Together AI - Gemma 3n-e4B vs Marin 32B Base
Together AI - Gemma 3n-e4B (2026) and Marin 32B Base (2025) are compact production models from Google DeepMind and Marin. Together AI - Gemma 3n-e4B 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.
Together AI - Gemma 3n-e4B is safer overall; choose Marin 32B Base when provider fit matters.
Decision scorecard
Local evidence first| Signal | Together AI - Gemma 3n-e4B | Marin 32B Base |
|---|---|---|
| Best for | tool-calling agents | general production evaluation |
| Decision fit | Agents, Classification, and JSON / Tool use | General |
| Context window | 8k | 4k |
| Cheapest output | $0.04/1M tokens | - |
| Provider routes | 1 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Together AI - Gemma 3n-e4B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Together AI - Gemma 3n-e4B has broader tracked provider coverage for fallback and procurement flexibility.
- Together AI - Gemma 3n-e4B uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
- Local decision data tags Together AI - Gemma 3n-e4B for Agents, Classification, and JSON / Tool use.
- 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.
Together AI - Gemma 3n-e4B
$26.00
Cheapest tracked route/tier: Together AI
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 Together AI - Gemma 3n-e4B and Marin 32B Base; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Marin 32B Base and Together AI - Gemma 3n-e4B; plan for SDK, billing, or endpoint changes.
- Together AI - Gemma 3n-e4B adds Function calling, Tool use, and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2025-10-25 |
| Context window | 8k | 4k |
| Parameters | 4B | 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 | Together AI - Gemma 3n-e4B | Marin 32B Base |
|---|---|---|
| Input price | $0.02/1M tokens | - |
| Output price | $0.04/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | Marin 32B Base |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | 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 function calling: Together AI - Gemma 3n-e4B, tool use: Together AI - Gemma 3n-e4B, and structured outputs: Together AI - Gemma 3n-e4B. 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: Together AI - Gemma 3n-e4B has $0.02/1M input tokens 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 Together AI - Gemma 3n-e4B 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.
FAQ
Which has a larger context window, Together AI - Gemma 3n-e4B or Marin 32B Base?
Together AI - Gemma 3n-e4B 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 Together AI - Gemma 3n-e4B or Marin 32B Base open source?
Together AI - Gemma 3n-e4B 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.
Which is better for function calling, Together AI - Gemma 3n-e4B or Marin 32B Base?
Together AI - Gemma 3n-e4B has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, Together AI - Gemma 3n-e4B or Marin 32B Base?
Together AI - Gemma 3n-e4B has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for structured outputs, Together AI - Gemma 3n-e4B or Marin 32B Base?
Together AI - Gemma 3n-e4B 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 Together AI - Gemma 3n-e4B and Marin 32B Base?
Together AI - Gemma 3n-e4B is available on Together AI. Marin 32B Base is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.