rewirebio.iobenchmarks
Configuration

GenomeOcean-4B, FP8 KV cache, vLLM generation (Yu et al. 2026)

Protocol B.1: FP8 E4M3 KV cache with dynamic per-tensor scaling; weights and activations BF16.

1 evaluation · 4 results

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Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Evaluations and results

1 evaluation · 4 results. Different protocols are not a single leaderboard.

Protocol: GenomeOcean-4B autoregressive generation throughput, power, energy efficiency and perplexity, BF16 versus FP8 (Yu et al. 2026 Table 4) · Dataset: 96 GTDB Bacteria genome sequences bounded to 102,400 tokens (Yu et al. 2026)

Sorted by Energy efficiency (Autoregressive generation; generated tokens per second per watt) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.

Tested configurationEnergy efficiency (Autoregressive generation; generated tokens per second per watt)Inference throughput (Autoregressive generation; generated tokens per second)Perplexity (Sliding-window perplexity on 96 GTDB Bacteria sequences (10,240-token context, 2,560-token stride))Power draw (Autoregressive generation; mean steady-state GPU power from NVML)
GenomeOcean-4B, FP8 KV cache, vLLM generation (Yu et al. 2026)Evaluation3.14 ± 0.022085.89 ± 34.49126.63 ± 1.04663.77 ± 8.84
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Tested configurationProtocol and datasetFindingEvidence and details
Configuration: GenomeOcean-4B, FP8 KV cache, vLLM generation (Yu et al. 2026)Protocol: GenomeOcean-4B autoregressive generation throughput, power, energy efficiency and perplexity, BF16 versus FP8 (Yu et al. 2026 Table 4)
Dataset: 96 GTDB Bacteria genome sequences bounded to 102,400 tokens (Yu et al. 2026)
3.14 ± 0.02 Energy efficiency (Autoregressive generation; generated tokens per second per watt)
sample-per-joule · higher

Uncertainty: SD 0.02

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

GenomeOcean-4B FP8 KV-Cache generation (Yu et al. 2026)

model-execution-20261011-protocol-yu2026-genomeocean-generation-fp8

Aggregation: Not reported

FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 4, row Protocol 'B.1', Quantization Scheme 'FP8 KV-Cache', column 'Efficiency (tok/W)'
Configuration: GenomeOcean-4B, FP8 KV cache, vLLM generation (Yu et al. 2026)Protocol: GenomeOcean-4B autoregressive generation throughput, power, energy efficiency and perplexity, BF16 versus FP8 (Yu et al. 2026 Table 4)
Dataset: 96 GTDB Bacteria genome sequences bounded to 102,400 tokens (Yu et al. 2026)
126.63 ± 1.04 Perplexity (Sliding-window perplexity on 96 GTDB Bacteria sequences (10,240-token context, 2,560-token stride))
unitless · lower

Uncertainty: SD 1.04

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

GenomeOcean-4B FP8 KV-Cache generation (Yu et al. 2026)

model-execution-20261011-protocol-yu2026-genomeocean-generation-fp8

Aggregation: Not reported

FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 4, row Protocol 'B.1', Quantization Scheme 'FP8 KV-Cache', column 'Perplexity (± SD)'
Configuration: GenomeOcean-4B, FP8 KV cache, vLLM generation (Yu et al. 2026)Protocol: GenomeOcean-4B autoregressive generation throughput, power, energy efficiency and perplexity, BF16 versus FP8 (Yu et al. 2026 Table 4)
Dataset: 96 GTDB Bacteria genome sequences bounded to 102,400 tokens (Yu et al. 2026)
663.77 ± 8.84 Power draw (Autoregressive generation; mean steady-state GPU power from NVML)
watt · lower

Uncertainty: SD 8.84

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

GenomeOcean-4B FP8 KV-Cache generation (Yu et al. 2026)

model-execution-20261011-protocol-yu2026-genomeocean-generation-fp8

Aggregation: Not reported

FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 4, row Protocol 'B.1', Quantization Scheme 'FP8 KV-Cache', column 'Power (W)'
Configuration: GenomeOcean-4B, FP8 KV cache, vLLM generation (Yu et al. 2026)Protocol: GenomeOcean-4B autoregressive generation throughput, power, energy efficiency and perplexity, BF16 versus FP8 (Yu et al. 2026 Table 4)
Dataset: 96 GTDB Bacteria genome sequences bounded to 102,400 tokens (Yu et al. 2026)
2085.89 ± 34.49 Inference throughput (Autoregressive generation; generated tokens per second)
sample-per-second · higher

Uncertainty: SD 34.49

Coverage: Not reported scored / Not reported eligible

Author-reported evaluation · Source checked
Methods, coverage and source

GenomeOcean-4B FP8 KV-Cache generation (Yu et al. 2026)

model-execution-20261011-protocol-yu2026-genomeocean-generation-fp8

Aggregation: Not reported

FP8 Inference in Genomic Foundation Models: Theoretical vs. Realized Speedups on GenomeOcean · Table 4, row Protocol 'B.1', Quantization Scheme 'FP8 KV-Cache', column 'Throughput (tok/s)'

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Stable ID: model-execution-20261011-config-yu2026-genomeocean-4b-fp8-kv-vllm

areas
dna-genomes
contexts
research
method types
foundation_model
reported name
4B FP8 KV cache
foundation model eligible
true
version
GenomeOcean-4B
parameters
4B parameters
access reuse
Checkpoint release not stated in this source; benchmarking code at https://github.com/jgi-genomeocean/genomeocean_efficiency (not pinned)
hardware
description: One NVIDIA H100 SXM5 GPU, 80 GB HBM3 (Section 2.2)
protocol
Protocol B.1: FP8 E4M3 KV cache with dynamic per-tensor scaling; weights and activations BF16.
source locator
Sections 2.1-2.4; Table 1; Table 2
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