Cloud A100 80GB (profile): Local AI & Business Fit
A widely available, often cheaper rentable 80GB card — a practical default for fine-tuning and serving when H100 supply is tight.
Here’s what the Cloud A100 80GB (profile) 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.
Specs at a glance
- Memory
- 80 GB
- Memory type
- HBM2e
- Bandwidth
- 2,039 GB/s
- Approx FP16
- 312 TFLOPS
- Architecture
- Ampere
- Process
- TSMC 7nm
- Power
- to verify
- Launch year
- 2020
Specs are approximate figures. Generic profile; pricing varies and is frequently below H100. Still highly capable for most LLM workloads.
AI compatibility scores
Transparent 0–100 heuristics blending usable memory, bandwidth and compute — relative guidance, not benchmarks.
Compatible LLMs
Open-weight chat, coding and reasoning models from our catalog graded for the Cloud A100 80GB (profile), best fit first.
- Qwen2.5 72BQwen · 72B · Qwen License
Fits at Q4_K_M (~44GB) with ~26.4GB headroom — about 1 concurrent instance.
Q4_K_M · ~44GBRuns well - Llama 3.1 70BLlama · 70B · Llama Community License
Fits at Q4_K_M (~42GB) with ~28.4GB headroom — about 1 concurrent instance.
Q4_K_M · ~42GBRuns well - Llama 3.3 70BLlama · 70B · Llama Community License
Fits at Q4_K_M (~42GB) with ~28.4GB headroom — about 1 concurrent instance.
Q4_K_M · ~42GBRuns well - DeepSeek-R1 Distill Llama 70BDeepSeek · 70B · MIT
Fits at Q4_K_M (~42GB) with ~28.4GB headroom — about 1 concurrent instance.
Q4_K_M · ~42GBRuns well - Mixtral 8x7B (MoE)Mistral · 47B · Apache-2.0
Fits at Q8_0 (~50GB) with ~20.4GB headroom — about 1 concurrent instance.
Q8_0 · ~50GBRuns well - CodeLlama 34BCodeLlama · 34B · Llama Community License
Fits at FP16 (~68GB) with ~2.4GB headroom — about 1 concurrent instance.
FP16 · ~68GBRuns well - Qwen2.5 32BQwen · 32B · Apache-2.0
Fits at FP16 (~64GB) with ~6.4GB headroom — about 1 concurrent instance.
FP16 · ~64GBRuns well - Qwen3 32BQwen · 32B · Apache-2.0
Fits at FP16 (~64GB) with ~6.4GB headroom — about 1 concurrent instance.
FP16 · ~64GBRuns well
Best models by business workload
Best for coding agents
Code completion, review and refactoring on private source.
- Qwen2.5 72BRuns well
- Llama 3.3 70BRuns well
- CodeLlama 34BRuns well
Best for RAG / search
Answering over your documents with citations.
- Qwen2.5 72BRuns well
- Llama 3.1 70BRuns well
- Llama 3.3 70BRuns well
Best for business automation
Document extraction and back-office workflows.
- Llama 3.1 70BRuns well
- Gemma 2 27BRuns well
- Gemma 3 27BRuns well
Good for a private AI Business OS?
As a rentable cloud profile this hosts AI Business OS agents elastically — ideal for bursts and the largest models in a hybrid setup.
Headline model it can host: Qwen2.5 72B.
Where it falls short
- ▸Ongoing rental cost and data leaving your premises; less suited to always-on private workloads.
Business agents that make sense
How this machine fits the core AI Business OS agent archetypes:
- Strong fitCustomer Support Agent
Answers customers over your docs, drafts replies, triages tickets.
- Strong fitDocument / RAG Agent
Reads contracts, reports and wikis and answers with citations.
- Strong fitLegal Evidence Agent (DocMatch-style)
Searches case files and exhibits to surface and link evidence.
- Strong fitHotel / Hospitality Agent
Handles guest messaging, bookings and front-desk automation.
- Strong fitAccounting / Odoo Agent
Extracts invoices, reconciles data and drives ERP workflows.
- Strong fitCoding / Product Engineering Agent
Local code completion, review and refactoring on private source.
- CapableFounder Ops / Business Command Center
A fleet of cooperating agents running the whole business privately.
“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 Cloud A100 80GB (profile) good for running local AI?+
It scores 72/100 on our Local AI Score (Strong tier), based on its 80GB of memory and available bandwidth/compute. That makes it suited to the Business AI Business OS tier.
Which LLMs can the Cloud A100 80GB (profile) run?+
Comfortably: Qwen2.5 72B (Q4_K_M), Llama 3.1 70B (Q4_K_M), Llama 3.3 70B (Q4_K_M). Larger models may run with heavier quantization or by splitting across devices.
Should I run AI locally or in the cloud on the Cloud A100 80GB (profile)?+
Cloud-first is recommended. This is a rentable cloud profile — ideal for bursty or short-lived heavy workloads. Pair with on-prem hardware for steady private workloads (hybrid).
Can I turn the Cloud A100 80GB (profile) 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 Cloud A100 80GB (profile) 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.
Get startedRelated hardware
Cloud H100 80GB (profile)
A rentable H100 instance — top-tier inference and fine-tuning without capital expenditure, billed by the hour.
- Memory
- 80 GB
- Architecture
- Hopper
Cloud L40S 48GB (profile)
A cost-effective rentable 48GB card — a sweet spot for steady mid-scale inference without HBM-tier pricing.
- Memory
- 48 GB
- Architecture
- Ada Lovelace
Cloud H200 141GB (profile)
A rentable Hopper card with 141GB of fast HBM3e — headroom for very large models and long context without multi-GPU splitting.
- Memory
- 141 GB
- Architecture
- Hopper
Cloud B200 (Blackwell profile, to verify)
A next-gen Blackwell datacenter profile for frontier-scale training and serving — listed to anchor the top of the cloud tier.
- Memory
- 180 GB
- Architecture
- Blackwell