96 GB · 196 reports

RTX PRO 6000 Blackwell Server Edition · 96 GB

Qualified results first; original reports and full tables stay below.
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Embedding · Qualified results

Speeds compare only within one exact test. Recipe availability is checked on each report against the published recipe executor.
  1. embeddinggemma-2

    google · 2 tested configurations

    • fp16 · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s
      Throughput · Batch 1
      207vectors/sec
      Best measured · Batch 16
      2,939vectors/sec
      Observed GPU occupancy
      1.5GiB
      P95 latency
      5 ms
      Test details · 3 batch sizes

      Occupancy includes engine buffers and reserved KV cache. It is not the minimum VRAM required by the model.

      Reports combined counts reports, not inference requests. Request successes and failures are listed in each report.

      Engine
      sentence-transformers · PyTorch 2.12.1+cu130
      Protocol
      native-forward-v1
      Dataset
      embedding-mteb-tasks-v1
      Workload
      embedding
      Batch sizeMean throughput (vectors/sec)P95TTFTObserved occupancy (GiB)GPU power (W)Reports combinedView report
      B1206.795 ms—1.48119.31196678d3 ↗
      B4764.956 ms—1.48141.41196678d3 ↗
      B162,938.636 ms—1.48161.81196678d3 ↗
    • 1 other test configurations on this GPU
      • nf4 · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s
        Throughput · Batch 1
        189vectors/sec
        Best measured · Batch 16
        2,572vectors/sec
        Observed GPU occupancy
        1.3GiB
        P95 latency
        6 ms
        Test details · 3 batch sizes

        Occupancy includes engine buffers and reserved KV cache. It is not the minimum VRAM required by the model.

        Reports combined counts reports, not inference requests. Request successes and failures are listed in each report.

        Engine
        sentence-transformers · PyTorch 2.12.1+cu130
        Protocol
        native-forward-v1
        Dataset
        embedding-mteb-tasks-v1
        Workload
        embedding
        Batch sizeMean throughput (vectors/sec)P95TTFTObserved occupancy (GiB)GPU power (W)Reports combinedView report
        B1189.236 ms—1.33145.51c673556b ↗
        B4713.326 ms—1.33142.81c673556b ↗
        B162,571.537 ms—1.33162.71c673556b ↗
  2. Qwen3-Embedding-0.6B

    Qwen · 3 tested configurations

    • fp16 · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s
      Throughput · Batch 1
      232vectors/sec
      Best measured · Batch 32
      3,763vectors/sec
      Observed GPU occupancy
      2.2GiB
      P95 latency
      5 ms
      Test details · 3 batch sizes

      Occupancy includes engine buffers and reserved KV cache. It is not the minimum VRAM required by the model.

      Reports combined counts reports, not inference requests. Request successes and failures are listed in each report.

      Engine
      sentence-transformers · PyTorch 2.12.1+cu130
      Protocol
      native-forward-v1
      Dataset
      embedding-mteb-tasks-v1
      Workload
      embedding
      Batch sizeMean throughput (vectors/sec)P95TTFTObserved occupancy (GiB)GPU power (W)Reports combinedView report
      B1232.185 ms—2.22155165594583 ↗
      B81,601.215 ms—2.22191.2165594583 ↗
      B323,763.079 ms—2.22208.7165594583 ↗
    • 2 other test configurations on this GPU
      • nf4 · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 15 s
        Throughput · Batch 1
        196vectors/sec
        Best measured · Batch 32
        3,091vectors/sec
        Observed GPU occupancy
        1.6GiB
        P95 latency
        5 ms
        Test details · 3 batch sizes

        Occupancy includes engine buffers and reserved KV cache. It is not the minimum VRAM required by the model.

        Reports combined counts reports, not inference requests. Request successes and failures are listed in each report.

