Nemotron-Nano-9B-v2 vs Stockmark 2 100B Instruct
Nemotron-Nano-9B-v2 (2025) and Stockmark 2 100B Instruct (2025) are compact production models from NVIDIA AI and Stockmark. Nemotron-Nano-9B-v2 ships a not-yet-sourced context window, while Stockmark 2 100B Instruct 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. It focuses on practical selection signals rather than broad model-family marketing.
Nemotron-Nano-9B-v2 is safer overall; choose Stockmark 2 100B Instruct when provider fit matters.
Decision scorecard
Local evidence first| Signal | Nemotron-Nano-9B-v2 | Stockmark 2 100B Instruct |
|---|---|---|
| Best for | provider-routed production | general production evaluation |
| Decision fit | Classification and JSON / Tool use | Long context |
| Context window | — | 128k |
| Cheapest output | $0.16/1M tokens | - |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Nemotron-Nano-9B-v2 has broader tracked provider coverage for fallback and procurement flexibility.
- Nemotron-Nano-9B-v2 uniquely exposes Structured outputs in local model data.
- Local decision data tags Nemotron-Nano-9B-v2 for Classification and JSON / Tool use.
- Stockmark 2 100B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Stockmark 2 100B Instruct for Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Nemotron-Nano-9B-v2
$72.00
Cheapest tracked route/tier: OpenRouter
Stockmark 2 100B Instruct
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Structured outputs before moving production traffic.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Nemotron-Nano-9B-v2 adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-18 | 2025-06-01 |
| Context window | — | 128k |
| Parameters | 9B | 100B |
| Architecture | decoder only | decoder only |
| License | Llama 3 Community | Open Weights |
| Openness | Open weights | Open weights |
| Commercial use | Commercial use with conditions | - |
| Knowledge cutoff | 2025-03 | - |
Pricing and availability
| Pricing attribute | Nemotron-Nano-9B-v2 | Stockmark 2 100B Instruct |
|---|---|---|
| Input price | $0.04/1M tokens | - |
| Output price | $0.16/1M tokens | - |
| Providers |
Capabilities
| Capability | Nemotron-Nano-9B-v2 | Stockmark 2 100B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | 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 differs most on structured outputs: Nemotron-Nano-9B-v2. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
Pricing coverage is uneven: Nemotron-Nano-9B-v2 has $0.04/1M input tokens and Stockmark 2 100B Instruct has no token price sourced yet. Provider availability is 3 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Nemotron-Nano-9B-v2 when provider fit and broader provider choice are central to the workload. Choose Stockmark 2 100B Instruct 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
Is Nemotron-Nano-9B-v2 or Stockmark 2 100B Instruct open source?
Nemotron-Nano-9B-v2 is listed under Llama 3 Community. Stockmark 2 100B Instruct is listed under Open Weights. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for structured outputs, Nemotron-Nano-9B-v2 or Stockmark 2 100B Instruct?
Nemotron-Nano-9B-v2 has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Nemotron-Nano-9B-v2 and Stockmark 2 100B Instruct?
Nemotron-Nano-9B-v2 is available on NVIDIA NIM, OpenRouter, and Vercel AI Gateway. Stockmark 2 100B Instruct is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Nemotron-Nano-9B-v2 over Stockmark 2 100B Instruct?
Nemotron-Nano-9B-v2 is safer overall; choose Stockmark 2 100B Instruct when provider fit matters. If your workload also depends on provider fit, start with Nemotron-Nano-9B-v2; if it depends on provider fit, run the same evaluation with Stockmark 2 100B Instruct.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.