LLM Reference

Gemini 1.5 Pro 002 vs ShieldGemma 9B

Gemini 1.5 Pro 002 (2024) and ShieldGemma 9B (2024) are compact production models from Google DeepMind. Gemini 1.5 Pro 002 ships a 2m-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.

Gemini 1.5 Pro 002 fits 250x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls.

Decision scorecard

Local evidence first
SignalGemini 1.5 Pro 002ShieldGemma 9B
Best forlong-context analysisgeneral production evaluation
Decision fitLong contextClassification
Context window2m8k
Cheapest output--
Provider routes0 tracked1 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose Gemini 1.5 Pro 002 when...
  • Gemini 1.5 Pro 002 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Gemini 1.5 Pro 002 for Long context.
Choose ShieldGemma 9B when...
  • ShieldGemma 9B has broader tracked provider coverage for fallback and procurement flexibility.
  • 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.

Gemini 1.5 Pro 002

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

Gemini 1.5 Pro 002 -> ShieldGemma 9B
  • No overlapping tracked provider route is sourced for Gemini 1.5 Pro 002 and ShieldGemma 9B; plan for SDK, billing, or endpoint changes.
ShieldGemma 9B -> Gemini 1.5 Pro 002
  • No overlapping tracked provider route is sourced for ShieldGemma 9B and Gemini 1.5 Pro 002; plan for SDK, billing, or endpoint changes.

Specs

Specification
Released2024-09-242024-07-01
Context window2m8k
Parameters9B
ArchitectureDecoder OnlyDecoder Only
LicenseProprietaryGemma
OpennessProprietaryOpen weights
Commercial useCommercial use: conditionalCommercial use: conditional
Knowledge cutoff2024-08-

Pricing and availability

Pricing attributeGemini 1.5 Pro 002ShieldGemma 9B
Input price--
Output price--
Providers-

Pricing not yet sourced for either model.

Capabilities

CapabilityGemini 1.5 Pro 002ShieldGemma 9B
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint is close: both models cover the core production surface. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

Pricing coverage is uneven: Gemini 1.5 Pro 002 has no token price sourced yet and ShieldGemma 9B has no token price sourced yet. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Gemini 1.5 Pro 002 when long-context analysis and larger context windows are central to the workload. Choose ShieldGemma 9B when provider fit and broader provider choice 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, Gemini 1.5 Pro 002 or ShieldGemma 9B?

Gemini 1.5 Pro 002 supports 2m 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 Gemini 1.5 Pro 002 or ShieldGemma 9B open source?

Gemini 1.5 Pro 002 is listed under Proprietary. 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.

Where can I run Gemini 1.5 Pro 002 and ShieldGemma 9B?

Gemini 1.5 Pro 002 is available on the tracked providers still being sourced. ShieldGemma 9B is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Gemini 1.5 Pro 002 over ShieldGemma 9B?

Gemini 1.5 Pro 002 fits 250x more tokens; pick it for long-context work and ShieldGemma 9B for tighter calls. If your workload also depends on long-context analysis, start with Gemini 1.5 Pro 002; if it depends on provider fit, run the same evaluation with ShieldGemma 9B.

Continue comparing

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