# Weaviate Openai Embedding Models **URL:** \ **Category:** General\ **Created:** [August 16, 2024, 3:01pm UTC](https://forum.weaviate.io/t/weaviate-openai-embedding-models/3375 "2024-08-16T15:01:30Z")\ **Posts on this page:** 9\ **Page:** 1
**Author:** ![spark](https://avatars.discourse-cdn.com/v4/letter/s/4da419/32.png) [@spark](https://forum.weaviate.io/u/spark)\ **Post date:** [August 16, 2024, 3:01pm UTC](https://forum.weaviate.io/t/weaviate-openai-embedding-models/3375/1 "2024-08-16T15:01:30Z")
do we have any models for text2vec-openai embedding module which has token limit greater than 8192? the message i’m getting: `weaviate.exceptions.UnexpectedStatusCodeException: Create class! Unexpected status code: 422, with response body: {'error': [{'message': "module 'text2vec-openai': wrong OpenAI model name, available model names are: [ada babbage curie davinci text-embedding-3-small text-embedding-3-large]"}]}.` ```auto "moduleConfig": { "generative-openai": {}, "text2vec-openai": { "model": "?????", } }, ``` ---
**Author:** ![DudaNogueira](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/dudanogueira/32/7846_2.png) [@DudaNogueira](https://forum.weaviate.io/u/DudaNogueira)\ **Post date:** [August 16, 2024, 6:47pm UTC](https://forum.weaviate.io/t/weaviate-openai-embedding-models/3375/2 "2024-08-16T18:47:06Z")
hi @spark !! by default, if you do not provide a model, it will use ada. However, you can use any of the supported models, as stated in the error message: - ada - babbage - curie - davinci - text-embedding-3-small - text-embedding-3-large Notice that with the last two you can also specify the dimensions. You can find more informations on this here: > **[text2vec-openai | Weaviate - Vector Database](https://weaviate.io/developers/weaviate/modules/retriever-vectorizer-modules/text2vec-openai#available-models-openai)** > > Overview Let me know if that helps! THanks! ---
**Author:** ![spark](https://avatars.discourse-cdn.com/v4/letter/s/4da419/32.png) [@spark](https://forum.weaviate.io/u/spark)\ **Post date:** [August 16, 2024, 7:22pm UTC](https://forum.weaviate.io/t/weaviate-openai-embedding-models/3375/3 "2024-08-16T19:22:22Z")
I totally understand @DudaNogueira but could you please help me out in this regard which I’m facing, I was using the default. `{'error': [{'message': "update vector: connection to: OpenAI API failed with status: 400 error: This model's maximum context length is 8192 tokens, however you requested 9655 tokens (9655 in your prompt; 0 for the completion). Please reduce your prompt; or completion length."}]}` `{'error': [{'message': "update vector: connection to: OpenAI API failed with status: 400 error: This model's maximum context length is 8192 tokens, however you requested 9745 tokens (9745 in your prompt; 0 for the completion). Please reduce your prompt; or completion length."}]}` ---
**Author:** ![JK\_Rider](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/jk_rider/32/1671_2.png) [@JK\_Rider](https://forum.weaviate.io/u/JK_Rider)\ **Post date:** [August 17, 2024, 5:00pm UTC](https://forum.weaviate.io/t/weaviate-openai-embedding-models/3375/4 "2024-08-17T17:00:37Z")
All of Openai’s embedding models currently max out 8192 tokens. Some open-source embedding models support larger context windows, but I’d suggest chunking your data and you’ll(probably) get better performance that way too. ---
**Author:** ![spark](https://avatars.discourse-cdn.com/v4/letter/s/4da419/32.png) [@spark](https://forum.weaviate.io/u/spark)\ **Post date:** [August 18, 2024, 3:08pm UTC](https://forum.weaviate.io/t/weaviate-openai-embedding-models/3375/5 "2024-08-18T15:08:03Z")
Could you please guide in this regard? @DudaNogueira @JK_Rider ---
**Author:** ![JK\_Rider](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/jk_rider/32/1671_2.png) [@JK\_Rider](https://forum.weaviate.io/u/JK_Rider)\ **Post date:** [August 18, 2024, 3:53pm UTC](https://forum.weaviate.io/t/weaviate-openai-embedding-models/3375/6 "2024-08-18T15:53:04Z")
Here’s a quick guide on Chunking which should help out:[A Guide to Chunking Strategies for Retrieval Augmented Generation (RAG) — Sagacify](https://www.sagacify.com/news/a-guide-to-chunking-strategies-for-retrieval-augmented-generation-rag). ---
**Author:** ![DudaNogueira](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/dudanogueira/32/7846_2.png) [@DudaNogueira](https://forum.weaviate.io/u/DudaNogueira)\ **Post date:** [August 19, 2024, 12:56pm UTC](https://forum.weaviate.io/t/weaviate-openai-embedding-models/3375/7 "2024-08-19T12:56:58Z")
hi @spark !! as @JK_Rider mentioned, the issue is about passing too much context. If you see this when vectorizing (which seems to be the case, considering the “update vector” part of the log), it is probably be because your chunks are too big to fit in that context windows. However, if you see this while generating, you are probably passing too much objects (limit=X) to the generation step. here are some other content on chunking. As you will soon discover, there isn’t a “one size fits all”, as it will depend on a lot of requirements. > **[A brief introduction to chunking | Weaviate - Vector Database](https://weaviate.io/developers/academy/py/standalone/chunking/introduction)** > > \