Best 80GB GPU for Local AI: A100 vs H100

Eight-device workload example: Kimi K2.5 on 8×H100 80GB shows why eight individually suitable GPUs can still leave too little aggregate runtime margin.

Short answer: choose A100 80GB when an older Ampere accelerator and a correctly qualified used or existing server provide the better complete-system path. Choose H100 80GB when Hopper software support, newer kernels, MIG or the qualified H100 platform solves a measured requirement. Both have the same nominal 80GB capacity, so H100 does not make a larger model fit merely by changing generations. If the complete workload is too tight for 80GB, compare H100 NVL 94GB, a 96GB workstation GPU or a larger tier.

Choose by constraint

A100 80GB: value or availability path when Ampere support and the exact PCIe/SXM system are already qualified.
H100 80GB: Hopper path when compatible kernels, MIG, platform capabilities or measured performance justify the full deployment cost.
H100 NVL 94GB or 96GB: exit the equal-capacity comparison when 80GB lacks complete-workload headroom.

A100 80GB vs H100 80GB at a glance

Decision factor	A100 80GB	H100 80GB	Why it matters
Architecture / compute capability	Ampere / 8.0	Hopper / 9.0	Drivers, frameworks, kernels and compiled extensions must support the exact target
Nominal memory	80GB HBM2e	80GB HBM3	Equal nominal capacity; generation alone does not change file fit
PCIe published bandwidth	1,935GB/s	2TB/s in NVIDIA’s original H100 datasheet	Peak bandwidth is not a tokens-per-second result
SXM published bandwidth	2,039GB/s	3.35TB/s on NVIDIA’s current H100 product page	PCIe and SXM are different products and platforms
PCIe power	300W	350W maximum; some configurations operate lower	Accelerator power is not whole-system wall power
Cooling / platform	Passive PCIe or SXM HGX/DGX module	Passive PCIe or SXM HGX/DGX module	Neither is an ordinary actively cooled desktop card

Manufacturer peak specifications, not HighVRAM benchmarks. Match the exact SKU, document revision, power mode and host platform.

Equal 80GB capacity means equal file gates

Complete artifact	Files	Nominal 80GB margin	Decision
Qwen3.5-35B-A3B official BF16	71.904GB	8.096GB	Bounded by files; validate cache, workspaces and concurrency
Qwen3.5-122B-A10B community Q4_K_M plus F16 projector	77.446GB	2.554GB	Unsafe runtime boundary on either 80GB GPU
Qwen3.5-122B-A10B official GPTQ-Int4	78.864GB	1.136GB	Unsafe runtime boundary on either 80GB GPU
Qwen3.5-122B-A10B official FP8	127.163GB	Does not fit	Requires a larger one-device tier or deliberate multi-device placement

Decimal file-size arithmetic only—not measured peak resident memory. Official and community artifacts remain separately labeled; the community multimodal total includes the listed projector.

The same 77.446GB or 78.864GB files leave the same nominal margin on A100 80GB and H100 80GB. Hopper may change which kernels are available and how fast a supported workload runs, but it does not create additional framebuffer. CUDA context, cache, runtime workspaces, allocator behavior, modality, batch and concurrency still need room.

When A100 80GB is the better path

Your exact runtime and kernels support compute capability 8.0.
The complete workload fits with measured per-device headroom.
A qualified PCIe or HGX/DGX Ampere system is already available or materially cheaper.
You have verified form factor, passive airflow, power, MIG state, exposed memory, health and return terms.

Used accelerator pricing can hide platform cost. A bare SXM module needs the matching baseboard, cooling, power and firmware. A passive PCIe card needs directed server airflow. Compare the complete tested system, not an isolated listing price.

When H100 80GB is the better path

Your software or quantization path specifically benefits from or requires Hopper-era support.
A controlled measurement shows a material workload improvement with the same model, format, runtime, context, concurrency and timing boundary.
The H100 platform’s MIG, NVLink/NVSwitch or support characteristics solve a documented deployment requirement.
The qualified-system cost, power and cooling remain justified after the accelerator price.

Do not turn sparse tensor peaks, memory bandwidth or generic AI TOPS into a local-LLM ranking. The benchmark database preserves source-specific definitions and currently contains a fixed 43 metric observations from seven sources; it does not establish a universal A100-versus-H100 winner.

When neither 80GB path is enough

Tight 122B 4-bit artifacts: H100 NVL 94GB or RTX PRO 6000 96GB provides more file headroom, but still requires complete-workload validation.
127GB-class FP8: move beyond 128GB nominal boundary cases toward a practical larger tier.
Multi-GPU: device capacities do not automatically pool. Record tensor, pipeline or expert placement and per-device peak memory.
Desktop workflow: compare an active workstation GPU or complete system rather than forcing passive accelerators into an unqualified host.

A reproducible A100-versus-H100 test

Record exact PCIe/SXM/NVL identity, capacity, power mode, MIG profile and host system.
Fix model repository, revision, quantization, runtime/version and kernel path.
Fix context, cache precision, modality, prompt/output profile, batch and concurrency.
Measure exposed memory and peak memory per device; disclose offload and placement.
Run warm-ups and repetitions with separate prompt processing, time to first token and decode timing.
Compare total deployment cost and operational constraints—not only accelerator price.

Continue the decision

Review A100 40GB/80GB variants · Review H100 PCIe/SXM/NVL variants · Compare A100 and H100 directly · Compare 48GB, 64GB, 80GB and 96GB · Inspect exact 122B boundaries · Calculate memory fit · Read source-specific results · Build a controlled benchmark record · Save private return criteria

Primary sources

Reviewed October 25, 2026. Manufacturer specifications describe different PCIe, SXM and NVL products and may change across document revisions. HighVRAM has not independently benchmarked every configuration. Capacity and peak specifications do not establish speed, reliability, output quality or value.

Applying the 80GB decision to GLM-4.7-Flash? The dedicated hardware guide shows the official 62.444GB BF16 file margin and the runtime evidence still required.