Gemma 2 9B SahabatAI Instruct vs Llama Guard 4 12B
Gemma 2 9B SahabatAI Instruct (2025) and Llama Guard 4 12B (2025) are compact production models from GoToCompany and AI at Meta. Gemma 2 9B SahabatAI Instruct ships a 8k-token context window, while Llama Guard 4 12B ships a 164k-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.
Llama Guard 4 12B fits 21x more tokens; pick it for long-context work and Gemma 2 9B SahabatAI Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemma 2 9B SahabatAI Instruct | Llama Guard 4 12B |
|---|---|---|
| Best for | general production evaluation | provider-routed production |
| Decision fit | General | RAG, Long context, and Classification |
| Context window | 8k | 164k |
| Cheapest output | - | $0.18/1M tokens |
| Provider routes | 1 tracked | 3 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- Use Gemma 2 9B SahabatAI Instruct when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
- Llama Guard 4 12B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama Guard 4 12B has broader tracked provider coverage for fallback and route flexibility.
- Llama Guard 4 12B uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama Guard 4 12B for RAG, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemma 2 9B SahabatAI Instruct
Unavailable
No complete token price in local provider data
Llama Guard 4 12B
$189
Cheapest tracked route/tier: OpenRouter
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.
- Llama Guard 4 12B adds Structured outputs in local capability data.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Structured outputs before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-01 | 2025-04-05 |
| Context window | 8k | 164k |
| Parameters | 9B | 12B |
| Architecture | Decoder Only | Decoder Only |
| License | Open Weights | Llama 2 Community |
| Openness | Open weights | Open weights |
| Weights | Unknown | Unknown |
| Code | Unknown | Unknown |
| Commercial use | - | Commercial use: conditional |
| Knowledge cutoff | - | 2024-08 |
Pricing and availability
| Pricing attribute | Gemma 2 9B SahabatAI Instruct | Llama Guard 4 12B |
|---|---|---|
| Input price | - | $0.18/1M tokens |
| Output price | - | $0.18/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 2 9B SahabatAI Instruct | Llama Guard 4 12B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| JSON / Tool use | No | No |
| Structured outputs | No | 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.
Continue comparing
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Last reviewed: 2026-07-09. Data sourced from public model cards and provider documentation.