LLM Reference

Mistral Small 4 vs ShieldGemma 9B

Mistral Small 4 (2026) and ShieldGemma 9B (2024) are compact production models from MistralAI and Google DeepMind. Mistral Small 4 ships a 256K-token context window, while ShieldGemma 9B ships a 8K-token context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Mistral Small 4 fits 32x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls.

Decision scorecard

Local evidence first
SignalMistral Small 4ShieldGemma 9B
Decision fitRAG, Agents, and Long contextClassification
Context window256K8K
Cheapest output$0.6/1M tokens-
Provider routes3 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Mistral Small 4 when...
  • Mistral Small 4 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Mistral Small 4 has broader tracked provider coverage for fallback and procurement flexibility.
  • Mistral Small 4 uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags Mistral Small 4 for RAG, Agents, and Long context.
Choose ShieldGemma 9B when...
  • Local decision data tags ShieldGemma 9B for Classification.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Mistral Small 4

$270

Cheapest tracked route: OpenRouter

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

Mistral Small 4 -> ShieldGemma 9B
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
ShieldGemma 9B -> Mistral Small 4
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • Mistral Small 4 adds Vision, Multimodal, and Function calling in local capability data.

Specs

Specification
Released2026-03-162024-07-01
Context window256K8K
Parameters119B (6.5B active)9B
Architecturemoedecoder only
LicenseApache 2.01
Knowledge cutoff2025-06-

Pricing and availability

Pricing attributeMistral Small 4ShieldGemma 9B
Input price$0.15/1M tokens-
Output price$0.6/1M tokens-
Providers

Capabilities

CapabilityMistral Small 4ShieldGemma 9B
VisionYesNo
MultimodalYesNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsNoNo
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Mistral Small 4, multimodal input: Mistral Small 4, function calling: Mistral Small 4, and tool use: Mistral Small 4. 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: Mistral Small 4 has $0.15/1M input tokens and ShieldGemma 9B has no token price sourced yet. Provider availability is 3 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Mistral Small 4 when long-context analysis, larger context windows, and broader provider choice 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.

FAQ

Which has a larger context window, Mistral Small 4 or ShieldGemma 9B?

Mistral Small 4 supports 256K 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 Mistral Small 4 or ShieldGemma 9B open source?

Mistral Small 4 is listed under Apache 2.0. ShieldGemma 9B is listed under 1. 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 vision, Mistral Small 4 or ShieldGemma 9B?

Mistral Small 4 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for multimodal input, Mistral Small 4 or ShieldGemma 9B?

Mistral Small 4 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for function calling, Mistral Small 4 or ShieldGemma 9B?

Mistral Small 4 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Mistral Small 4 and ShieldGemma 9B?

Mistral Small 4 is available on OpenRouter, NVIDIA NIM, and Mistral AI Studio. ShieldGemma 9B is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.