2026-10-07-quick-card-prompts-f0c765
By output dimension
| Dims | Score (95% interval over tasks) | Δ vs reference | Fidelity |
|---|---|---|---|
| 768 | −0.71 [−1.01, −0.43] | degradedcos 0.9805 · top-10 0.72 | |
| 512 | −0.27 [−0.93, +0.28] | degradedcos 0.9812 · top-10 0.72 | |
| 256 | −0.45 [−1.23, +0.55] | degradedcos 0.9832 · top-10 0.69 | |
| 128 | −0.24 [−1.06, +0.50] | degradedcos 0.9879 · top-10 0.63 |
Per task
MTEB main score ×100
| Task | 768 | 512 | 256 | 128 |
|---|---|---|---|---|
| NanoArguAnaRetrieval | 65.01 | 64.78 | 65.27 | 59.49 |
| NanoClimateFeverRetrieval | 27.28 | 28.36 | 26.81 | 26.29 |
| NanoDBPediaRetrieval | 64.40 | 62.33 | 61.19 | 55.47 |
| NanoFEVERRetrieval | 90.47 | 92.36 | 89.03 | 85.97 |
| NanoFiQA2018Retrieval | 44.45 | 44.09 | 39.67 | 33.58 |
| NanoHotpotQARetrieval | 88.79 | 89.10 | 87.52 | 79.34 |
| NanoMSMARCORetrieval | 56.46 | 56.38 | 55.00 | 51.56 |
| NanoNFCorpusRetrieval | 38.27 | 36.33 | 34.20 | 28.92 |
| NanoNQRetrieval | 76.70 | 75.96 | 71.22 | 70.66 |
| NanoQuoraRetrieval | 95.27 | 95.32 | 94.90 | 92.20 |
| NanoSCIDOCSRetrieval | 36.67 | 38.10 | 35.77 | 30.70 |
| NanoSciFactRetrieval | 86.77 | 86.08 | 85.17 | 74.45 |
| NanoTouche2020Retrieval | 43.42 | 44.29 | 43.39 | 39.80 |
| STSBenchmark | 87.24 | 87.29 | 87.24 | 86.83 |
| Banking77Classification | 91.61 | 91.62 | 91.57 | 90.34 |
Throughput
- Prefill tokens/s (engine)
- 12,530 (embedding has no decode)
- Prefill tokens/s (wall)
- 7,183 (includes HTTP and base64)
- Texts
- 66,939 texts · 11,589,994 tokens · 41.5 texts/s
- Engine
- backend=onnxruntime · onnx_file=model_q4.onnx · requested_provider=CUDAExecutionProvider · active_providers=CUDAExecutionProvider,CPUExecutionProvider · onnxruntime=1.29.0 · transformers=5.19.0 · max_seq_length=8192 · token_budget_per_forward=16384 · python=3.12.15 · platform=Linux-7.0.0-34-generic-x86_64-with-glibc2.36 · machine=x86_64 · numpy=2.5.3
Run
- Suite
- embeddings · quick tier · profile card-prompts · mode native
- Items
- 2,092 succeeded of 2,092 attempted (66,939 planned)
- When
- 2026-10-07 04:54:28 UTC · 31 min
- Hardware
- NVIDIA P100 · 16 GB
2026-10-07: device facts copied from the operator's inventory after the run; the launcher did not record them yet - Harness
- bench @ d7cc285 · scorer mteb 2.22.5
- Suite hash
- d499aab0d7091e3ba5b211e1cbaedf79ed4c9c86a7214156946d2ee4d21299ec
- Recipe
- embeddinggemma-2/p100/st-ort · profile ort-q4 · inference-engines @ 98e8454
- Latency
- p50 541 ms · p95 1.63 s · p99 4.04 s (per request)
- Usage
- 11,589,994 input tokens · 0 output tokens · $0.00
- dimensions below 768 are the same vectors truncated and re-normalized (Matryoshka); fidelity compares each dimension with the reference at the same dimension
Reproduce
npm run bench -- run --recipe embeddinggemma-2/p100/st-ort \
--recipe-profile ort-q4 \
--on <host with a p100:p100> \
--suite embeddings --tier quick --profile card-prompts \
--reference results/embeddinggemma-2/hf-914f7f8/fp32-google/sentence-transformers-torch-cuda-st6.1.0-torch2.14.1-cu126/embeddings/2026-10-07-quick-card-prompts-d0777fFiles
exactly as committed under results/