Chinchilla 70B
Chinchilla 70B has model metadata, but missing tracked provider pricing keeps it from being a default production pick.
Use it for
- Teams evaluating general LLM work
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
- Chinchilla
- Released
- 2022-03-29
- Parameters
- 70B
- Architecture
- Decoder Only
- Specialization
- general
- Training
- finetuned
No tracked provider token pricing is available yet.
About
Chinchilla 70B is a large language model from Google DeepMind, launched in March 2022. It adopts a compute-optimal approach, emphasizing a balance between model size and training data quantity, contrasting previous trends that prioritized model size alone. The model's architecture is based on transformers and utilizes innovations like RMSNorm and relative positional encoding. Trained with the MassiveText dataset using 1.4 trillion tokens, Chinchilla delivers superior performance compared to other larger models like GPT-3. While it demonstrates efficiency in tasks such as reading comprehension and common sense reasoning, limitations include high training costs and the potential for biased outputs. Additionally, it remains inaccessible for public use, restricting broader experimentation.
Chinchilla 70B is a model in the Chinchilla family. No headline benchmark score is tracked for Chinchilla 70B 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.