Aquila 2 34B vs Llama 2 7B
Aquila 2 34B (2023) and Llama 2 7B (2023) are compact production models from Beijing Academy of Artificial Intelligence (BAAI) and AI at Meta. Aquila 2 34B ships a not-yet-sourced context window, while Llama 2 7B ships a 4K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Aquila 2 34B is safer overall; choose Llama 2 7B when provider fit matters.
Decision scorecard
Local evidence first| Signal | Aquila 2 34B | Llama 2 7B |
|---|---|---|
| Decision fit | General | Coding and Classification |
| Context window | — | 4K |
| Cheapest output | - | $0.2/1M tokens |
| Provider routes | 0 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Use Aquila 2 34B when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
- Llama 2 7B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 2 7B has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 2 7B for Coding and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Aquila 2 34B
Unavailable
No complete token price in local provider data
Llama 2 7B
$210
Cheapest tracked route: Fireworks AI
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 34B and Llama 2 7B; plan for SDK, billing, or endpoint changes.
- No overlapping tracked provider route is sourced for Llama 2 7B and Aquila 2 34B; plan for SDK, billing, or endpoint changes.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-11-02 | 2023-07-18 |
| Context window | — | 4K |
| Parameters | 34B | 7B |
| Architecture | decoder only | decoder only |
| License | Unknown | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Aquila 2 34B | Llama 2 7B |
|---|---|---|
| Input price | - | $0.2/1M tokens |
| Output price | - | $0.2/1M tokens |
| Providers | - |
Capabilities
| Capability | Aquila 2 34B | Llama 2 7B |
|---|---|---|
| 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 |
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 34B has no token price sourced yet and Llama 2 7B has $0.2/1M input tokens. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Aquila 2 34B when provider fit are central to the workload. Choose Llama 2 7B when provider fit and broader provider choice 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
Is Aquila 2 34B or Llama 2 7B open source?
Aquila 2 34B is listed under Unknown. Llama 2 7B is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Where can I run Aquila 2 34B and Llama 2 7B?
Aquila 2 34B is available on the tracked providers still being sourced. Llama 2 7B is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Aquila 2 34B over Llama 2 7B?
Aquila 2 34B is safer overall; choose Llama 2 7B when provider fit matters. If your workload also depends on provider fit, start with Aquila 2 34B; if it depends on provider fit, run the same evaluation with Llama 2 7B.
What is the main difference between Aquila 2 34B and Llama 2 7B?
Aquila 2 34B and Llama 2 7B 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: 2026-04-19. Data sourced from public model cards and provider documentation.