        Engine
        sentence-transformers · PyTorch 2.12.1+cu130
        Protocol
        native-forward-v1
        Dataset
        embedding-mteb-tasks-v1
        Workload
        embedding
        Batch sizeMean throughput (vectors/sec)P95TTFTObserved occupancy (GiB)GPU power (W)Reports combinedView report
        B1195.85 ms—1.61174.81b9501833 ↗
        B81,156.97 ms—1.611961b9501833 ↗
        B323,091.0810 ms—1.61207.41b9501833 ↗
      • fp16 · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 15 s
        Throughput · Batch 1
        218vectors/sec
        Best measured · Batch 32
        3,617vectors/sec
        Observed GPU occupancy
        2.2GiB
        P95 latency
        5 ms
        Test details · 3 batch sizes

        Occupancy includes engine buffers and reserved KV cache. It is not the minimum VRAM required by the model.

        Reports combined counts reports, not inference requests. Request successes and failures are listed in each report.

        Engine
        sentence-transformers · PyTorch 2.12.1+cu130
        Protocol
        native-forward-v1
        Dataset
        embedding-mteb-tasks-v1
        Workload
        embedding
        Batch sizeMean throughput (vectors/sec)P95TTFTObserved occupancy (GiB)GPU power (W)Reports combinedView report
        B1217.925 ms—2.22156.51a7d85bcf ↗
        B81,494.895 ms—2.22185.41a7d85bcf ↗
        B323,616.749 ms—2.22206.81a7d85bcf ↗

Occupancy includes engine buffers and reserved KV cache. It is not the minimum VRAM required by the model.

Sortable tables by exact test condition · 15 rows

C: concurrency · B: batch · —: not measured

Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 15 s · Batch 1 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
Qwen/Qwen3-Embedding-0.6BScaling curves ↗nf4sentence-transformersembeddingnative-forward-v1B1195.8195.8—0.0051.61174.8195.81.121 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 15 s · Batch 1 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
Qwen/Qwen3-Embedding-0.6BScaling curves ↗fp16sentence-transformersembeddingnative-forward-v1B1217.92217.92—0.0052.22156.5217.921.391 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 15 s · Batch 8 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
Qwen/Qwen3-Embedding-0.6BScaling curves ↗nf4sentence-transformersembeddingnative-forward-v1B81,156.91,156.9—0.0071.611961,156.95.91 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 15 s · Batch 8 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
Qwen/Qwen3-Embedding-0.6BScaling curves ↗fp16sentence-transformersembeddingnative-forward-v1B81,494.891,494.89—0.0052.22185.41,494.898.061 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 15 s · Batch 32 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
Qwen/Qwen3-Embedding-0.6BScaling curves ↗nf4sentence-transformersembeddingnative-forward-v1B323,091.083,091.08—0.011.61207.43,091.0814.91 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 15 s · Batch 32 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
Qwen/Qwen3-Embedding-0.6BScaling curves ↗fp16sentence-transformersembeddingnative-forward-v1B323,616.743,616.74—0.0092.22206.83,616.7417.491 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s · Batch 1 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
google/embeddinggemma-2Scaling curves ↗fp16sentence-transformersembeddingnative-forward-v1B1206.79206.79—0.0051.48119.3206.791.731 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s · Batch 1 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
google/embeddinggemma-2Scaling curves ↗nf4sentence-transformersembeddingnative-forward-v1B1189.23189.23—0.0061.33145.5189.231.31 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s · Batch 1 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
Qwen/Qwen3-Embedding-0.6BScaling curves ↗fp16sentence-transformersembeddingnative-forward-v1B1232.18232.18—0.0052.22155232.181.51 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s · Batch 4 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
google/embeddinggemma-2Scaling curves ↗fp16sentence-transformersembeddingnative-forward-v1B4764.95764.95—0.0061.48141.4764.955.411 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s · Batch 4 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
google/embeddinggemma-2Scaling curves ↗nf4sentence-transformersembeddingnative-forward-v1B4713.32713.32—0.0061.33142.8713.324.991 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s · Batch 8 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
Qwen/Qwen3-Embedding-0.6BScaling curves ↗fp16sentence-transformersembeddingnative-forward-v1B81,601.211,601.21—0.0052.22191.21,601.218.371 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s · Batch 16 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
google/embeddinggemma-2Scaling curves ↗fp16sentence-transformersembeddingnative-forward-v1B162,938.632,938.63—0.0061.48161.82,938.6318.161 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s · Batch 16 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
google/embeddinggemma-2Scaling curves ↗nf4sentence-transformersembeddingnative-forward-v1B162,571.532,571.53—0.0071.33162.72,571.5315.81 ↗
Embedding · Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s · Batch 32 · vectors/sec · 1 rows
ModelFormatEngineWorkloadConcurrency / batchMean throughputBest measuredTTFT (ms)P95 (s)Observed occupancy (GiB)GPU power (W)Lowest measuredThroughput / WReports combined
Qwen/Qwen3-Embedding-0.6BScaling curves ↗fp16sentence-transformersembeddingnative-forward-v1B323,763.073,763.07—0.0092.22208.73,763.0718.031 ↗
Scaling curves and individual runs

