NVIDIA H100 80GB: Specs & Local-AI Compatibility
The Hopper workhorse: 80GB HBM3 and very high bandwidth.
Specs
- Memory
- 80 GB
- Memory type
- HBM3
- Bandwidth
- 3,350 GB/s
- Approx FP16
- 990 TFLOPS
- Architecture
- Hopper
- Process
- TSMC 4N
- Power
- 700 W
- Launch
- 2022
Models this chip can run
Open models graded for a single NVIDIA H100 80GB, best fit first.
- Qwen2.5 72BQwen · ~72B · 128K ctx · 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 · 128K ctx · 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 · 128K ctx · 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 · 128K ctx · 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 · 32K ctx · Apache-2.0
Fits at Q8_0 (~50GB) with ~20.4GB headroom — about 1 concurrent instance.
Q8_0 · ~50GBRuns well - CodeLlama 34BCodeLlama · ~34B · 16K ctx · Llama Community License
Fits at FP16 (~68GB) with ~2.4GB headroom — about 1 concurrent instance.
FP16 · ~68GBRuns well - Qwen2.5 32BQwen · ~32B · 128K ctx · Apache-2.0
Fits at FP16 (~64GB) with ~6.4GB headroom — about 1 concurrent instance.
FP16 · ~64GBRuns well - Qwen3 32BQwen · ~32B · 128K ctx · Apache-2.0
Fits at FP16 (~64GB) with ~6.4GB headroom — about 1 concurrent instance.
FP16 · ~64GBRuns well
Devices built on this chip
Build a private AI Business OS on NVIDIA H100 80GB
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.
Explore the AI Business OS