Gemma 3n 2B (free) vs Marin 32B Base
Gemma 3n 2B (free) (2025) and Marin 32B Base (2025) are compact production models from Google DeepMind and Marin. Gemma 3n 2B (free) ships a 8k-token context window, while Marin 32B Base ships a 4k-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.
Marin 32B Base is safer overall; choose Gemma 3n 2B (free) when long-context analysis matters.
Decision scorecard
Local evidence first| Signal | Gemma 3n 2B (free) | Marin 32B Base |
|---|---|---|
| Best for | general production evaluation | general production evaluation |
| Decision fit | General | General |
| Context window | 8k | 4k |
| Cheapest output | - | - |
| Provider routes | 1 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 3n 2B (free) has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemma 3n 2B (free) has broader tracked provider coverage for fallback and procurement flexibility.
- Use Marin 32B Base 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.
Gemma 3n 2B (free)
Unavailable
No complete token price in local provider data
Marin 32B Base
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 Gemma 3n 2B (free) and Marin 32B Base; plan for SDK, billing, or endpoint changes.
- No overlapping tracked provider route is sourced for Marin 32B Base and Gemma 3n 2B (free); plan for SDK, billing, or endpoint changes.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-03 | 2025-10-25 |
| Context window | 8k | 4k |
| Parameters | 5B (2B effective active) | 32.5B |
| Architecture | decoder only | decoder only |
| License | Gemma | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2024-06 | 2024-07 |
Pricing and availability
| Pricing attribute | Gemma 3n 2B (free) | Marin 32B Base |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers | - |
Pricing not yet sourced for either model.
Capabilities
| Capability | Gemma 3n 2B (free) | Marin 32B Base |
|---|---|---|
| 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: Gemma 3n 2B (free) has no token price sourced yet and Marin 32B Base 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 Gemma 3n 2B (free) when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Marin 32B Base 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, Gemma 3n 2B (free) or Marin 32B Base?
Gemma 3n 2B (free) supports 8k tokens, while Marin 32B Base supports 4k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Gemma 3n 2B (free) or Marin 32B Base open source?
Gemma 3n 2B (free) is listed under Gemma. Marin 32B Base is listed under Apache 2.0. 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 Gemma 3n 2B (free) and Marin 32B Base?
Gemma 3n 2B (free) is available on NVIDIA NIM. Marin 32B Base 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 Gemma 3n 2B (free) over Marin 32B Base?
Marin 32B Base is safer overall; choose Gemma 3n 2B (free) when long-context analysis matters. If your workload also depends on long-context analysis, start with Gemma 3n 2B (free); if it depends on provider fit, run the same evaluation with Marin 32B Base.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.