Together AI - Gemma 3n-e4B vs Sarvam-M Multilingual Hybrid
Together AI - Gemma 3n-e4B (2026) and Sarvam-M Multilingual Hybrid (2025) are compact production models from Google DeepMind and Sarvam.ai. Together AI - Gemma 3n-e4B ships a 8k-token context window, while Sarvam-M Multilingual Hybrid ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Sarvam-M Multilingual Hybrid fits 16x more tokens; pick it for long-context work and Together AI - Gemma 3n-e4B for tighter calls.
Decision scorecard
Local evidence first| Signal | Together AI - Gemma 3n-e4B | Sarvam-M Multilingual Hybrid |
|---|---|---|
| Best for | tool-calling agents | general production evaluation |
| Decision fit | Agents, Classification, and JSON / Tool use | Long context |
| Context window | 8k | 128k |
| Cheapest output | $0.04/1M tokens | - |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Together AI - Gemma 3n-e4B uniquely exposes JSON / Tool use and Structured outputs in local model data.
- Local decision data tags Together AI - Gemma 3n-e4B for Agents, Classification, and JSON / Tool use.
- Sarvam-M Multilingual Hybrid has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Sarvam-M Multilingual Hybrid for Long context.
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
Sarvam-M Multilingual Hybrid
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Together AI - Gemma 3n-e4B and Sarvam-M Multilingual Hybrid; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for JSON / Tool use and Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Sarvam-M Multilingual Hybrid and Together AI - Gemma 3n-e4B; plan for SDK, billing, or endpoint changes.
- Together AI - Gemma 3n-e4B adds JSON / Tool use and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2025-06-01 |
| Context window | 8k | 128k |
| Parameters | 4B | 24B |
| Architecture | Decoder Only | Decoder Only |
| License | Gemma | Apache 2.0OSI-approved |
| Openness | Open weights | Open source |
| Weights | Unknown | Not released |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2024-06 | - |
Pricing and availability
| Pricing attribute | Together AI - Gemma 3n-e4B | Sarvam-M Multilingual Hybrid |
|---|---|---|
| Input price | $0.02/1M tokens | - |
| Output price | $0.04/1M tokens | - |
| Providers |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | Sarvam-M Multilingual Hybrid |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| JSON / Tool use | Yes | No |
| Structured outputs | Yes | No |
| 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: 2026-09-08. Data sourced from public model cards and provider documentation.