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// NVIDIA Nemotron · Text LLM

NVIDIA-Nemotron-Labs-Dory1.0-4B-BF16: VRAM & local deployment

3.98B parameters. About 3.6 GB at 4-bit and 9.7 GB at BF16 with one 8K-token request.

released 2026-10-16licence: Commercial OKmemory figures are estimates

01Specs

PublisherNVIDIA · nvidia
Family / seriesNVIDIA Nemotron · NVIDIA-Nemotron-Labs-Dory1.0
TypeText LLM (text-generation)
Parameters3.98B Source: counted from official safetensors weights
Context length256K tokens (262,144)max_position_embeddings in config.json
Architecture72 layers (9 full-attention) · 27 sliding-window layers (1024) · GQA
Released weightsBF16 · 8.0 GBdownload
LicenceOpenMDW-1.1 · Commercial OKPermissive licence (Apache-2.0 / MIT / CC-BY / OpenMDW): commercial use allowed.
Released2026-10-16 (Hugging Face repo created)

02How much VRAM it needs (estimate)

Total = weights + 10% + 0.5GB overhead + KV cache for one request (FP16 KV). More concurrent users multiply the KV column.

PrecisionWeightsTotal @ 8KTotal @ 32KTotal @ 128KSmallest GPUMac
BF16 / FP16 (original)8.0 GB 9.7 GB10.6 GB14.2 GB 12GB GPUMac 24GB
FP8 / INT8 / Q8_04.2 GB 5.6 GB6.5 GB10.1 GB 8GB GPUMac 16GB
4-bit (Q4_K_M / AWQ / GPTQ-Int4)2.4 GB 3.6 GB4.5 GB8.1 GB 8GB GPUMac 16GB

KV cache per request: 8K 0.4 GB · 32K 1.3 GB · 128K 5.0 GB

Bits per weight: BF16 16, FP8 8.5, 4-bit 4.85. “Fits” = total ≤ 90% of memory; Mac GPU can use ~2/3 of unified memory (≤36GB) or ~3/4 (larger). For MoE, all experts must be in memory, so size by total parameters. Method →

03How to run it

Only runtimes the publisher or the runtime’s official library names for this model.

Which inference engine to choose →

04Official repositories & quantised builds

4 official repo(s) from nvidia.

05Other NVIDIA Nemotron models

All 62 →
ModelParams4-bit totalReleased
Nemotron-3.5-Rerank-8B-BF168.38B6.1 GB2026-10-15
NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16124.5B / 12B83.5 GB2026-10-12
NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF1674.9B / 9B50.4 GB2026-10-09
Nemotron-3.5-Embed-1B-BF161.55B1.5 GB2026-10-07
Nemotron-3.5-Embed-8B-BF168.38B6.1 GB2026-10-07
Nemotron-3.5-Parse631M1.1 GB2026-09-03
Nemotron-3-Labs-Ultra-Math-RL550B / 55B367 GB2026-09-02
NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF1631.6B / 3B21.6 GB2026-08-01

06Sources

Data checked 2026-10-16. Parameters, context and licence are copied from the official repository; memory figures are our estimates.

Data updated: Self-host open models(UTC+8)