Dataset

GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)

Fragments of about one million tokens per genome: 5,000 bp for the 100M and 500M models and 50,000 bp for the 4B model.

Evaluation results

6 evaluations · 21 results. Different protocols are not a single leaderboard.

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: GenomeOcean-100M, BF16, PyTorch embedding extraction (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	0.3608 ± 0.0619 Adjusted rand index (DBSCAN clustering of embeddings against GTDB species labels) unitless · higher Uncertainty: SD 0.0619 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-100M BF16 embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '100M', Precision 'BF16', column 'DBSCAN ARI'
Configuration: GenomeOcean-100M, BF16, PyTorch embedding extraction (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	21.1 Peak memory (Embedding extraction; peak GPU memory allocated) gigabyte · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-100M BF16 embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '100M', Precision 'BF16', column 'Peak VRAM (GB)'
Configuration: GenomeOcean-100M, BF16, PyTorch embedding extraction (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	613,371 ± 22,439 Inference throughput (Embedding extraction; input tokens per second) sample-per-second · higher Uncertainty: SD 22439 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-100M BF16 embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '100M', Precision 'BF16', column 'Throughput (tok/s)'
Configuration: GenomeOcean-100M, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	0.3533 ± 0.0588 Adjusted rand index (DBSCAN clustering of embeddings against GTDB species labels) unitless · higher Uncertainty: SD 0.0588 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-100M FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '100M', Precision 'FP8 (E4M3)', column 'DBSCAN ARI'
Configuration: GenomeOcean-100M, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	21 Peak memory (Embedding extraction; peak GPU memory allocated) gigabyte · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-100M FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '100M', Precision 'FP8 (E4M3)', column 'Peak VRAM (GB)'
Configuration: GenomeOcean-100M, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	460,733 ± 1,694 Inference throughput (Embedding extraction; input tokens per second) sample-per-second · higher Uncertainty: SD 1694 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-100M FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '100M', Precision 'FP8 (E4M3)', column 'Throughput (tok/s)'
Configuration: GenomeOcean-100M, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	−24.9% Throughput change (Embedding extraction; relative to the BF16 baseline of the same model scale) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-100M FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '100M', Precision 'FP8 (E4M3)', column 'Change'
Configuration: GenomeOcean-4B, BF16, PyTorch embedding extraction (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	0.5278 ± 0.0672 Adjusted rand index (DBSCAN clustering of embeddings against GTDB species labels) unitless · higher Uncertainty: SD 0.0672 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-4B BF16 embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '4B', Precision 'BF16', column 'DBSCAN ARI'
Configuration: GenomeOcean-4B, BF16, PyTorch embedding extraction (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	72.1 Peak memory (Embedding extraction; peak GPU memory allocated) gigabyte · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-4B BF16 embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '4B', Precision 'BF16', column 'Peak VRAM (GB)'
Configuration: GenomeOcean-4B, BF16, PyTorch embedding extraction (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	21,386 ± 126 Inference throughput (Embedding extraction; input tokens per second) sample-per-second · higher Uncertainty: SD 126 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-4B BF16 embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '4B', Precision 'BF16', column 'Throughput (tok/s)'
