Aquila 2 7B vs Llama 3.3 Nemotron Super 49B v1
Aquila 2 7B (2023) and Llama 3.3 Nemotron Super 49B v1 (2025) are compact production models from Beijing Academy of Artificial Intelligence (BAAI) and NVIDIA AI. Aquila 2 7B ships a 2k-token context window, while Llama 3.3 Nemotron Super 49B v1 ships a 128k-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.
Llama 3.3 Nemotron Super 49B v1 fits 64x more tokens; pick it for long-context work and Aquila 2 7B for tighter calls.
Decision scorecard
Local evidence first| Signal | Aquila 2 7B | Llama 3.3 Nemotron Super 49B v1 |
|---|---|---|
| Best for | general production evaluation | general production evaluation |
| Decision fit | General | Long context |
| Context window | 2k | 128k |
| Cheapest output | - | - |
| Provider routes | 0 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
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.
- Llama 3.3 Nemotron Super 49B v1 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 3.3 Nemotron Super 49B v1 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.3 Nemotron Super 49B v1 for Long context.
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
Llama 3.3 Nemotron Super 49B v1
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 Llama 3.3 Nemotron Super 49B v1; plan for SDK, billing, or endpoint changes.
- No overlapping tracked provider route is sourced for Llama 3.3 Nemotron Super 49B v1 and Aquila 2 7B; plan for SDK, billing, or endpoint changes.
Specs
| Specification | ||
|---|---|---|
| Released | 2023-11-02 | 2025-06-01 |
| Context window | 2k | 128k |
| Parameters | 7B | 49B |
| Architecture | Decoder Only | Decoder Only |
| License | Proprietary | NVIDIA Open Model |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Aquila 2 7B | Llama 3.3 Nemotron Super 49B v1 |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Aquila 2 7B | Llama 3.3 Nemotron Super 49B v1 |
|---|---|---|
| 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 scores are currently available 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 Llama 3.3 Nemotron Super 49B v1 has no token price sourced yet. 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 7B when provider fit are central to the workload. Choose Llama 3.3 Nemotron Super 49B v1 when long-context analysis, larger context windows, 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.
FAQ
Which has a larger context window, Aquila 2 7B or Llama 3.3 Nemotron Super 49B v1?
Llama 3.3 Nemotron Super 49B v1 supports 128k 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 Llama 3.3 Nemotron Super 49B v1 open source?
Aquila 2 7B is listed under Proprietary. Llama 3.3 Nemotron Super 49B v1 is listed under NVIDIA Open Model. 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 7B and Llama 3.3 Nemotron Super 49B v1?
Aquila 2 7B is available on the tracked providers still being sourced. Llama 3.3 Nemotron Super 49B v1 is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Aquila 2 7B over Llama 3.3 Nemotron Super 49B v1?
Llama 3.3 Nemotron Super 49B v1 fits 64x 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 Llama 3.3 Nemotron Super 49B v1.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.