Jetson AGX Orin 64GB for Edge AI — Specs, Sizing & Deployment Fit
Last updated: September 2026
The high-density workhorse: 275 TOPS, 64 GB of unified memory, and ~20-stream planning capacity for heavy multi-model pipelines and ≤13B-parameter LLMs.
Planning Takeaway
The high-density workhorse: 275 TOPS, 64 GB of unified memory, and ~20-stream planning capacity for heavy multi-model pipelines and ≤13B-parameter LLMs. Since July 2026 it shares its ~$2,999 module price with the newer Jetson T4000 — a real decision point for new designs.
Specifications
| Spec | Value |
|---|---|
| Compute | 275 INT8 TOPS (Ampere GPU + 2× NVDLA) |
| Memory | 64 GB LPDDR5, ~204.8 GB/s |
| Power modes | 15W · 30W · 50W · MAXN (15–60 W envelope; the 40W preset belongs to the 32GB variant) |
| Video decode (datasheet) | H.265 22× 1080p30 / 7× 4K30 · H.264 13× 1080p30 / 3× 4K30 (source) |
| Est. planning capacity | ~20 concurrent 1080p detection streams |
| Cooling | Active required |
| Form factor | Jetson AGX module (100×87 mm) |
| Runtimes / precisions | TensorRT, PyTorch, ONNX, llama.cpp · FP32/FP16/INT8 |
| Software | JetPack 7.2 (Ubuntu 24.04, CUDA 13, June 2026) — current; JetPack 6.x (Ubuntu 22.04) — legacy track. Sibling AGX Orin 32GB module (~$1,799) gained MAXN_SUPER on JetPack 7.2 (200 → 241 TOPS) |
| Indicative price | ~$2,999 module / ~$3,499 dev kit (as of mid-2026) |
Sizing Fit
Suits 16-camera-class analytics nodes, multi-model + VLM co-location within 64 GB, and head-node roles in hierarchical edge deployments.
- 16-camera smart-city traffic architecture — Reference architecture
- Thor vs AGX Orin decision framework — Comparison
- Which VLM fits which Jetson — Guide
- Multi-model inference on Jetson — Guide
- YOLO with TensorRT: FP16 vs INT8 throughput — Benchmarks
- Camera interfaces: CSI vs USB vs GMSL vs IP — Guide
Decision Framework
Choose the AGX Orin 64GB if:
- You need 16+ streams or heavy multi-model pipelines with headroom on one node.
- Your workload includes quantized LLMs up to roughly the 13B–30B (GGUF Q4) class alongside vision.
- You want the mature, widely deployed AGX ecosystem, carrier options, and a dev kit (~$3,499).
Choose a sibling instead if:
- Jetson T4000 — starting a new design at the same ~$2,999: newer Blackwell-generation FP4 compute in a lower power envelope, at the cost of a younger ecosystem.
- Jetson AGX Thor T5000 — you need 70B-class on-device LLMs, VLA robotics models, or 128 GB memory.
- Jetson Orin NX 16GB — your node serves ≤12 streams — the ~$999 NX is the better-balanced spend.
Video decode & encode (datasheet)
Hardware codec limits for the Jetson AGX Orin 64GB as NVIDIA publishes them, identical in every power mode. Streams per module at 1080p30 and 4K30, rated decoder throughput, and NVENC streams at 1080p30. Full profile tables, sources and class-D interpolation: decode capacity for the Jetson AGX Orin 64GB.
| Codec | Decode 1080p30 | Decode 4K30 | Decode MP/s | Encode 1080p30 |
|---|---|---|---|---|
| H.265 | 22 | 7 | 1300 | 16 |
| H.264 | 13 | 3 | 850 | 14 |
| AV1 | 18 | 6 | 1200 | 16 |
| VP9 | 18 | 6 | 1200 | — |
NVIDIA · DS-10662-001 v1.8 §4.4 Multi-Standard Video Decoder, Table 4-2 (JAO 64GB) · verified 2026-09-07 · Jetson AGX Orin Series Modules Data Sheet · class A
Production carriers
9 carrier boards, systems and developer kits in the registry list the Jetson AGX Orin 64GB, each with power, camera, Ethernet/PoE, expansion and price cited to the vendor or a reseller. Full ranked table and common-needs shortlist: production carriers for the Jetson AGX Orin 64GB.
- NVIDIA Jetson AGX Orin Developer Kit (reference carrier) (developer kit, $3,499)
- Seeed Studio reServer Industrial J501 (carrier board, $379)
- Connect Tech Inc. Forge Carrier (carrier board)
- Auvidea X230D Carrier Board (carrier board)
- Aetina Corporation AIE-PX11/12/21/22 (system)
Frequently Asked Questions
How much does the Jetson AGX Orin 64GB cost?
As of the July 2026 NVIDIA repricing: ~$2,999 for the module (up from $1,599) and ~$3,499 for the developer kit. The AGX Orin 32GB module lists at ~$1,799.
AGX Orin 64GB or Jetson T4000 — they cost the same?
Both modules list at ~$2,999 as of mid-2026. The AGX Orin 64GB offers the mature ecosystem, 64 GB, and proven carrier/thermal designs; the T4000 offers newer-generation compute (up to ~1200 FP4 TFLOPs) in a lower power envelope but a younger deployment ecosystem. For established vision fleets choose AGX; for new long-horizon designs weigh the T4000 seriously.
Can the AGX Orin 64GB run large language models?
Yes, within limits: 13B-class models run comfortably quantized, and ~30B-class fits with GGUF Q4. It lacks FP4 hardware, so 70B-class on-device models are Thor territory.
What JetPack version does the AGX Orin run?
JetPack 7.2 (June 2026) is current for this module — Ubuntu 24.04, Linux kernel 6.8, CUDA 13. JetPack 6.x remains a widely deployed legacy track on Ubuntu 22.04. Moving an existing JetPack 6 install to 7 requires the OTA package or a full reflash — a plain apt upgrade is not an upgrade path. JetPack 7.2 also added MAXN_SUPER on the sibling AGX Orin 32GB, lifting it from 200 to 241 TOPS.