text-babbage
text-babbage has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Use it for
- Teams evaluating general LLM work
- Workloads that can use a 2k context window
Do not use it for
- Cost-sensitive launches that need sourced token pricing
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
- Family
- GPT-3 Instruct
- Released
- 2020-06-01
- Context
- 2k
- Parameters
- 1.3B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2019-10
- Specialization
- general
- Training
- finetuned
About
The text-babbage-001 model is part of the GPT-3 family, distinguished by its speed and cost-effectiveness relative to more advanced variants like text-davinci-003. It is particularly adept at straightforward tasks such as semantic search and simple classification, though its abilities are less comprehensive than those of larger models. Despite initially being a base model, enhancements for instruction-based tasks have refined its performance. Although OpenAI hasn't detailed the model's parameter count, it is estimated to have 1.3 billion parameters. With a token window of 2049 tokens, it balances performance and efficiency, sitting in the middle range of GPT-3 models.
text-babbage is a model in the GPT-3 Instruct family. The structured metadata tracks a 2k-token context window. No headline benchmark score is tracked for text-babbage yet.
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
No tracked provider token pricing is available 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
text-babbage-001