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NVIDIA · AI AppliancesAnnounced

NVIDIA DGX Spark (GB10 class): Local AI & Business Fit

A desktop AI appliance built on the GB10 Grace Blackwell superchip with ~128GB unified memory — a personal AI developer box.

Here’s what the NVIDIA DGX Spark (GB10 class) means for a business that wants to run private AI on hardware it controls: which open LLMs fit, which agents it can power, the AI Business OS tier it suits, and whether to run local, cloud or hybrid.

66/100· Strong·~

Specs at a glance

Memory
128 GB unified
Memory type
LPDDR5X (unified, Grace Blackwell)
Bandwidth
273 GB/s
Approx FP16
to verify
Architecture
NVIDIA Grace Blackwell GB10
Process
to verify
Power
to verify
Launch year
2025

Specs are placeholder figures. PLACEHOLDER. Figures based on early announcements; bandwidth and compute to verify. Positioned as a turnkey local AI development appliance rather than a general PC.

AI compatibility scores

Transparent 0–100 heuristics blending usable memory, bandwidth and compute — relative guidance, not benchmarks.

Local AI (overall)66/100
Document RAG68/100
Coding agents66/100
Multi-agent51/100
Business automation61/100

~ Some specs are unverified, so these scores are provisional.

Compatible LLMs

Open-weight chat, coding and reasoning models from our catalog graded for the NVIDIA DGX Spark (GB10 class), best fit first.

  • CodeLlama 13B
    CodeLlama · 13B · Llama Community License

    Fits at FP16 (~26GB) with ~63.6GB headroom — about 3 concurrent instances.

    FP16 · ~26GBRuns well
  • Gemma 3 12B
    Gemma 3 · 12B · Gemma Terms of Use

    Fits at FP16 (~24GB) with ~65.6GB headroom — about 3 concurrent instances.

    FP16 · ~24GBRuns well
  • Mistral Nemo 12B
    Mistral · 12B · Apache-2.0

    Fits at FP16 (~24GB) with ~65.6GB headroom — about 3 concurrent instances.

    FP16 · ~24GBRuns well
  • Gemma 2 9B
    Gemma · 9B · Gemma Terms of Use

    Fits at FP16 (~19GB) with ~70.6GB headroom — about 4 concurrent instances.

    FP16 · ~19GBRuns well
  • Llama 3.1 8B
    Llama · 8B · Llama Community License

    Fits at FP16 (~17GB) with ~72.6GB headroom — about 5 concurrent instances.

    FP16 · ~17GBRuns well
  • Qwen3 8B
    Qwen · 8B · Apache-2.0

    Fits at FP16 (~17GB) with ~72.6GB headroom — about 5 concurrent instances.

    FP16 · ~17GBRuns well
  • Granite 3 8B
    Granite · 8B · Apache-2.0

    Fits at FP16 (~17GB) with ~72.6GB headroom — about 5 concurrent instances.

    FP16 · ~17GBRuns well
  • DeepSeek-R1 Distill 8B
    DeepSeek · 8B · MIT

    Fits at FP16 (~17GB) with ~72.6GB headroom — about 5 concurrent instances.

    FP16 · ~17GBRuns well

See the full model catalog →

Best models by business workload

Best for coding agents

Code completion, review and refactoring on private source.

Best for RAG / search

Answering over your documents with citations.

Best for business automation

Document extraction and back-office workflows.

Good for a private AI Business OS?

✓

Yes — this is a viable private AI Business OS host for a department-scale deployment, running models like CodeLlama 13B on hardware you control.

Headline model it can host: CodeLlama 13B.

Where it falls short

  • ▸Unified-memory bandwidth trails discrete HBM GPUs, so large models run but generate tokens more slowly.
  • ▸Specifications are provisional (placeholder/announced) and must be verified before purchase.

Business agents that make sense

How this machine fits the core AI Business OS agent archetypes:

  • Customer Support Agent

    Answers customers over your docs, drafts replies, triages tickets.

    Strong fit
  • Document / RAG Agent

    Reads contracts, reports and wikis and answers with citations.

    Strong fit
  • Legal Evidence Agent (DocMatch-style)

    Searches case files and exhibits to surface and link evidence.

    Strong fit
  • Hotel / Hospitality Agent

    Handles guest messaging, bookings and front-desk automation.

    Strong fit
  • Accounting / Odoo Agent

    Extracts invoices, reconciles data and drives ERP workflows.

    Capable
  • Coding / Product Engineering Agent

    Local code completion, review and refactoring on private source.

    Strong fit
  • Founder Ops / Business Command Center

    A fleet of cooperating agents running the whole business privately.

    Cloud-assist

“Cloud-assist” means run it locally for light loads and burst to the cloud for heavier jobs. See business use cases for how each agent maps to hardware.

Frequently asked questions

Is the NVIDIA DGX Spark (GB10 class) good for running local AI?+

It scores 66/100 on our Local AI Score (Strong tier), based on its 128GB of memory and available bandwidth/compute. Some specs are unverified, so treat the score as provisional. That makes it suited to the Business AI Business OS tier.

Which LLMs can the NVIDIA DGX Spark (GB10 class) run?+

Comfortably: Qwen2.5 72B (Q8_0), Llama 3.1 70B (Q8_0), Llama 3.3 70B (Q8_0). Larger models may run with heavier quantization or by splitting across devices.

Should I run AI locally or in the cloud on the NVIDIA DGX Spark (GB10 class)?+

Local-first is recommended. Enough capability to host real agents locally for privacy and predictable cost; use cloud only to burst beyond peak demand.

Can I turn the NVIDIA DGX Spark (GB10 class) into a private AI Business OS?+

Yes. AI Business OS can run on this machine at the Business tier, giving you private agents on your own hardware. See the call-to-action above to get started.

Turn the NVIDIA DGX Spark (GB10 class) into a private AI Business OS

Run your own AI agents on hardware you control — private by design, no per-seat data leaving your premises. BrainOutput helps you pick the right machine and turn it into a working AI Business OS.

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