Configuration: GenomeOcean-4B, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	0.5280 ± 0.0653 Adjusted rand index (DBSCAN clustering of embeddings against GTDB species labels) unitless · higher Uncertainty: SD 0.0653 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-4B FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '4B', Precision 'FP8 (E4M3)', column 'DBSCAN ARI'
Configuration: GenomeOcean-4B, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	67.9 Peak memory (Embedding extraction; peak GPU memory allocated) gigabyte · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-4B FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '4B', Precision 'FP8 (E4M3)', column 'Peak VRAM (GB)'
Configuration: GenomeOcean-4B, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	22,401 ± 204 Inference throughput (Embedding extraction; input tokens per second) sample-per-second · higher Uncertainty: SD 204 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-4B FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '4B', Precision 'FP8 (E4M3)', column 'Throughput (tok/s)'
Configuration: GenomeOcean-4B, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	4.7% Throughput change (Embedding extraction; relative to the BF16 baseline of the same model scale) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-4B FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '4B', Precision 'FP8 (E4M3)', column 'Change'
Configuration: GenomeOcean-500M, BF16, PyTorch embedding extraction (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	0.3345 ± 0.0479 Adjusted rand index (DBSCAN clustering of embeddings against GTDB species labels) unitless · higher Uncertainty: SD 0.0479 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-500M BF16 embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '500M', Precision 'BF16', column 'DBSCAN ARI'
Configuration: GenomeOcean-500M, BF16, PyTorch embedding extraction (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	47.2 Peak memory (Embedding extraction; peak GPU memory allocated) gigabyte · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-500M BF16 embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '500M', Precision 'BF16', column 'Peak VRAM (GB)'
Configuration: GenomeOcean-500M, BF16, PyTorch embedding extraction (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	230,523 ± 651 Inference throughput (Embedding extraction; input tokens per second) sample-per-second · higher Uncertainty: SD 651 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-500M BF16 embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '500M', Precision 'BF16', column 'Throughput (tok/s)'
Configuration: GenomeOcean-500M, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	0.3273 ± 0.0508 Adjusted rand index (DBSCAN clustering of embeddings against GTDB species labels) unitless · higher Uncertainty: SD 0.0508 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-500M FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '500M', Precision 'FP8 (E4M3)', column 'DBSCAN ARI'
Configuration: GenomeOcean-500M, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	46.7 Peak memory (Embedding extraction; peak GPU memory allocated) gigabyte · lower Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-500M FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '500M', Precision 'FP8 (E4M3)', column 'Peak VRAM (GB)'
Configuration: GenomeOcean-500M, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	204,973 ± 777 Inference throughput (Embedding extraction; input tokens per second) sample-per-second · higher Uncertainty: SD 777 Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-500M FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '500M', Precision 'FP8 (E4M3)', column 'Throughput (tok/s)'
Configuration: GenomeOcean-500M, FP8 (E4M3) static weights, PyTorch with FBGEMM (Yu et al. 2026)	Protocol: GenomeOcean embedding extraction throughput, peak VRAM and binning fidelity, BF16 versus FP8 weights (Yu et al. 2026 Table 3) Dataset: GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026)	−11.1% Throughput change (Embedding extraction; relative to the BF16 baseline of the same model scale) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source GenomeOcean-500M FP8 (E4M3) embedding extraction (Yu et al. 2026) model-execution-20261011-protocol-yu2026-genomeocean-embedding-fp8 Aggregation: Not reported FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 3, row Model '500M', Precision 'FP8 (E4M3)', column 'Change'

