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OP·Eruo Fredoline
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RUNLOCALAI · v38
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  2. Home
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  4. /NVIDIA H20 (96GB)
UNIT · NVIDIA · GPU
96 GB VRAMworkstation·Reviewed June 2026

NVIDIA H20 (96GB)

NVDA · HARDWARE
NVIDIA H20 (96GB)

No editorial image yet — generic vendor mark shown. Credentials in spec table below.

The China-market Hopper SKU tuned for inference: 96GB HBM3 (more than the standard H100's 80GB), 4.0 TB/s, 400W, with ~41% fewer cores than a full H100. Export-compliant and highly relevant where H100/H200 are restricted.

Released 2024·4000 GB/s memory bandwidth
RUNLOCALAI SCORE
See full leaderboard →
697/ 1000
BB-tier
Estimated
Throughput
500/ 500
VRAM-fit
200/ 200
Ecosystem
200/ 200
Efficiency
96/ 100

Sub-scores sum to 996 / 1000. Headline = 996 × 0.70 (Estimated-confidence discount) = 697. This is an algorithmic performance-tier score — distinct from, and often lower than, the editorial “Our verdict” below, which weighs value and real-world fit (especially for hardware we haven’t measured yet). How scoring works →

Extrapolated from 4000 GB/s bandwidth — 480.0 tok/s estimated. No measured benchmarks yet.

WORKLOAD FIT
Try other hardware →

Plain-English: Runs 70B comfortably — snappy enough for a coding agent; vision models supported.

7B chat✓
Comfortable
14B chat✓
Comfortable
32B chat✓
Comfortable
70B chat✓
Comfortable
Coding agent✓
Comfortable
Vision (≤8B VLM)✓
Comfortable
Long context (32K)✓
Comfortable
✓Comfortable — fits with headroom
~Tight — works, no slack
△Marginal — needs aggressive quant
✗Doesn't fit usefully

Verdicts extrapolated from catalog VRAM + bandwidth + ecosystem flags. Hover any chip for the rationale. Want measured numbers? Submit your own run with runlocalai-bench --submit.

BLK · VERDICT

Our verdict

OP · Eruo Fredoline|VERIFIED JUN 18, 2026
7.4/10

What it is

The H20 is NVIDIA's export-compliant Hopper part for the Chinese market — deliberately tuned for inference rather than training. It pairs cut-down compute (~41% fewer cores than a full H100) with an unusually large 96GB of HBM3 at 4.0 TB/s, which actually exceeds the standard H100's 80GB. At 400W it runs 30B FP16 or 70B quantized comfortably.

Relevance to local AI

For local/on-prem AI buyers in China — where H100/H200 are restricted — the H20 is often the most capable CUDA card legally available, and its 96GB makes it a genuinely strong inference GPU despite the compute cuts (inference is more memory- than compute-bound). The high VRAM-to-compute ratio is well-matched to serving, less so to training. Outside China it's largely irrelevant given access to full Hopper/Blackwell parts.

Bottom line

A niche-but-real entry: the export-compliant 96GB Hopper inference card that matters specifically to China-market local-AI deployments. Included for completeness; not relevant to buyers with access to standard H100/H200.

BLK · OVERVIEW

Overview

The China-market Hopper SKU tuned for inference: 96GB HBM3 (more than the standard H100's 80GB), 4.0 TB/s, 400W, with ~41% fewer cores than a full H100. Export-compliant and highly relevant where H100/H200 are restricted.

Retailers we'd check:Amazon

Search-fallback link — editorial hasn't yet curated a retailer URL for this card.

Some links above are affiliate links. We may earn a commission at no extra cost to you. How we make money.

BLK · SPECS

Specs

VRAM96 GB
Power draw (peak)400 W
Released2024
Backends
CUDA

Models that fit

Open-weight models small enough to run on NVIDIA H20 (96GB) with usable context.

all-MiniLM-L6-v2
0.022B · other
FLUX.1 [dev]
12B · other
Qwen 3 0.6B
0.6B · qwen
BGE Large EN v1.5
0.335B · other
Nomic Embed Text v1.5
0.137B · other
Kokoro 82M
0.082B · other
Llama 3.1 8B Instruct
8B · llama
Qwen 3 30B-A3B
30B · qwen

Frequently asked

What models can NVIDIA H20 (96GB) run?

With 96GB VRAM, the NVIDIA H20 (96GB) runs 70B models in 4-bit quantization, plus everything smaller. See the model list below for tested combinations.

Does NVIDIA H20 (96GB) support CUDA?

Yes — NVIDIA H20 (96GB) is an NVIDIA card with full CUDA support, the most mature local-AI backend. llama.cpp, Ollama, vLLM, and ExLlamaV2 all run natively.

Where next?

Buyer guides
  • Best GPU for local AI →
  • Best laptop for local AI →
  • Best Mac for local AI →
  • Best used GPU for local AI →
Troubleshooting
  • CUDA out of memory →
  • Ollama running slowly →
  • ROCm not detected →
  • Model keeps crashing →

Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.

Compare alternatives

Hardware worth comparing

The closest alternatives by price, memory bandwidth, and form factor, plus a step up and down — so you can frame the buying decision against real options.

Closest matches
Similar price, bandwidth & form factor
  • Intel Gaudi 3
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  • Intel Gaudi 2
    intel · 96 GB VRAM
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  • AMD Instinct MI300A (APU)
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  • AMD Instinct MI250X
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  • AMD Instinct MI300X
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  • NVIDIA H100 SXM
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Step up
More capable — more memory or a higher tier
  • Intel Gaudi 3
    intel · 128 GB VRAM
    8.2/10
  • AMD Instinct MI300A (APU)
    amd · 128 GB VRAM
    10.0/10
  • NVIDIA H100 NVL
    nvidia · 188 GB VRAM
    10.0/10
Step down
Lighter — cheaper or more constrained
  • AMD Instinct MI210
    amd · 64 GB VRAM
    9.8/10
  • Intel Arc Pro B60 24GB
    intel · 24 GB VRAM
    7.6/10
  • AMD Radeon RX 7900 XTX
    amd · 24 GB VRAM
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