LLM Reference

babbage

Released
2023-08-22
Last refreshed
2026-04-27
Status
Researched 244d ago
ProprietaryCommercial use: conditional

babbage 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 2k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Family
GPT-3
Released
2023-08-22
Context
2k
Parameters
1.3B
Architecture
Decoder Only
Knowledge cutoff
2021-09
Specialization
general
Openness
Proprietary
License
ProprietaryCommercial use: conditional
Weights
Not released
Code
Unknown
Training
Fine-tuned
Created by

Cutting-edge research and development.

San Francisco, California, United States
Founded 2015
Website
Pricing
Output / 1M
$0.400
Input / 1M
$0.400

Cheapest of 1 route · Azure OpenAI

About

The Babbage model is a large language AI model within the GPT-3 family, recognized for its speed and cost-effectiveness 569. Although it is not as capable as the Davinci model, it outperforms the Ada model in various capabilities 129. Ideal for simpler classification tasks and semantic searches, Babbage efficiently ranks document relevance to search queries 129. With an estimated 1.3 billion parameters 9, it requires less computational power compared to other models like Davinci, which has 175 billion parameters 9.

Top use-case fit

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

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.

API versions

babbagebabbage-002