Meta Llama 2 70B / Meta-Llama-2-70B-Chat — Provisioned throughput — Retired — shutdown February 27, 2026
For Meta Llama 2 70B / Meta-Llama-2-70B-Chat, provider is Databricks; lifecycle status is Retired; shutdown / retirement date is February 27, 2026; recommended replacement is Comparable model on the same offering, like Llama 3.2, 3.3, or 4 model of similar size; platform / deployment scope is Databricks Foundation Model APIs — provisioned throughput; serving offering or footprint is Provisioned throughput, recorded from its source on 2026-09-15.
- Provider
- Databricks our reading
- Model ID / API name
- Meta Llama 2 70B / Meta-Llama-2-70B-Chat verified
- Serving offering or footprint
- Provisioned throughput verified
- Lifecycle status
- Retired
- Shutdown / retirement date
- February 27, 2026 verified
- Recommended replacement
- Comparable model on the same offering, like Llama 3.2, 3.3, or 4 model of similar size verified
- Platform / deployment scope
- Databricks Foundation Model APIs — provisioned throughput our reading
Values marked our reading are our classification of what the source says — the source does not print them in those words. The quote below is the evidence for each one; judge it yourself.
What the source says
Meta Llama 2 70B / Meta-Llama-2-70B-Chat | Pay-per-token: October 30, 2024 Provisioned throughput: February 27, 2026 | Pay-per-token: Meta-Llama-4-Maverick Provisioned throughput: Comparable model on the same offering, like Llama 3.2, 3.3, or 4 model of similar size. |
— learn.microsoft.com, retrieved 2026-09-15
Where each value comes from
This source states these in separate places, so each value is shown with the passage that states it.
Serving offering or footprint and Shutdown / retirement date
Provisioned throughput: February 27, 2026
Recommended replacement
Provisioned throughput: Comparable model on the same offering, like Llama 3.2, 3.3, or 4 model of similar size.
— all from learn.microsoft.com, retrieved 2026-09-15
Source
- learn.microsoft.comhttps://learn.microsoft.com/en-us/azure/databricks/machine-learning/retired-models-policy