text-embedding-3-large
azure/text-embedding-3-large제공: azure · 패밀리: text-embedding · 출시 2024-01-25
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
기능
Model fit scores
0–100 · higher is betterThese 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 efficiency84
- Headline price (log-scaled)84/95
- Has prompt-cache pricing0/5
Long context0
- Context ≥ 100K0/100
Production-readiness58
- Number of independent providers5/40
- Has published per-token price20/20
- Context window ≥ 8K8/15
- 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.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.65 < $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 | $1.30 < $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 | $0.26 < $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 | $1.04 < $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 | $1.56 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
가격 상세
추천 가격 제공자: azure · text-embedding-3-large
1곳 제공사에서 이용 가능
| 제공자 | 제공자 모델 ID | 입력 / 1M | 출력 / 1M | 컨텍스트 | 출시일 |
|---|---|---|---|---|---|
| Azure azure | text-embedding-3-large | $0.130 | Unknown | 8K | 2024-01-25 |
Frequently asked questions
How much does text-embedding-3-large cost?
text-embedding-3-large costs $0.130 per 1M input tokens and Unknown per 1M output tokens, sourced from azure. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of text-embedding-3-large?
text-embedding-3-large has a context window of 8K tokens, with a max output of 3K tokens per reply. This is the total combined size of prompt + completion.
Does text-embedding-3-large support tool calling?
No. text-embedding-3-large does not support tool calling (function calling). If your workflow requires it, look at the /capabilities/tool-calling list for alternatives.
Does text-embedding-3-large support structured output / JSON mode?
Support for structured output / JSON-schema-constrained decoding is not reported for text-embedding-3-large in our data source. Verify with azure's official documentation before relying on it in production.
Can text-embedding-3-large accept image input?
No. text-embedding-3-large only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is text-embedding-3-large open-weight?
No. text-embedding-3-large is a proprietary model — only azure (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to text-embedding-3-large?
If text-embedding-3-large doesn't fit, consider Codex Mini, Ministral 3B, text-embedding-ada-002. 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 azure models
- Codex Mini$1.50 in / $6.00 out
- Ministral 3B$0.04 in / $0.04 out
- text-embedding-ada-002$0.10 in / $0.00 out
- o1$15.00 in / $60.00 out
- Model Router$0.14 in / $0.00 out
마지막 업데이트:
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.