Sarvam-M Multilingual Hybrid vs ShieldGemma 9B
Sarvam-M Multilingual Hybrid (2025) and ShieldGemma 9B (2024) are compact production models from Sarvam.ai and Google DeepMind. Sarvam-M Multilingual Hybrid ships a 128k-token context window, while ShieldGemma 9B ships a 8k-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. It focuses on practical selection signals rather than broad model-family marketing.
Sarvam-M Multilingual Hybrid fits 16x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls.
Decision scorecard
Local evidence first| Signal | Sarvam-M Multilingual Hybrid | ShieldGemma 9B |
|---|---|---|
| Best for | general production evaluation | general production evaluation |
| Decision fit | Long context | Classification |
| Context window | 128k | 8k |
| Cheapest output | - | - |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- 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.
- Local decision data tags ShieldGemma 9B for Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Sarvam-M Multilingual Hybrid
Unavailable
No complete token price in local provider data
ShieldGemma 9B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-01 | 2024-07-01 |
| Context window | 128k | 8k |
| Parameters | 24B | 9B |
| Architecture | Decoder Only | Decoder Only |
| License | Apache 2.0OSI-approved | Gemma |
| Openness | Open source | Open weights |
| Weights | Not released | Unknown |
| Code | Unknown | Unknown |
| Commercial use | Commercial use: permitted | Commercial use: conditional |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Sarvam-M Multilingual Hybrid | ShieldGemma 9B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers |
Pricing not yet sourced for either model.
Capabilities
| Capability | Sarvam-M Multilingual Hybrid | ShieldGemma 9B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| JSON / Tool use | No | No |
| Structured outputs | No | 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.