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sentence-transformers/all-MiniLM-L6-v2

deepinfra/sentence-transformers/all-MiniLM-L6-v2

textContext 512

We present a sentence transformation model that achieves state-of-the-art results on various NLP tasks without requiring task-specific architectures or fine-tuning. Our approach leverages contrastive learning and utilizes a variety of datasets to learn robust sentence representations. We evaluate our model on several benchmarks and demonstrate its effectiveness in various applications such as text classification, sentiment analysis, named entity recognition, and question answering.

Price

Input$0.005

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Every rate
UnitInputOutputFlatConfidence
token $0.005/1M Not published— Not published— official

Price history

sentence-transformers/all-MiniLM-L6-v2
0.0055 0 2026-10-08: $0.0052026-10-09: $0.0052026-10-10: $0.0052026-10-11: $0.0052026-10-12: $0.0052026-10-13: $0.0052026-10-14: $0.0052026-10-15: $0.0052026-10-16: $0.0052026-10-17: $0.0052026-10-18: $0.0052026-10-19: $0.0052026-10-20: $0.0052026-10-21: $0.0052026-10-22: $0.0052026-10-23: $0.0052026-10-24: $0.0052026-10-25: $0.0052026-10-26: $0.0052026-10-27: $0.0052026-10-28: $0.0052026-10-29: $0.0052026-10-30: $0.005 2026-10-08 2026-10-30

input or flat output

Daily snapshots
UTC dateUnitInputOutputFlat
2026-10-08 token $0.005 Not published— Not published—
2026-10-09 token $0.005 Not published— Not published—
2026-10-10 token $0.005 Not published— Not published—
2026-10-11 token $0.005 Not published— Not published—
2026-10-12 token $0.005 Not published— Not published—
2026-10-13 token $0.005 Not published— Not published—
2026-10-14 token $0.005 Not published— Not published—
2026-10-15 token $0.005 Not published— Not published—
2026-10-16 token $0.005 Not published— Not published—
2026-10-17 token $0.005 Not published— Not published—
2026-10-18 token $0.005 Not published— Not published—
2026-10-19 token $0.005 Not published— Not published—
2026-10-20 token $0.005 Not published— Not published—
2026-10-21 token $0.005 Not published— Not published—
2026-10-22 token $0.005 Not published— Not published—
2026-10-23 token $0.005 Not published— Not published—
2026-10-24 token $0.005 Not published— Not published—
2026-10-25 token $0.005 Not published— Not published—
2026-10-26 token $0.005 Not published— Not published—
2026-10-27 token $0.005 Not published— Not published—
2026-10-28 token $0.005 Not published— Not published—
2026-10-29 token $0.005 Not published— Not published—
2026-10-30 token $0.005 Not published— Not published—

Alternatives

Parameters (1)
embed
Call this model

OpenRouter id deepinfra/sentence-transformers/all-MiniLM-L6-v2. InferenceList does not send the request.

curl 
curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepinfra/sentence-transformers/all-MiniLM-L6-v2","messages":[{"role":"user","content":"Hello"}]}'

JavaScript 
await fetch("https://openrouter.ai/api/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: "Bearer " + process.env.OPENROUTER_API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "deepinfra/sentence-transformers/all-MiniLM-L6-v2",
    messages: [{ role: "user", content: "Hello" }],
  }),
});

Python 
import os, json, urllib.request
req = urllib.request.Request(
    "https://openrouter.ai/api/v1/chat/completions",
    data=json.dumps({"model": "deepinfra/sentence-transformers/all-MiniLM-L6-v2", "messages": [{"role": "user", "content": "Hello"}]}).encode(),
    headers={"Authorization": "Bearer " + os.environ["OPENROUTER_API_KEY"], "Content-Type": "application/json"},
)
print(urllib.request.urlopen(req).read().decode())

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