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AI chip · NVIDIA

NVIDIA Rubin (R100)

Announced at GTC 2025 (ships H2 2026): the Blackwell successor. Dual-die 3nm, 336B transistors, 288 GB HBM4, ~50 PFLOPS NVFP4. Pairs with the Vera CPU as the Vera Rubin platform.

Market position

Announced at GTC 2025 (ships H2 2026): the Blackwell successor. Dual-die 3nm, 336B transistors, 288 GB HBM4, ~50 PFLOPS NVFP4 (about 2.5x B200). Pairs with the Vera CPU as the Vera Rubin platform (VR200 NVL144 rack). Specs provisional pending launch.

What fits in 288 GB

Which open-source LLMs run on one NVIDIA Rubin (R100), by precision. Weights only: add roughly 15% headroom for real serving. If a model does not fit at FP16, try INT8 or INT4 (smaller quality trade-off than most people expect).

ModelParamsFP16INT8INT4
Llama 3.1 8B
dense
8 B16 GB ✓8 GB ✓4 GB ✓
Llama 3.1 70B
dense
70 B140 GB ✓70 GB ✓35 GB ✓
Llama 3.1 405B
dense
405 B810 GB ✗405 GB ✗203 GB ✓
Llama 3.3 70B
dense
70 B140 GB ✓70 GB ✓35 GB ✓
DeepSeek V3
MoE (671B total, 37B active per token)
671 B1342 GB ✗671 GB ✗336 GB ✗
DeepSeek R1
MoE (671B total, 37B active per token)
671 B1342 GB ✗671 GB ✗336 GB ✗
Qwen 2.5 7B
dense
7 B14 GB ✓7 GB ✓4 GB ✓
Qwen 2.5 72B
dense
72 B144 GB ✓72 GB ✓36 GB ✓
Mixtral 8x7B
MoE (46.7B total, 12.9B active per token)
46.7 B93 GB ✓47 GB ✓23 GB ✓
Mixtral 8x22B
MoE (141B total, 39B active per token)
141 B282 GB ✓141 GB ✓71 GB ✓
Gemma 2 27B
dense
27 B54 GB ✓27 GB ✓14 GB ✓
Command R+
dense
104 B208 GB ✓104 GB ✓52 GB ✓
Kimi K2
MoE (1T total, 32B active per token)
1000 B2000 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

How much does NVIDIA Rubin (R100) cost?

NVIDIA Rubin (R100) doesn't have a public launch list price. Vendors like this one usually price through direct sales rather than a public sheet. See list price per TFLOP for chips that do publish.

How much memory does NVIDIA Rubin (R100) have?

288 GB of HBM4. Straight from the vendor datasheet. See chips with the most memory for context.

Which open-source LLMs fit on one NVIDIA Rubin (R100)?

Of 13 open-source LLMs we track, 9 fit at FP16, 9 at INT8, and 10 at INT4 (for example Llama 3.1 8B, Llama 3.1 70B and Llama 3.1 405B). Full table above with each model's memory need.

See every answer we publish →

Key facts

Class
Compute SoC (AI accelerator)
Designer
NVIDIA
Safety-critical?
No (data-center inference / training)
Record as of
2026-09-27
Specifications (7 fields, click to expand)

Straight from the vendor datasheet. Dense throughput shown first; sparse (2:4) numbers in parentheses where the vendor publishes them. Full datasheet linked below.

Process node
TSMC 3nm (N3)
Transistors
336 B
Memory
288 GB HBM4
FP4 (dense)
50,000 TFLOPS
Form factor
SXM
Announced
2025-03-18
Released
2026-10-01

Source: vendor datasheet

Generation

Foundry & process

Process node
TSMC 3nm (N3)
Transistors
336 B

Sources

Adoption rows appear as we confirm each chip-in-robot pairing from a public source. See every chip we track for the full catalog or the NVIDIA page.