Aquila 2 7B vs Swallow 30B
Aquila 2 7B (2023) and Swallow 30B (2025) are compact production models from Beijing Academy of Artificial Intelligence (BAAI) and Tokyo Institute of Technology. Aquila 2 7B ships a 2k-token context window, while Swallow 30B ships a 16k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Swallow 30B fits 8x more tokens; pick it for long-context work and Aquila 2 7B for tighter calls.
Decision scorecard
Local evidence first| Signal | Aquila 2 7B | Swallow 30B |
|---|---|---|
| Best for | general production evaluation | general production evaluation |
| Decision fit | General | General |
| Context window | 2k | 16k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Use Aquila 2 7B when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
- Swallow 30B has the larger context window for long prompts, retrieval packs, or transcript analysis.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Aquila 2 7B
Unavailable
No complete token price in local provider data
Swallow 30B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Aquila 2 7B and Swallow 30B; plan for SDK, billing, or endpoint changes.
- No overlapping tracked provider route is sourced for Swallow 30B and Aquila 2 7B; plan for SDK, billing, or endpoint changes.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-11-02 | 2025-02-14 |
| Context window | 2k | 16k |
| Parameters | 7B | 30B |
| Architecture | decoder only | - |
| License | Proprietary | Llama 2 Community |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | - | 2023 |
Pricing and availability
| Pricing attribute | Aquila 2 7B | Swallow 30B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Aquila 2 7B | Swallow 30B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
Pricing coverage is uneven: Aquila 2 7B has no token price sourced yet and Swallow 30B has no token price sourced yet. Provider availability is 0 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Aquila 2 7B when provider fit are central to the workload. Choose Swallow 30B when long-context analysis and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Aquila 2 7B or Swallow 30B?
Swallow 30B supports 16k tokens, while Aquila 2 7B supports 2k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Aquila 2 7B or Swallow 30B open source?
Aquila 2 7B is listed under Proprietary. Swallow 30B is listed under Llama 2 Community. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
When should I pick Aquila 2 7B over Swallow 30B?
Swallow 30B fits 8x more tokens; pick it for long-context work and Aquila 2 7B for tighter calls. If your workload also depends on provider fit, start with Aquila 2 7B; if it depends on long-context analysis, run the same evaluation with Swallow 30B.
What is the main difference between Aquila 2 7B and Swallow 30B?
Aquila 2 7B and Swallow 30B differ most on context, provider coverage, capabilities, or pricing depending on the data currently sourced. Use the specs table first, then validate the model behavior with your own prompts.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.