T4 · 16 GB

embeddinggemma-2

Open a report for complete measurements.
Task
Embedding · Text → Vectors
Workload
Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s
Batch size
Batch 4
Format · Engine
fp16 · sentence-transformers · PyTorch 2.12.1+cu126
Unit
vectors/sec
Mean throughput
366vectors/sec
Observed GPU occupancy
0.9 GiB
P95 latency
11 ms
Reports combined
2
View configuration and run options ↗

Launch this model

Paste in your terminal. The recipe starts the model and connects the selected app.

Model API
bash -o pipefail -c 'curl -fsSL --connect-timeout 10 --max-time 60 --retry 2 '\''https://m.recipes/launch.py'\'' | python3 - "$@"' -- '--engine' 'embedding-recipe' '--model' 'google/embeddinggemma-2' '--benchmark' '2846de88-e5c7-4d91-a005-cfd72c4df946' '--batch-size' '4' '--client' 'api'
Requirements and startup checks

Managed runtimes: Linux x86_64, Python 3 and a compatible NVIDIA GPU. Ollama recipes require Ollama. OpenCode 1 and 2 are supported; its tool-call check must pass before opening.

This report has no pinned model revision. Startup uses the named model; it does not reproduce an immutable checkpoint.

The model runs on your machine. Existing OpenCode configuration is not overwritten. Add --dry-run to inspect settings or --check to verify startup without opening the app.

Individual tests

Text → Vectors · Embedding · fp16 · sentence-transformers · embedding · vectors/sec
Sortable table
Individual tests · 2 rows
Test dateThroughputConcurrency / batchP95 (s)TTFT (ms)Observed occupancy (GiB)GPU power (W)Decode (tok/s)Uncached prefill (tok/s)ParametersView report
10/19/2026, 6:24:52 AM365.65 vectors/sec40.011—0.8957.1—Uncached prefill unavailableView reportParameters ↗77f9bf12 ↗
10/19/2026, 6:45:33 AM365.65 vectors/sec40.011—0.8958.66—Uncached prefill unavailableView reportParameters ↗2846de88 ↗

Recorded test parameters

Configuration 1 · Parameters
model
google/embeddinggemma-2
engine
sentence-transformers
quant
fp16
method
native-forward-v1
task
embedding
dataset
embedding-mteb-tasks-v1
context
embedding
input_tokens
0
output_tokens
0
duration
90
concurrency
4
unit
vectors/sec
software
{ "torch": "2.12.1+cu126", "transformers": "5.19.0", "sentence-transformers": "6.1.0", "OMP_NUM_THREADS": "2", "MKL_NUM_THREADS": "2", "OPENBLAS_NUM_THREADS": "2", "NUMEXPR_NUM_THREADS": "2" }
engine_provenance
—
kernel_settings
—
precision
fp16
resolution
—
performance_task
—
performance_scope
fixed tokenized STS-B English inputs; CUDA graph forward, pooling, host copy and normalization; excludes tokenization
batch_size
4
dimensions
—
weight_quantization
none
max_sequence_length
2048
model_scope
text-only
performance_dataset
mteb/stsbenchmark-sts@96943a16ea6a35129e253c659081cb59daf81b30
workload_mode
single
graph_mode
captured
model_revision
914f7f89142e33e77833254d9c9b90c3cef7303b
client_version
python-native-bench-1.1.3