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CHIP RESULT, LAST TESTED 8 OCTOBER 2026

NVIDIA H200

Across 600 compute runs, every output element stayed inside its proven error bound and every repeat matched the first run bit for bit. All 29,863,444,480 memory words read back correctly. The self-tests caught 90 of the 90 faults planted to prove the checks work.

Every number on this page is read from the result files listed at the bottom, written in the OCP Test and Validation format. New to this? Start with what a silent error is and how a chip is tested here.

2
probes run on this chip
600
compute runs checked element by element
29.9 billion
memory words written and read back
0
silent faults found
90 of 90
planted faults caught in self-tests
HOW CLOSE IT CAME

Error budget used

Floating-point answers are never exact, so each check allows a rounding error and proves how large it can honestly be. The red line is that proven limit. A bar shows the largest error this chip produced, as a share of the limit, across every run. Anything past the line would be a wrong answer.

BF16 matrix multiply
86.9% of bound
FP16 matrix multiply
50.9% of bound
FP32 matrix multiply
0.5% of bound

Checked exactly, where any difference at all fails: INT8 matrix multiply. Every one matched.

Bars close to the line at FP16 and BF16 are expected: there the limit is dominated by the single rounding of the output, so a correct chip has almost nothing to spare. A bar past the line is a failed run.

PROOF THE CHECKS WORK

Every planted fault was caught

A clean result is only worth something if the tester would have seen a fault. So next to every clean run, the self-test plants faults on purpose, including the patterns NVIDIA measured at gate level, and every one must be caught. How the self-test works.

Compute probe
60 of 60 caught
Memory probe
30 of 30 caught
Device memory swept
111.25 GiB of 139.81 GiB
PROBE 1

Compute probe

Matrix multiplies at several shapes and precisions. Every output element is checked against an exact or float64 reference under a proven rounding-error bound, and every run is compared bit for bit with the first run.

No silent faults.
600 runs across 12 steps. The self-test caught 60 of 60 planted faults.

Tool v0.2.0, PyTorch 2.8.0+cu128, 8 October 2026. Result file · Self-test file

Show all 12 steps from the result file
Step in the result fileSizeWorst error / boundVerdict
gemm_fp32_1024x1024x102450 runs0.005no-silent-errors
gemm_fp16_1024x1024x102450 runs0.509no-silent-errors
gemm_bf16_1024x1024x102450 runs0.869no-silent-errors
gemm_int8_1024x1024x102450 runsexactno-silent-errors
gemm_fp32_4096x4096x409650 runs0.001no-silent-errors
gemm_fp16_4096x4096x409650 runs0.115no-silent-errors
gemm_bf16_4096x4096x409650 runs0.504no-silent-errors
gemm_int8_4096x4096x409650 runsexactno-silent-errors
gemm_fp32_32x4096x1100850 runsunder 0.001no-silent-errors
gemm_fp16_32x4096x1100850 runs0.112no-silent-errors
gemm_bf16_32x4096x1100850 runs0.498no-silent-errors
gemm_int8_32x4096x1100850 runsexactno-silent-errors
PROBE 2

Memory probe

Most of the device memory written with six patterns, left to dwell, and read back word by word.

No silent faults.
29,863,444,480 memory words read back. The self-test caught 30 of 30 planted faults.

Tool v0.1.0, 8 October 2026. Result file · Self-test file

Show all 1 steps from the result file
Step in the result fileSizeWorst error / boundVerdict
memory_sweep_pass1111.25 GiBno-memory-errors
EVIDENCE

Setup and files

The chip

Name, as the driver reports it
NVIDIA H200
Device memory
139.81 GiB

The software

PyTorch
2.8.0+cu128
Probe versions
Compute probe v0.2.0, Memory probe v0.1.0

The test

Dates tested
8 October 2026
Result files
4 files in the OCP Test and Validation format

Result files

READ BEFORE RELYING ON IT

What this result shows

These numbers describe one unit of this chip, tested on the dates above. A clean result means no silent error showed up in these runs under these checks. It cannot rule out a fault that appears under other workloads, temperatures or ages, and another unit of the same model can behave differently. What a PASS means explains the limits in full.

TAKE PART

Run it on your chip

The same tests on your own hardware, in one command. Every result file it writes can be published here as a new row.

pip install ai-chip-integrity
chip-integrity run --name nvidia-h200

Cite the tool as: Yasha Khandelwal, ai-chip-integrity, version 0.4.2, 2026, https://doi.org/10.5281/zenodo.23393790

ALL CHIPS

Other chips measured