vendor-published, E estimate. Unknown is never assumed."
}