Gemma 3n 2B (free) vs Mistral NeMo Instruct (2407)
Gemma 3n 2B (free) (2025) and Mistral NeMo Instruct (2407) (2024) are compact production models from Google DeepMind and MistralAI. Gemma 3n 2B (free) ships a 8K-token context window, while Mistral NeMo Instruct (2407) ships a 128K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Mistral NeMo Instruct (2407) fits 16x more tokens; pick it for long-context work and Gemma 3n 2B (free) for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemma 3n 2B (free) | Mistral NeMo Instruct (2407) |
|---|---|---|
| Decision fit | General | Coding, Long context, and Classification |
| Context window | 8K | 128K |
| Cheapest output | - | $0.04/1M tokens |
| Provider routes | 1 tracked | 7 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Use Gemma 3n 2B (free) when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
- Mistral NeMo Instruct (2407) has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Mistral NeMo Instruct (2407) has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Mistral NeMo Instruct (2407) for Coding, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Gemma 3n 2B (free)
Unavailable
No complete token price in local provider data
Mistral NeMo Instruct (2407)
$26.00
Cheapest tracked route: DeepInfra
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.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-03 | 2024-07-18 |
| Context window | 8K | 128K |
| Parameters | — | 12B |
| Architecture | decoder only | decoder only |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Gemma 3n 2B (free) | Mistral NeMo Instruct (2407) |
|---|---|---|
| Input price | - | $0.02/1M tokens |
| Output price | - | $0.04/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 3n 2B (free) | Mistral NeMo Instruct (2407) |
|---|---|---|
| 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 |
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 Mistral NeMo Instruct (2407) has $0.02/1M input tokens. Provider availability is 1 tracked routes versus 7. 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 provider fit are central to the workload. Choose Mistral NeMo Instruct (2407) when long-context analysis, larger context windows, and broader provider choice 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 Mistral NeMo Instruct (2407)?
Mistral NeMo Instruct (2407) supports 128K tokens, while Gemma 3n 2B (free) supports 8K 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 Mistral NeMo Instruct (2407) open source?
Gemma 3n 2B (free) is listed under Open Source. Mistral NeMo Instruct (2407) 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 Mistral NeMo Instruct (2407)?
Gemma 3n 2B (free) is available on NVIDIA NIM. Mistral NeMo Instruct (2407) is available on NVIDIA NIM, Microsoft Foundry, DeepInfra, Fireworks AI, and Arcee AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 3n 2B (free) over Mistral NeMo Instruct (2407)?
Mistral NeMo Instruct (2407) fits 16x more tokens; pick it for long-context work and Gemma 3n 2B (free) for tighter calls. If your workload also depends on provider fit, start with Gemma 3n 2B (free); if it depends on long-context analysis, run the same evaluation with Mistral NeMo Instruct (2407).
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.