Together AI - Gemma 3n-e4B vs Mistral Nemotron
Together AI - Gemma 3n-e4B (2026) and Mistral Nemotron (2025) are compact production models from Google DeepMind and MistralAI. Together AI - Gemma 3n-e4B ships a 8k-token context window, while Mistral Nemotron ships a not-yet-sourced 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.
Together AI - Gemma 3n-e4B is safer overall; choose Mistral Nemotron when provider fit matters.
Decision scorecard
Local evidence first| Signal | Together AI - Gemma 3n-e4B | Mistral Nemotron |
|---|---|---|
| Best for | tool-calling agents | general production evaluation |
| Decision fit | Agents, Classification, and JSON / Tool use | General |
| Context window | 8k | — |
| Cheapest output | $0.04/1M tokens | - |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
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 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 Mistral Nemotron 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
Mistral Nemotron
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 Mistral Nemotron; 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 Mistral Nemotron 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 | 2025-12-01 |
| Context window | 8k | — |
| Parameters | 4B | 70B |
| Architecture | Decoder Only | Decoder Only |
| License | Gemma | Proprietary |
| Openness | Open weights | Proprietary |
| Commercial use | Commercial use: conditional | - |
| Knowledge cutoff | 2024-06 | - |
Pricing and availability
| Pricing attribute | Together AI - Gemma 3n-e4B | Mistral Nemotron |
|---|---|---|
| Input price | $0.02/1M tokens | - |
| Output price | $0.04/1M tokens | - |
| Providers |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | Mistral Nemotron |
|---|---|---|
| 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 scores are currently available 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 Mistral Nemotron has no token price sourced yet. Provider availability is 1 tracked routes versus 1. 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 provider fit are central to the workload. Choose Mistral Nemotron 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
Is Together AI - Gemma 3n-e4B or Mistral Nemotron open source?
Together AI - Gemma 3n-e4B is listed under Gemma. Mistral Nemotron is listed under Proprietary. 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 Mistral Nemotron?
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 Mistral Nemotron?
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 Mistral Nemotron?
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 Mistral Nemotron?
Together AI - Gemma 3n-e4B is available on Together AI. Mistral Nemotron is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
When should I pick Together AI - Gemma 3n-e4B over Mistral Nemotron?
Together AI - Gemma 3n-e4B is safer overall; choose Mistral Nemotron when provider fit matters. If your workload also depends on provider fit, start with Together AI - Gemma 3n-e4B; if it depends on provider fit, run the same evaluation with Mistral Nemotron.
Continue comparing
Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.