Llama 3.3 Nemotron Super 49B v1 vs Swallow 30B
Llama 3.3 Nemotron Super 49B v1 (2025) and Swallow 30B (2025) are compact production models from NVIDIA AI and Tokyo Institute of Technology. Llama 3.3 Nemotron Super 49B v1 ships a 128k-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.
Llama 3.3 Nemotron Super 49B v1 fits 8x more tokens; pick it for long-context work and Swallow 30B for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 3.3 Nemotron Super 49B v1 | Swallow 30B |
|---|---|---|
| Best for | general production evaluation | general production evaluation |
| Decision fit | Long context | General |
| Context window | 128k | 16k |
| Cheapest output | - | - |
| Provider routes | 1 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- 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.
- Use Swallow 30B when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 3.3 Nemotron Super 49B v1
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 Llama 3.3 Nemotron Super 49B v1 and Swallow 30B; plan for SDK, billing, or endpoint changes.
- No overlapping tracked provider route is sourced for Swallow 30B and Llama 3.3 Nemotron Super 49B v1; plan for SDK, billing, or endpoint changes.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-01 | 2025-02-14 |
| Context window | 128k | 16k |
| Parameters | 49B | 30B |
| Architecture | decoder only | - |
| License | 1 | Open Source |
| Knowledge cutoff | - | 2023 |
Pricing and availability
| Pricing attribute | Llama 3.3 Nemotron Super 49B v1 | Swallow 30B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Llama 3.3 Nemotron Super 49B v1 | 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: Llama 3.3 Nemotron Super 49B v1 has no token price sourced yet and Swallow 30B has no token price sourced yet. Provider availability is 1 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Llama 3.3 Nemotron Super 49B v1 when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Swallow 30B when provider fit 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, Llama 3.3 Nemotron Super 49B v1 or Swallow 30B?
Llama 3.3 Nemotron Super 49B v1 supports 128k tokens, while Swallow 30B supports 16k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Llama 3.3 Nemotron Super 49B v1 or Swallow 30B open source?
Llama 3.3 Nemotron Super 49B v1 is listed under 1. Swallow 30B 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 Llama 3.3 Nemotron Super 49B v1 and Swallow 30B?
Llama 3.3 Nemotron Super 49B v1 is available on NVIDIA NIM. Swallow 30B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 3.3 Nemotron Super 49B v1 over Swallow 30B?
Llama 3.3 Nemotron Super 49B v1 fits 8x more tokens; pick it for long-context work and Swallow 30B for tighter calls. If your workload also depends on long-context analysis, start with Llama 3.3 Nemotron Super 49B v1; if it depends on provider fit, run the same evaluation with Swallow 30B.
Continue comparing
Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.