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OpenAI model

Text Embedding 3 Large

Text Embedding 3 Large is a OpenAI model listed in the NextModel catalog for General chat via OpenAI, API workloads workloads. Its listed price is $0.13 / 1M tokens input and $0 / 1M tokens output, with a — token context window.

OpenAIPlatform curatedCatalog
Streaming
Input price$0.13 / 1M tokens
Output price$0 / 1M tokens
Context length— tokens
Max output8.2k tokens

What is Text Embedding 3 Large in NextModel?

Text Embedding 3 Large is a OpenAI model listed in the NextModel catalog for General chat via OpenAI, API workloads workloads. Its listed price is $0.13 / 1M tokens input and $0 / 1M tokens output, with a — token context window.

Best use cases

  • General chat via OpenAI
  • API workloads

OpenAI-compatible code example

Keep the OpenAI SDK style, set base_url to NextModel, and use the catalog model ID openai--text-embedding-3-large.

Python
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.nextmodel.app/v1"
)

resp = client.chat.completions.create(
    model="openai/text-embedding-3-large",
    messages=[{"role": "user", "content": "Hello from NextModel"}]
)

print(resp.choices[0].message.content)

Similar alternatives

OpenAICatalog

Available through the NextModel gateway via OpenAI.

$1.25 / 1M tokensInput$10 / 1M tokensOutputContext
Best forGeneral chat via OpenAI, API workloads
RoutingConfigured
Streaming
Platform curatedNextModel gateway catalog (Go origin)
View details
OpenAICatalog

Available through the NextModel gateway via OpenAI.

$0.02 / 1M tokensInput$0 / 1M tokensOutputContext
Best forGeneral chat via OpenAI, API workloads
RoutingConfigured
Streaming
Platform curatedNextModel gateway catalog (Go origin)
View details
OpenAICatalog

Available through the NextModel gateway via OpenAI.

$0 / 1M tokensInput$0 / 1M tokensOutputContext
Best forGeneral chat via OpenAI, API workloads
RoutingConfigured
Platform curatedNextModel gateway catalog (Go origin)
View details

Reading

Articles that explain Text Embedding 3 Large

FAQ

Text Embedding 3 Large API questions