Magistral Small 2506 vs ShieldGemma 9B
Magistral Small 2506 (2025) and ShieldGemma 9B (2024) are frontier reasoning models from MistralAI and Google DeepMind. Magistral Small 2506 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.
Magistral Small 2506 fits 16x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls.
Decision scorecard
Local evidence first| Signal | Magistral Small 2506 | ShieldGemma 9B |
|---|---|---|
| Best for | reasoning-heavy apps | general production evaluation |
| Decision fit | Long context | Classification |
| Context window | 128k | 8k |
| Cheapest output | - | - |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Magistral Small 2506 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Magistral Small 2506 uniquely exposes Reasoning in local model data.
- Local decision data tags Magistral Small 2506 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.
Magistral Small 2506
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.
- Check replacement coverage for Reasoning before moving production traffic.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Magistral Small 2506 adds Reasoning in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-06-10 | 2024-07-01 |
| Context window | 128k | 8k |
| Parameters | 24B | 9B |
| Architecture | decoder only | decoder only |
| License | Apache 2.0(OSI) | Gemma |
| Openness | Open source | Open weights |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | 2025-06 | - |
Pricing and availability
| Pricing attribute | Magistral Small 2506 | ShieldGemma 9B |
|---|---|---|
| Input price | - | - |
| Output price | - | - |
| Providers |
Pricing not yet sourced for either model.
Capabilities
| Capability | Magistral Small 2506 | ShieldGemma 9B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | No | No |
| 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 rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: Magistral Small 2506. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
Pricing coverage is uneven: Magistral Small 2506 has no token price sourced yet and ShieldGemma 9B has no token price sourced yet. Provider availability is 1 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Magistral Small 2506 when reasoning depth and larger context windows are central to the workload. Choose ShieldGemma 9B when provider fit 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Magistral Small 2506 or ShieldGemma 9B?
Magistral Small 2506 supports 128k tokens, while ShieldGemma 9B supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Magistral Small 2506 or ShieldGemma 9B open source?
Magistral Small 2506 is listed under Apache 2.0. ShieldGemma 9B is listed under Gemma. 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 reasoning mode, Magistral Small 2506 or ShieldGemma 9B?
Magistral Small 2506 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Magistral Small 2506 and ShieldGemma 9B?
Magistral Small 2506 is available on NVIDIA NIM. ShieldGemma 9B is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
When should I pick Magistral Small 2506 over ShieldGemma 9B?
Magistral Small 2506 fits 16x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls. If your workload also depends on reasoning depth, start with Magistral Small 2506; if it depends on provider fit, run the same evaluation with ShieldGemma 9B.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.