LLM ReferenceLLM Reference

Together AI - Gemma 3n-e4B vs Nemotron 3 Nano

Together AI - Gemma 3n-e4B (2026) and Nemotron 3 Nano (2025) are compact production models from Google DeepMind and NVIDIA AI. Together AI - Gemma 3n-e4B ships a 8K-token context window, while Nemotron 3 Nano ships a 256K-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.

Nemotron 3 Nano fits 31x more tokens; pick it for long-context work and Together AI - Gemma 3n-e4B for tighter calls.

Decision scorecard

Local evidence first
SignalTogether AI - Gemma 3n-e4BNemotron 3 Nano
Decision fitAgents, Classification, and JSON / Tool useRAG, Agents, and Long context
Context window8K256K
Cheapest output$0.04/1M tokens-
Provider routes1 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Together AI - Gemma 3n-e4B when...
  • Together AI - Gemma 3n-e4B uniquely exposes Structured outputs in local model data.
  • Local decision data tags Together AI - Gemma 3n-e4B for Agents, Classification, and JSON / Tool use.
Choose Nemotron 3 Nano when...
  • Nemotron 3 Nano has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Nemotron 3 Nano for RAG, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Together AI - Gemma 3n-e4B

$26.00

Cheapest tracked route: Together AI

Nemotron 3 Nano

Unavailable

No complete token price in local provider data

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Together AI - Gemma 3n-e4B -> Nemotron 3 Nano
  • No overlapping tracked provider route is sourced for Together AI - Gemma 3n-e4B and Nemotron 3 Nano; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Structured outputs before moving production traffic.
Nemotron 3 Nano -> Together AI - Gemma 3n-e4B
  • No overlapping tracked provider route is sourced for Nemotron 3 Nano and Together AI - Gemma 3n-e4B; plan for SDK, billing, or endpoint changes.
  • Together AI - Gemma 3n-e4B adds Structured outputs in local capability data.

Specs

Specification
Released2026-03-152025-12-15
Context window8K256K
Parameters4B3.97B
Architecturedecoder onlymixture of experts
LicenseOpen SourceApache 2.0
Knowledge cutoff--

Pricing and availability

Pricing attributeTogether AI - Gemma 3n-e4BNemotron 3 Nano
Input price$0.02/1M tokens-
Output price$0.04/1M tokens-
Providers

Capabilities

CapabilityTogether AI - Gemma 3n-e4BNemotron 3 Nano
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingYesYes
Tool useYesYes
Structured outputsYesNo
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on structured outputs: Together AI - Gemma 3n-e4B. Both models share function calling and tool use, 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 Nemotron 3 Nano 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 Nemotron 3 Nano when long-context analysis and larger context windows 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, Together AI - Gemma 3n-e4B or Nemotron 3 Nano?

Nemotron 3 Nano supports 256K tokens, while Together AI - Gemma 3n-e4B supports 8K 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 Nemotron 3 Nano open source?

Together AI - Gemma 3n-e4B is listed under Open Source. Nemotron 3 Nano 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 Nemotron 3 Nano?

Both Together AI - Gemma 3n-e4B and Nemotron 3 Nano expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for tool use, Together AI - Gemma 3n-e4B or Nemotron 3 Nano?

Both Together AI - Gemma 3n-e4B and Nemotron 3 Nano expose tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Which is better for structured outputs, Together AI - Gemma 3n-e4B or Nemotron 3 Nano?

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 Nemotron 3 Nano?

Together AI - Gemma 3n-e4B is available on Together AI. Nemotron 3 Nano is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.