Aquila 2 Models by Beijing Academy of Artificial Intelligence (BAAI)
Last refreshed 2026-05-19. Next refresh: weekly.
Details
About
The Aquila 2 family is a series of bilingual large language models designed to proficiently handle Chinese and English languages. These models vary significantly in size, from 7 billion to 70 billion parameters, offering a broad range for different computational needs. They are developed using the advanced HeuriMentor (HM) framework, which enhances the training process by dynamically adjusting data distributions, thereby boosting efficiency and model performance. This framework includes components such as the Adaptive Training Engine (ATE) and Training State Monitor (TSM). The Aquila 2 models consistently perform well on key benchmarks and have been open-sourced to encourage further innovation. Notably, the Aquila2-34B model retains performance standards even when quantized to Int4 format, highlighting its efficiency and accuracy. The AquilaChat2 variants are specially fine-tuned for conversational applications, demonstrating the versatility of the Aquila 2 family 14.
Decision facts
- Best fit
- codingchatbot and role-playing use caseslong-context generation
- Capability starting point
- Aquila Chat 2 34B-16K with 16k context
- Lowest tracked input
- Not tracked
- Closest related family
- BGE
Current Variants
Use-when guidance is based on each model's tracked capabilities, context window, release date, and replacement status.
Use when the workload needs 2k context and 70B parameters.
Use when the workload needs 2k context and 34B parameters.
Use when the workload needs 2k context and 7B parameters.
Use when the workload needs 16k context and 34B parameters.
Use when the workload needs 16k context and 7B parameters.
Use when the workload needs 2k context and 70B parameters.
Use when the workload needs 2k context and 34B parameters.
Use when the workload needs 2k context and 7B parameters.
| Model | Use when | Released | Signals | Status |
|---|---|---|---|---|
| Aquila Chat 2 70B Expressive | Use when the workload needs 2k context and 70B parameters. | 2023-11 | 2k context70B parameters | Current |
| Aquila Chat 2 34B | Use when the workload needs 2k context and 34B parameters. | 2023-11 | 2k context34B parameters | Current |
| Aquila Chat 2 7B | Use when the workload needs 2k context and 7B parameters. | 2023-11 | 2k context7B parameters | Current |
| Aquila Chat 2 34B-16K | Use when the workload needs 16k context and 34B parameters. | 2023-11 | 16k context34B parameters | Current |
| Aquila Chat 2 7B-16K | Use when the workload needs 16k context and 7B parameters. | 2023-11 | 16k context7B parameters | Current |
| Aquila 2 70B Expressive | Use when the workload needs 2k context and 70B parameters. | 2023-11 | 2k context70B parameters | Current |
| Aquila 2 34B | Use when the workload needs 2k context and 34B parameters. | 2023-11 | 2k context34B parameters | Current |
| Aquila 2 7B | Use when the workload needs 2k context and 7B parameters. | 2023-11 | 2k context7B parameters | Current |
Release Timeline
1 release groupSpecifications(8 models)
| Model | Released | Context | Parameters |
|---|---|---|---|
| Aquila Chat 2 70B Expressive | 2023-11 | 2k | 70B |
| Aquila Chat 2 34B | 2023-11 | 2k | 34B |
| Aquila Chat 2 7B | 2023-11 | 2k | 7B |
| Aquila Chat 2 34B-16K | 2023-11 | 16k | 34B |
| Aquila Chat 2 7B-16K | 2023-11 | 16k | 7B |
| Aquila 2 70B Expressive | 2023-11 | 2k | 70B |
| Aquila 2 34B | 2023-11 | 2k | 34B |
| Aquila 2 7B | 2023-11 | 2k | 7B |
Popular comparisons in this family
- Aquila 2 7B vs Bielik 11B v2.6 Instruct37
- Aquila 2 34B vs Hunyuan Hy3 Preview12
- Aquila 2 7B vs Falcon 180B9
- Aquila 2 7B vs Xiaomi MiMo-V2.59
- Aquila 2 7B vs Dracarys Llama 3.1 70B Instruct9
- Aquila Chat 2 70B Expressive vs Dracarys Llama 3.1 70B Instruct8
- Aquila 2 7B vs Llama 3.1 Swallow 8B Instruct8
- Aquila 2 34B vs Llama 2 7B Chat7
- Aquila 2 34B vs Llama 3 Taiwan 70B Instruct7
- Aquila 2 7B vs Claude Instant6
