Together AI - Gemma 3n-e4B vs Mistral Small 3
Together AI - Gemma 3n-e4B (2026) and Mistral Small 3 (2025) are compact production models from Google DeepMind and MistralAI. Together AI - Gemma 3n-e4B ships a 8K-token context window, while Mistral Small 3 ships a 33K-token context window. On pricing, Together AI - Gemma 3n-e4B costs $0.02/1M input tokens versus $0.1/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Together AI - Gemma 3n-e4B is ~400% cheaper at $0.02/1M; pay for Mistral Small 3 only for long-context analysis.
Decision scorecard
Local evidence first| Signal | Together AI - Gemma 3n-e4B | Mistral Small 3 |
|---|---|---|
| Decision fit | Agents, Classification, and JSON / Tool use | Agents, Classification, and JSON / Tool use |
| Context window | 8K | 33K |
| Cheapest output | $0.04/1M tokens | $0.3/1M tokens |
| Provider routes | 1 tracked | 1 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.
- Local decision data tags Together AI - Gemma 3n-e4B for Agents, Classification, and JSON / Tool use.
- Mistral Small 3 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Mistral Small 3 for Agents, Classification, and JSON / Tool use.
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
Mistral Small 3
$155
Cheapest tracked route: Together AI
Estimated monthly gap: $129. 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.
- Mistral Small 3 is $0.26/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Provider overlap exists on Together AI; start route-level A/B tests there.
- Together AI - Gemma 3n-e4B is $0.26/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2025-01-01 |
| Context window | 8K | 33K |
| Parameters | 4B | — |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Together AI - Gemma 3n-e4B | Mistral Small 3 |
|---|---|---|
| Input price | $0.02/1M tokens | $0.1/1M tokens |
| Output price | $0.04/1M tokens | $0.3/1M tokens |
| Providers |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | Mistral Small 3 |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| 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 function calling, tool use, and structured outputs. 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.
For cost, Together AI - Gemma 3n-e4B lists $0.02/1M input and $0.04/1M output tokens, while Mistral Small 3 lists $0.1/1M input and $0.3/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Together AI - Gemma 3n-e4B lower by about $0.13 per million blended tokens. Availability is 1 providers versus 1, 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 Mistral Small 3 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.
FAQ
Which has a larger context window, Together AI - Gemma 3n-e4B or Mistral Small 3?
Mistral Small 3 supports 33K 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 Mistral Small 3?
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. Mistral Small 3 costs $0.1/1M input and $0.3/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Together AI - Gemma 3n-e4B or Mistral Small 3 open source?
Together AI - Gemma 3n-e4B is listed under Open Source. Mistral Small 3 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 Mistral Small 3?
Both Together AI - Gemma 3n-e4B and Mistral Small 3 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 Mistral Small 3?
Both Together AI - Gemma 3n-e4B and Mistral Small 3 expose tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Together AI - Gemma 3n-e4B and Mistral Small 3?
Together AI - Gemma 3n-e4B is available on Together AI. Mistral Small 3 is available on Together AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-14. Data sourced from public model cards and provider documentation.