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Claims, original sources and review scope · Release 2026-10-22-1b7cf027e4f6
Property and statement	Original source and location	Review and provenance
Population 20 genomes per trial sampled from a pool of 50 GTDB bacterial genomes; a representative 20-genome sample is listed in Table 5 Context-only references	FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean Original source ↗ Section 2.5 'Metagenomic binning (Protocol A)'; Section 2.7; Table 5 Version: bioRxiv preprint version 1, posted 2026-08-14 (PDF footer); bioRxiv API date 2026-08-18 Retrieved: 2026-10-11T21:42:49Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.population` Source artifact SHA-256: `ca54817d1f1a308f09bd3022e56cf6f8b86a875b110da0a38fe31236e39ca076` Hash scope: bioRxiv stamps each PDF download, so artifact_sha256 describes one retrieval (a second download differed in 40 bytes). The pdftotext -layout text layer (poppler) of both downloads has SHA-256 bec6e695ce46c4ebd6692e01a1a93167e212dffbb97b6558f1da88b1eb453501. Inspected artifact
Source location Section 2.5 'Metagenomic binning (Protocol A)'; Section 2.7; Table 5 Context-only references	FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean Original source ↗ Section 2.5 'Metagenomic binning (Protocol A)'; Section 2.7; Table 5 Version: bioRxiv preprint version 1, posted 2026-08-14 (PDF footer); bioRxiv API date 2026-08-18 Retrieved: 2026-10-11T21:42:49Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.source_locator` Source artifact SHA-256: `ca54817d1f1a308f09bd3022e56cf6f8b86a875b110da0a38fe31236e39ca076` Hash scope: bioRxiv stamps each PDF download, so artifact_sha256 describes one retrieval (a second download differed in 40 bytes). The pdftotext -layout text layer (poppler) of both downloads has SHA-256 bec6e695ce46c4ebd6692e01a1a93167e212dffbb97b6558f1da88b1eb453501. Inspected artifact
Split Five trials with random seeds 42-46 Context-only references	FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean Original source ↗ Section 2.5 'Metagenomic binning (Protocol A)'; Section 2.7; Table 5 Version: bioRxiv preprint version 1, posted 2026-08-14 (PDF footer); bioRxiv API date 2026-08-18 Retrieved: 2026-10-11T21:42:49Z	not individually reviewed No individual claim review recorded Audit details Field: `attributes.split` Source artifact SHA-256: `ca54817d1f1a308f09bd3022e56cf6f8b86a875b110da0a38fe31236e39ca076` Hash scope: bioRxiv stamps each PDF download, so artifact_sha256 describes one retrieval (a second download differed in 40 bytes). The pdftotext -layout text layer (poppler) of both downloads has SHA-256 bec6e695ce46c4ebd6692e01a1a93167e212dffbb97b6558f1da88b1eb453501. Inspected artifact
Description Fragments of about one million tokens per genome: 5,000 bp for the 100M and 500M models and 50,000 bp for the 4B model. Context-only references	FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean Original source ↗ Section 2.5 'Metagenomic binning (Protocol A)'; Section 2.7; Table 5 Version: bioRxiv preprint version 1, posted 2026-08-14 (PDF footer); bioRxiv API date 2026-08-18 Retrieved: 2026-10-11T21:42:49Z	not individually reviewed No individual claim review recorded Audit details Field: `description` Source artifact SHA-256: `ca54817d1f1a308f09bd3022e56cf6f8b86a875b110da0a38fe31236e39ca076` Hash scope: bioRxiv stamps each PDF download, so artifact_sha256 describes one retrieval (a second download differed in 40 bytes). The pdftotext -layout text layer (poppler) of both downloads has SHA-256 bec6e695ce46c4ebd6692e01a1a93167e212dffbb97b6558f1da88b1eb453501. Inspected artifact
Name GTDB genome fragments for metagenomic binning, 20 of a pre-sampled pool of 50 bacterial genomes per trial (Yu et al. 2026) Context-only references	FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean Original source ↗ Section 2.5 'Metagenomic binning (Protocol A)'; Section 2.7; Table 5 Version: bioRxiv preprint version 1, posted 2026-08-14 (PDF footer); bioRxiv API date 2026-08-18 Retrieved: 2026-10-11T21:42:49Z	not individually reviewed No individual claim review recorded Audit details Field: `name` Source artifact SHA-256: `ca54817d1f1a308f09bd3022e56cf6f8b86a875b110da0a38fe31236e39ca076` Hash scope: bioRxiv stamps each PDF download, so artifact_sha256 describes one retrieval (a second download differed in 40 bytes). The pdftotext -layout text layer (poppler) of both downloads has SHA-256 bec6e695ce46c4ebd6692e01a1a93167e212dffbb97b6558f1da88b1eb453501. Inspected artifact

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Release 2026-10-22-1b7cf027e4f6 · Record review: source checked

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FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Original source · bioRxiv preprint version 1, posted 2026-08-14 (PDF footer); bioRxiv API date 2026-08-18

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Technical metadata and extraction receipts

Stable ID: model-execution-20261011-data-yu2026-gtdb-binning

areas: dna-genomes
contexts: research
population: 20 genomes per trial sampled from a pool of 50 GTDB bacterial genomes; a representative 20-genome sample is listed in Table 5
split: Five trials with random seeds 42-46
source locator: Section 2.5 'Metagenomic binning (Protocol A)'; Section 2.7; Table 5
missing metadata: version: reason: unreported; note: GTDB release not stated

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