LLM Reference

Aquila 2 70B Expressive

Released
2023-11-02
Last refreshed
2026-05-19
Status
Researched 16d ago

Aquila 2 70B Expressive 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
Specifications
Family
Aquila 2
Released
2023-11-02
Context
2k
Parameters
70B
Architecture
Decoder Only
Specialization
general
Training
finetuned
Created by

Open-source AI fostering global collaboration

Beijing, China
Founded 2018
Website
Pricing

No tracked provider token pricing is available yet.

About

The Aquila2-70B-Expr, developed by the Beijing Academy of Artificial Intelligence, is a large language model featuring 70 billion parameters. It is part of the Aquila2 series, known for its bilingual capabilities in English and Chinese. This experimental model excels in language understanding and generation, supported by the HeuriMentor framework which optimizes training through dynamic data distribution. Its training process benefits from techniques like Grouped Query Attention and Rotary Position Embedding for improved efficiency. As an open-source model, Aquila2-70B-Expr's weights and code are accessible, allowing independent research and development, though users should note its experimental nature and the substantial computational resources required for its deployment.

Aquila 2 70B Expressive is a model in the Aquila 2 family. The structured metadata tracks a 2k-token context window. No headline benchmark score is tracked for Aquila 2 70B Expressive 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.

Rankings & picks(4)