Together AI - Gemma 3n-e4B vs Nemotron-Nano-12B-v2-VL
Together AI - Gemma 3n-e4B (2026) and Nemotron-Nano-12B-v2-VL (2025) are compact production models from Google DeepMind and NVIDIA AI. Together AI - Gemma 3n-e4B ships a 8k-token context window, while Nemotron-Nano-12B-v2-VL ships a not-yet-sourced context window. On pricing, Together AI - Gemma 3n-e4B costs $0.02/1M input tokens versus $0.20/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Together AI - Gemma 3n-e4B is ~900% cheaper at $0.02/1M; pay for Nemotron-Nano-12B-v2-VL only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | Together AI - Gemma 3n-e4B | Nemotron-Nano-12B-v2-VL |
|---|---|---|
| Best for | tool-calling agents | multimodal apps and provider-routed production |
| Decision fit | Agents, Classification, and JSON / Tool use | Vision and JSON / Tool use |
| Context window | 8k | — |
| Cheapest output | $0.04/1M tokens | $0.60/1M tokens |
| Provider routes | 1 tracked | 3 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 has the lower cheapest tracked output price at $0.04/1M tokens.
- Together AI - Gemma 3n-e4B uniquely exposes JSON / Tool use in local model data.
- Local decision data tags Together AI - Gemma 3n-e4B for Agents, Classification, and JSON / Tool use.
- Nemotron-Nano-12B-v2-VL has broader tracked provider coverage for fallback and route flexibility.
- Nemotron-Nano-12B-v2-VL uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Nemotron-Nano-12B-v2-VL for Vision and JSON / Tool use.
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
Nemotron-Nano-12B-v2-VL
$310
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $284. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Together AI - Gemma 3n-e4B and Nemotron-Nano-12B-v2-VL; plan for SDK, billing, or endpoint changes.
- Nemotron-Nano-12B-v2-VL is $0.56/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for JSON / Tool use before moving production traffic.
- Nemotron-Nano-12B-v2-VL adds Vision and Multimodal in local capability data.
- No overlapping tracked provider route is sourced for Nemotron-Nano-12B-v2-VL and Together AI - Gemma 3n-e4B; plan for SDK, billing, or endpoint changes.
- Together AI - Gemma 3n-e4B is $0.56/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- Together AI - Gemma 3n-e4B adds JSON / Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2025-10-28 |
| Context window | 8k | — |
| Parameters | 4B | 12B |
| Architecture | Decoder Only | Decoder Only |
| License | Gemma | Llama 3 Community |
| Openness | Open weights | Open weights |
| Weights | Unknown | Available |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: conditional |
| Knowledge cutoff | 2024-06 | - |
Pricing and availability
| Pricing attribute | Together AI - Gemma 3n-e4B | Nemotron-Nano-12B-v2-VL |
|---|---|---|
| Input price | $0.02/1M tokens | $0.20/1M tokens |
| Output price | $0.04/1M tokens | $0.60/1M tokens |
| Providers |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | Nemotron-Nano-12B-v2-VL |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| JSON / Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| 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.
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Last reviewed: 2026-06-29. Data sourced from public model cards and provider documentation.