One model and test protocol per curve; different workloads are never joined into one line.

google/embeddinggemma-2 · fp16 · sentence-transformers · embedding · native-forward-v1

Mean throughput vectors/sec
Batch size 1: 207 vectors/sec; Batch size 4: 765 vectors/sec; Batch size 16: 2,940 vectors/sec08081,6202,4203,2301416Batch size · log₂

Measured points only. Select a point to open its source report.

Mean run P95 latency s
Batch size 1: 0.0055 s; Batch size 4: 0.00579 s; Batch size 16: 0.00624 s00.001720.003430.005150.006861416Batch size · log₂

Measured points only. Select a point to open its source report.

Mean GPU memory used GB
Batch size 1: 1.48 GB; Batch size 4: 1.48 GB; Batch size 16: 1.48 GB00.4060.8131.221.631416Batch size · log₂

Measured points only. Select a point to open its source report.

Each point is the mean of recorded runs at that level. A source report may differ from the mean; all runs are listed below.

Runs behind the curve · google/embeddinggemma-2 · vectors/sec · 3 rows
Batch sizeThroughputDecode (tok/s)Uncached prefill (tok/s)GPU power (W)TTFT (ms)P95 (s)Observed occupancy (GiB)Test dateView report
1206.79 vectors/sec—Uncached prefill unavailableView report119.33—0.0051.4810/19/2026, 10:00:34 PM196678d3 ↗
4764.95 vectors/sec—Uncached prefill unavailableView report141.4—0.0061.4810/19/2026, 10:00:34 PM196678d3 ↗
162,938.63 vectors/sec—Uncached prefill unavailableView report161.85—0.0061.4810/19/2026, 10:00:34 PM196678d3 ↗

Original reports

Every report for this task, including quality, diagnostic and legacy runs that do not enter comparisons.
Original reports · 5 rows
ModelTest taskFormatEngineWorkloadProtocolQuality scoreTest date
embeddinggemma-2 ↗Embeddingfp16sentence-transformersembeddingnative-forward-v1—10/19/2026, 10:00:34 PM
embeddinggemma-2 ↗Embeddingnf4sentence-transformersembeddingnative-forward-v1—10/19/2026, 9:52:34 PM
Qwen3-Embedding-0.6B ↗Embeddingfp16sentence-transformersembeddingnative-forward-v1—10/14/2026, 8:39:45 AM
Qwen3-Embedding-0.6B ↗Embeddingnf4sentence-transformersembeddingnative-forward-v1—10/14/2026, 6:35:06 AM
Qwen3-Embedding-0.6B ↗Embeddingfp16sentence-transformersembeddingnative-forward-v1—10/14/2026, 6:31:26 AM

Running benchmarks

0Updates automatically

No benchmarks are currently reported as running.

RTX PRO 6000 Blackwell Server Edition · 96 GB · 403 queued · 0 running · 0 awaiting reassignment · 6 succeeded · 3 failed or exhausted

Methodology

Average of error-free runs for the selected recorded configuration. Missing methods and fallback runs are not ranked. Performance index = average / fastest matching hardware × 100. Value index = performance per purchase cost / best comparable value × 100. Quality is separate by dataset and protocol. Prices are dated seller listings, not completed transactions or market averages.

Updated 11/5/2026, 11:07:29 PM