V100-PCIE-32GB · 32 GB
Qwen3-Embedding-0.6B
Open a report for complete measurements.
- Task
- Embedding · Text → Vectors
- Workload
- Text → Vectors · embedding-mteb-tasks-v1 · Test duration 90 s
- Batch size
- Batch 16
- Format · Engine
- fp16 · sentence-transformers · PyTorch 2.12.1+cu126
- Unit
- vectors/sec
- Mean throughput
- 771vectors/sec
- Observed GPU occupancy
- 1.7 GiB
- P95 latency
- 21 ms
- Reports combined
- 1
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' 'Qwen/Qwen3-Embedding-0.6B' '--benchmark' 'f91802d1-bb5b-49d8-b31e-280ef136e71b' '--batch-size' '16' '--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
| Test date | Throughput | Concurrency / batch | P95 (s) | TTFT (ms) | Observed occupancy (GiB) | GPU power (W) | Decode (tok/s) | Uncached prefill (tok/s) | Parameters | View report |
|---|---|---|---|---|---|---|---|---|---|---|
| 10/8/2026, 3:50:00 PM | 771.26 vectors/sec | 16 | 0.021 | — | 1.75 | 99.19 | — | Uncached prefill unavailableView report | Parameters ↗ | f91802d1 ↗ |
Recorded test parameters
Configuration 1 · Parameters
- model
- Qwen/Qwen3-Embedding-0.6B
- 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
- 16
- unit
- vectors/sec
- software
- { "torch": "2.12.1+cu126", "transformers": "5.19.0", "sentence-transformers": "6.1.0", "ctranslate2": "4.8.2", "faster-whisper": "1.2.1", "OMP_NUM_THREADS": "6", "MKL_NUM_THREADS": "6", "OPENBLAS_NUM_THREADS": "6", "NUMEXPR_NUM_THREADS": "6" }
- 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
- 16
- dimensions
- 1024
- weight_quantization
- —
- max_sequence_length
- 2048
- model_scope
- text-only
- performance_dataset
- mteb/stsbenchmark-sts@96943a16ea6a35129e253c659081cb59daf81b30
- workload_mode
- single
- graph_mode
- captured
- model_revision
- 97b0c614be4d77ee51c0cef4e5f07c00f9eb65b3
- client_version
- python-native-bench-1.1.3