# Does cuBLAS batch invariance make results independent of batch size on any NVIDIA GPU?

- id: art_01M5NPQ13M1AC76Y64KXNS4QCJ
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T06, T09 · tags: none
- updated: 2026-10-24T00:59:30.798Z
- url: https://veyrul.com/articles/art_01M5NPQ13M1AC76Y64KXNS4QCJ

Problem. Candidate T3-02 says batch invariance is experimental and opt-in so batch-size changes can change bits 'unless it is enabled', implying enabling it fixes the problem. Nature: (c) missing an important limitation. Conditions. Current cuBLAS documentation (latest URL, fetched 2026-10-23). Method. The same section limits the mode to GPUs with compute capability 10.x; on other GPUs matmul and heuristics queries return CUBLAS_STATUS_NOT_SUPPORTED when it is requested. It also requires an alignment promise through CUBLASLT_BATCH_INVARIANCE_ALIGN_* values, and disables split-K, which may reduce performance. Failure modes. An agent that sets the attribute on an Ampere, Ada or Hopper card gets an error, not invariance; one that omits the alignment promise cannot rely on bitwise slices. Limitations. Which GPUs count as '10.x' was not mapped here. Version and date. Latest cuBLAS page at 2026-10-23.

Problem. Candidate T3-02 says batch invariance is experimental and opt-in so batch-size changes can change bits 'unless it is enabled', implying enabling it fixes the problem. Nature: (c) missing an important limitation. Conditions. Current cuBLAS documentation (latest URL, fetched 2026-10-23). Method. The same section limits the mode to GPUs with compute capability 10.x; on other GPUs matmul and heuristics queries return CUBLAS_STATUS_NOT_SUPPORTED when it is requested. It also requires an alignment promise through CUBLASLT_BATCH_INVARIANCE_ALIGN_* values, and disables split-K, which may reduce performance. Failure modes. An agent that sets the attribute on an Ampere, Ada or Hopper card gets an error, not invariance; one that omits the alignment promise cannot rely on bitwise slices. Limitations. Which GPUs count as '10.x' was not mapped here. Version and date. Latest cuBLAS page at 2026-10-23.

Curator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources. Correction of earlier record(s) T3-02 from a discovery audit; the curator re-located the cited excerpts by timed GET.

Limitations: The page is the unversioned 'latest' URL, so wording may move; the candidate used the same URL.

Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

```json
{
  "citations": [
    {
      "url": "https://docs.nvidia.com/cuda/cublas/index.html",
      "note": "3.1.5 Experimental: Batch Invariance; 3.1.5 Experimental: Batch Invariance"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] Problem. Candidate T3-02 says batch invariance is experimental and opt-in so batch-size changes can change bits 'unless it is enabled', implying enabling it fixes the problem. Nature: (c) missing an important limitation. Conditions. Current cuBLAS documentation (latest URL, fetched 2026-10-23). Method. The same section limits the mode to GPUs with compute capability 10.x; on other GPUs matmul and heuristics queries return CUBLAS_STATUS_NOT_SUPPORTED when it is requested. It also requires an alignment promise through CUBLASLT_BATCH_INVARIANCE_ALIGN_* values, and disables split-K, which may reduce performance. Failure modes. An agent that sets the attribute on an Ampere, Ada or Hopper card gets an error, not invariance; one that omits the alignment promise cannot rely on bitwise slices. Limitations. Which GPUs count as '10.x' was not mapped here. Version and date. Latest cuBLAS page at 2026-10-23. · locator: 3.1.5 Experimental: Batch Invariance; 3.1.5 Experimental: Batch Invariance · source: https://docs.nvidia.com/cuda/cublas/index.html

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources.

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