Together AI - Gemma 3n-e4B vs Llama 3.1 405B Instruct
Together AI - Gemma 3n-e4B (2026) and Llama 3.1 405B Instruct (2024) are compact production models from Google DeepMind and AI at Meta. Together AI - Gemma 3n-e4B ships a 8K-token context window, while Llama 3.1 405B Instruct ships a 128K-token context window. On pricing, Together AI - Gemma 3n-e4B costs $0.02/1M input tokens versus $2.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Together AI - Gemma 3n-e4B is ~11900% cheaper at $0.02/1M; pay for Llama 3.1 405B Instruct only for long-context analysis.
Decision scorecard
Local evidence first| Signal | Together AI - Gemma 3n-e4B | Llama 3.1 405B Instruct |
|---|---|---|
| Decision fit | Agents, Classification, and JSON / Tool use | RAG, Long context, and Classification |
| Context window | 8K | 128K |
| Cheapest output | $0.04/1M tokens | $2.4/1M tokens |
| Provider routes | 1 tracked | 11 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Together AI - Gemma 3n-e4B has the lower cheapest tracked output price at $0.04/1M tokens.
- Together AI - Gemma 3n-e4B uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Together AI - Gemma 3n-e4B for Agents, Classification, and JSON / Tool use.
- Llama 3.1 405B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.
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
Llama 3.1 405B Instruct
$2,520
Cheapest tracked route: AWS Bedrock
Estimated monthly gap: $2,494. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Llama 3.1 405B Instruct is $2.36/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Together AI - Gemma 3n-e4B is $2.36/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Together AI - Gemma 3n-e4B adds Function calling and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2024-07-23 |
| Context window | 8K | 128K |
| Parameters | 4B | 405B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Together AI - Gemma 3n-e4B | Llama 3.1 405B Instruct |
|---|---|---|
| Input price | $0.02/1M tokens | $2.4/1M tokens |
| Output price | $0.04/1M tokens | $2.4/1M tokens |
| Providers |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | Llama 3.1 405B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | 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 and tool use: Together AI - Gemma 3n-e4B. Both models share structured outputs, 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.
For cost, Together AI - Gemma 3n-e4B lists $0.02/1M input and $0.04/1M output tokens, while Llama 3.1 405B Instruct lists $2.4/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Together AI - Gemma 3n-e4B lower by about $2.37 per million blended tokens. Availability is 1 providers versus 11, so concentration risk also matters.
Choose Together AI - Gemma 3n-e4B when provider fit and lower input-token cost are central to the workload. Choose Llama 3.1 405B Instruct 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.
FAQ
Which has a larger context window, Together AI - Gemma 3n-e4B or Llama 3.1 405B Instruct?
Llama 3.1 405B Instruct supports 128K 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.
Which is cheaper, Together AI - Gemma 3n-e4B or Llama 3.1 405B Instruct?
Together AI - Gemma 3n-e4B is cheaper on tracked token pricing. Together AI - Gemma 3n-e4B costs $0.02/1M input and $0.04/1M output tokens. Llama 3.1 405B Instruct costs $2.4/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Together AI - Gemma 3n-e4B or Llama 3.1 405B Instruct open source?
Together AI - Gemma 3n-e4B is listed under Open Source. Llama 3.1 405B Instruct is listed under Open Source. 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 Llama 3.1 405B Instruct?
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 Llama 3.1 405B Instruct?
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.
Where can I run Together AI - Gemma 3n-e4B and Llama 3.1 405B Instruct?
Together AI - Gemma 3n-e4B is available on Together AI. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.