LLM Reference

text-embedding-3-large

Released
2024-01-25
Last refreshed
2026-06-29
Status
Researched 128d ago
ProprietaryCommercial use: conditional

text-embedding-3-large is worth evaluating for general LLM work when its provider route and context window match the workload.

Use it for

  • Teams evaluating general LLM work
  • Workloads that can use a 8k context window
  • Buyers comparing 2 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Released
2024-01-25
Context
8k
Knowledge cutoff
2021-09
Specialization
embedding
Openness
Proprietary
License
ProprietaryCommercial use: conditional
Weights
Not released
Code
Unknown
Created by

Cutting-edge research and development.

San Francisco, California, United States
Founded 2015
Website
Pricing
Output / 1M
-
Input / 1M
$0.130

Cheapest of 2 routes · OpenAI API

About

OpenAI's most capable text embedding model with 3072 output dimensions (configurable). Supports Matryoshka representation learning for smaller embeddings with reduced quality loss.

Top use-case fit

No primary decision-task fit is mapped for this model yet.

Provider price ladder

Compare all 2

Compare API pricing across 2 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
OpenAI API$0.130-
ServerlessPartial
Vercel AI Gateway$0.130-
ServerlessPartial

Available via routers & gateways(15)

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Coding

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.