AI chip · NVIDIA
NVIDIA Jetson AGX Orin
Ampere-based embedded AI compute module (32-64 GB), the dominant robotics-side Nvidia SKU 2022-2025 before Jetson Thor ramp.
On the DEPLOY graph: 9 robots on record adopt this chip.
Market position
AGX Orin is the humanoid + delivery-robot standard chip of 2023-2025: 275 TOPS in a 60 W automotive module. Figure, Apptronik Apollo, Agility Digit and dozens of Chinese humanoids shipped on it before Thor became available.
DEPLOY editorial. What the vendor PDF cannot tell you.
What fits in 64 GB
Weights-only footprint for public open-weight LLMs. Pure arithmetic: params × bytes/param. Excludes KV cache and activation memory; add ~10-30% headroom for real serving. A model that does not fit at FP16 may still fit at INT8 or INT4 with quality trade-offs. Not a benchmark.
| Model | Params | FP16 | INT8 | INT4 |
|---|---|---|---|---|
| Llama 3.1 8B dense | 8 B | 16 GB ✓ | 8 GB ✓ | 4 GB ✓ |
| Llama 3.1 70B dense | 70 B | 140 GB ✗ | 70 GB ✗ | 35 GB ✓ |
| Llama 3.1 405B dense | 405 B | 810 GB ✗ | 405 GB ✗ | 203 GB ✗ |
| Llama 3.3 70B dense | 70 B | 140 GB ✗ | 70 GB ✗ | 35 GB ✓ |
| DeepSeek V3 MoE (671B total, 37B active per token) | 671 B | 1342 GB ✗ | 671 GB ✗ | 336 GB ✗ |
| DeepSeek R1 MoE (671B total, 37B active per token) | 671 B | 1342 GB ✗ | 671 GB ✗ | 336 GB ✗ |
| Qwen 2.5 7B dense | 7 B | 14 GB ✓ | 7 GB ✓ | 4 GB ✓ |
| Qwen 2.5 72B dense | 72 B | 144 GB ✗ | 72 GB ✗ | 36 GB ✓ |
| Mixtral 8x7B MoE (46.7B total, 12.9B active per token) | 46.7 B | 93 GB ✗ | 47 GB ✓ | 23 GB ✓ |
| Mixtral 8x22B MoE (141B total, 39B active per token) | 141 B | 282 GB ✗ | 141 GB ✗ | 71 GB ✗ |
| Gemma 2 27B dense | 27 B | 54 GB ✓ | 27 GB ✓ | 14 GB ✓ |
| Command R+ dense | 104 B | 208 GB ✗ | 104 GB ✗ | 52 GB ✓ |
| Kimi K2 MoE (1T total, 32B active per token) | 1000 B | 2000 GB ✗ | 1000 GB ✗ | 500 GB ✗ |
Math: FP16 = params × 2 bytes; INT8 = params × 1 byte; INT4 = params × 0.5 bytes. MoE models sum every expert (full weights on disk), not the per-token active subset.
Common questions
Answer-first, sourced. Every claim below traces to a specific field on this page or a cited datasheet. FAQPage schema is emitted so LLM crawlers can lift these verbatim.
How much does NVIDIA Jetson AGX Orin cost?
NVIDIA Jetson AGX Orin launch pricing is not on record in the DEPLOY registry. Vendor list prices are typically published in the vendor's own briefing rather than the datasheet.
How much memory does NVIDIA Jetson AGX Orin have?
64 GB of LPDDR5 at 204.8 GB/s. Vendor datasheet, first-party.
How much power does one NVIDIA Jetson AGX Orin draw?
60 W TDP (thermal design power) per chip. System-level draw is higher: see the reference-design section for rack-level kW.
What runs on NVIDIA Jetson AGX Orin?
9 robot models on the DEPLOY registry adopt this chip, including Spot, Serve Gen 3, Unitree G1, and 6 more. Full list below.
Which open-weight LLMs fit on one NVIDIA Jetson AGX Orin?
Of the 13 public open-weight LLMs DEPLOY tracks: 3 fit at FP16, 4 at INT8, 8 at INT4 (weights only, excludes KV cache). The full table is above with per-model math. Sparsity, offloading and multi-GPU serving change the picture; this row is single-chip weights-only.
Key facts
- Class
- Compute SoC (AI accelerator)
- Designer
- NVIDIA
- Safety-critical?
- Yes (embedded / automotive)
- Record as of
- 2026-08-25
Specifications (10 fields, click to expand)
Vendor datasheet figures (first-party). Dense throughput first; sparse (2:4) in parentheses where NVIDIA quotes it. The exhaustive spec sheet lives on the datasheet URL below the table: this row set covers what buyers actually compare on.
- Process node
- Samsung 8N
- CUDA cores
- 2,048
- Tensor cores
- 64 (3rd gen (Ampere))
- TDP
- 60 W
- Memory
- 64 GB LPDDR5
- Memory bandwidth
- 204.8 GB/s
- INT8 (dense)
- 275 TOPS
- Form factor
- Module (AGX Orin 64GB)
- Announced
- 2022-03-22
- Released
- 2022-07-01
Source: vendor datasheet
Generation
Compare with
Robot models running NVIDIA Jetson AGX Orin
Every model on the DEPLOY registry with a public chip-integration claim for NVIDIA Jetson AGX Orin. Ranked by verified deployment count.
| Model | Maker | Form factor | Role | Source | Deployments |
|---|---|---|---|---|---|
| Spot | Boston Dynamics | quadruped | onboard AI compute (CORE I/O) | reported | 28 |
| Serve Gen 3 | Serve Robotics | sidewalk | primary inference compute | reported | 15 |
| Unitree G1 | Unitree Robotics | humanoid | developer-kit inference option | reported | 10 |
| May Mobility Autonomous Sienna | May Mobility | av | onboard AV compute | reported | 9 |
| Cruise AV (Chevrolet Bolt) | Cruise | av | primary inference compute | reported | 6 |
| Unitree H1 | Unitree Robotics | humanoid | developer-kit inference option | reported | 5 |
| Digit v5 | Agility Robotics | humanoid | primary inference compute | reported | 4 |
| Booster T1 | Booster Robotics | humanoid | onboard humanoid compute | reported | 2 |
| Cassie | Agility Robotics | humanoid | onboard bipedal compute | inferred | 0 |
Sources
- Jetson OrinNvidia
Adoption rows appear as we verify chip-integration claims per model. Every row is a public claim the maker or a tier-1 source has stated; verification tier (verified / reported / inferred) is shown per row. See every chip on record for the full catalog or the NVIDIA record.