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All-MiniLM-L6-v2

digitalocean/all-mini-lm-l6-v2

من digitalocean · العائلة: text-embedding · أُصدِر 2021-08-30

$0.009
الإدخال / 1M رمز
Unknown
الإخراج / 1M رمز
256
نافذة السياق
384
أقصى إخراج

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

القدرات

✗ استدعاء الأدوات✗ تفكير? إخراج منظم✗ المرفقات✓ أوزان مفتوحة✗ التحكم بالحرارة
الوسائط المدعومة: إدخال text · إخراج text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding1
  • Tool calling0/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)0/20
  • Provider availability1/10
Agents1
  • Tool calling0/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit0/15
  • Provider availability1/10
JSON / structured output20
  • Structured output / JSON mode0/50
  • Tool calling0/20
  • Temperature control0/10
  • Price-friendly for high-volume20/20
Cost efficiency95
  • Headline price (log-scaled)95/95
  • Has prompt-cache pricing0/5
Long context0
  • Context ≥ 100K0/100
Production-readiness50
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K0/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$0.05
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$0.09
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$0.02
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$0.07
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$0.11
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

تفاصيل التسعير

السعر المُوصى به من digitalocean · all-mini-lm-l6-v2

$0.009
إدخال
Unknown
إخراج

متاح لدى 1 مزود

المزودمعرف نموذج المزودإدخال / 1Mإخراج / 1Mالسياقتاريخ الإصدار
DigitalOcean
digitalocean
all-mini-lm-l6-v2$0.009Unknown2562021-08-30

Frequently asked questions

How much does All-MiniLM-L6-v2 cost?

All-MiniLM-L6-v2 costs $0.009 per 1M input tokens and Unknown per 1M output tokens, sourced from digitalocean. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of All-MiniLM-L6-v2?

All-MiniLM-L6-v2 has a context window of 256 tokens, with a max output of 384 tokens per reply. This is the total combined size of prompt + completion.

Does All-MiniLM-L6-v2 support tool calling?

No. All-MiniLM-L6-v2 does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.

Does All-MiniLM-L6-v2 support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for All-MiniLM-L6-v2 in our data source. Verify with digitalocean's official documentation before relying on it in production.

Can All-MiniLM-L6-v2 accept image input?

No. All-MiniLM-L6-v2 only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is All-MiniLM-L6-v2 open-weight?

Yes. All-MiniLM-L6-v2's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.

What are the best alternatives to All-MiniLM-L6-v2?

If All-MiniLM-L6-v2 doesn't fit, consider Multi-QA-mpnet-base-dot-v1, Wan2.2-T2V-A14B, E5 Large v2. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

Explore more

More digitalocean models

Capability lists this model is in

See also

آخر تحديث:

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.