LLM Reference

Nano Banana Pro (Gemini 3 Pro Image Preview) vs Gemma 2 9B SahabatAI Instruct

Nano Banana Pro (Gemini 3 Pro Image Preview) (2025) and Gemma 2 9B SahabatAI Instruct (2025) are compact production models from Google DeepMind. Nano Banana Pro (Gemini 3 Pro Image Preview) ships a 66k-token context window, while Gemma 2 9B SahabatAI Instruct 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.

Nano Banana Pro (Gemini 3 Pro Image Preview) fits 8x more tokens; pick it for long-context work and Gemma 2 9B SahabatAI Instruct for tighter calls.

Decision scorecard

Local evidence first
SignalNano Banana Pro (Gemini 3 Pro Image Preview)Gemma 2 9B SahabatAI Instruct
Best forprovider-routed productiongeneral production evaluation
Decision fitGeneralGeneral
Context window66k8k
Cheapest output$120/1M tokens-
Provider routes3 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Nano Banana Pro (Gemini 3 Pro Image Preview) when...
  • Nano Banana Pro (Gemini 3 Pro Image Preview) has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Nano Banana Pro (Gemini 3 Pro Image Preview) has broader tracked provider coverage for fallback and procurement flexibility.
Choose Gemma 2 9B SahabatAI Instruct when...
  • 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.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Nano Banana Pro (Gemini 3 Pro Image Preview)

$31,600

Cheapest tracked route/tier: Google AI Studio

Gemma 2 9B SahabatAI Instruct

Unavailable

No complete token price in local provider data

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Nano Banana Pro (Gemini 3 Pro Image Preview) -> Gemma 2 9B SahabatAI Instruct
  • No overlapping tracked provider route is sourced for Nano Banana Pro (Gemini 3 Pro Image Preview) and Gemma 2 9B SahabatAI Instruct; plan for SDK, billing, or endpoint changes.
Gemma 2 9B SahabatAI Instruct -> Nano Banana Pro (Gemini 3 Pro Image Preview)
  • No overlapping tracked provider route is sourced for Gemma 2 9B SahabatAI Instruct and Nano Banana Pro (Gemini 3 Pro Image Preview); plan for SDK, billing, or endpoint changes.

Specs

Specification
Released2025-09-012025-01-01
Context window66k8k
Parameters9B
Architecturedecoder onlydecoder only
LicenseProprietaryGemma
OpennessProprietaryOpen weights
Commercial useCommercial use with conditionsCommercial use with conditions
Knowledge cutoff--

Pricing and availability

Pricing attributeNano Banana Pro (Gemini 3 Pro Image Preview)Gemma 2 9B SahabatAI Instruct
Input price$2/1M tokens-
Output price$120/1M tokens-
Providers

Capabilities

CapabilityNano Banana Pro (Gemini 3 Pro Image Preview)Gemma 2 9B SahabatAI Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced 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: Nano Banana Pro (Gemini 3 Pro Image Preview) has $2/1M input tokens and Gemma 2 9B SahabatAI Instruct 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 Nano Banana Pro (Gemini 3 Pro Image Preview) when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Gemma 2 9B SahabatAI Instruct 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, Nano Banana Pro (Gemini 3 Pro Image Preview) or Gemma 2 9B SahabatAI Instruct?

Nano Banana Pro (Gemini 3 Pro Image Preview) supports 66k tokens, while Gemma 2 9B SahabatAI Instruct supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Nano Banana Pro (Gemini 3 Pro Image Preview) or Gemma 2 9B SahabatAI Instruct open source?

Nano Banana Pro (Gemini 3 Pro Image Preview) is listed under Proprietary. Gemma 2 9B SahabatAI Instruct 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 Nano Banana Pro (Gemini 3 Pro Image Preview) and Gemma 2 9B SahabatAI Instruct?

Nano Banana Pro (Gemini 3 Pro Image Preview) is available on Google AI Studio, GCP Vertex AI, and OpenRouter. Gemma 2 9B SahabatAI Instruct is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Nano Banana Pro (Gemini 3 Pro Image Preview) over Gemma 2 9B SahabatAI Instruct?

Nano Banana Pro (Gemini 3 Pro Image Preview) fits 8x more tokens; pick it for long-context work and Gemma 2 9B SahabatAI Instruct for tighter calls. If your workload also depends on long-context analysis, start with Nano Banana Pro (Gemini 3 Pro Image Preview); if it depends on provider fit, run the same evaluation with Gemma 2 9B SahabatAI Instruct.

Continue comparing

Last reviewed: 2026-05-31. Data sourced from public model cards and provider documentation.