# Can't deploy model on ML node due to insufficient memory

**URL:** <https://discuss.elastic.co/t/cant-deploy-model-on-ml-node-due-to-insufficient-memory/387871>\
**Category:** Elasticsearch\
**Tags:** elastic-stack-machine-learning\
**Created:** [July 8, 2026, 11:23am UTC](https://discuss.elastic.co/t/cant-deploy-model-on-ml-node-due-to-insufficient-memory/387871 "2026-07-08T11:23:02Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![Giorgi\_Jambazishvili](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/giorgi_jambazishvili/32/101881_2.png) [@Giorgi\_Jambazishvili](https://discuss.elastic.co/u/Giorgi_Jambazishvili)\
**Post date:** [July 8, 2026, 11:23am UTC](https://discuss.elastic.co/t/cant-deploy-model-on-ml-node-due-to-insufficient-memory/387871/1 "2026-07-08T11:23:02Z")

</div>

I am using Elasticsearch cloud. I currently host the free-tier ML node, but the same behavior occurs on the next available tier _(node w/ 2GB of memory)._

I am trying to deploy the `E5` embedding model, preferably base, but small could also be considered. When I start deploying the model _(base or small)_, we receive this error:

`Could not start deployment because no suitable nodes were found`

_`Reason:_ This _node has insufficient available memory. Available memory for ML [432013312 (412mb)], free memory [432013312 (412mb)], estimated memory required for this model [501554824 (478.3mb)]`_

I understand that the required memory exceeds the available memory. When I upgrade the node, the same error still occurs. However, after upgrading, the required memory is less than the available memory - how can I explain that?

In addition, I am not able to change `xpack.ml.max_machine_memory_percent` and/or `xpack.ml.use_auto_machine_memory_percent` setting, not from developer tools, neither from cluster management.

I need a clear explanation of how ES memory calculations work, because I can't wrap my head around:

- If required memory is more than avialable - I can't deploy.

- If required memory is less than available - I can't deploy.
- What is the case when I can deploy?

In addition, which part of the docs mention this, if explanation exists?