LLM Reference

Gemini Deep Research vs Llama 3.2 11B Instruct

Gemini Deep Research (2024) and Llama 3.2 11B Instruct (2025) are compact production models from Google DeepMind and AI at Meta. Gemini Deep Research ships a 128k-token context window, while Llama 3.2 11B Instruct ships a 128k-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 3.2 11B Instruct is safer overall; choose Gemini Deep Research when provider fit matters.

Decision scorecard

Local evidence first
SignalGemini Deep ResearchLlama 3.2 11B Instruct
Best fortool-calling agentsmultimodal apps
Decision fitRAG, Agents, and Long contextRAG, Long context, and Vision
Context window128k128k
Cheapest output-$0.27/1M tokens
Provider routes1 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Gemini Deep Research when...
  • Gemini Deep Research uniquely exposes Function calling and Tool use in local model data.
  • Local decision data tags Gemini Deep Research for RAG, Agents, and Long context.
Choose Llama 3.2 11B Instruct when...
  • Llama 3.2 11B Instruct uniquely exposes Vision and Multimodal in local model data.
  • Local decision data tags Llama 3.2 11B Instruct for RAG, Long context, and Vision.

Monthly cost at traffic

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

Gemini Deep Research

Unavailable

No complete token price in local provider data

Llama 3.2 11B Instruct

$228

Cheapest tracked route/tier: AWS Bedrock

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

Switch friction

Gemini Deep Research -> Llama 3.2 11B Instruct
  • No overlapping tracked provider route is sourced for Gemini Deep Research and Llama 3.2 11B Instruct; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Function calling and Tool use before moving production traffic.
  • Llama 3.2 11B Instruct adds Vision and Multimodal in local capability data.
Llama 3.2 11B Instruct -> Gemini Deep Research
  • No overlapping tracked provider route is sourced for Llama 3.2 11B Instruct and Gemini Deep Research; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision and Multimodal before moving production traffic.
  • Gemini Deep Research adds Function calling and Tool use in local capability data.

Specs

Specification
Released2024-12-112025-09-01
Context window128k128k
Parameters11B
Architecturedecoder only-
LicenseProprietaryLlama 3 Community
OpennessProprietaryOpen weights
Commercial useCommercial use with conditionsCommercial use with conditions
Knowledge cutoff2025-012023-12

Pricing and availability

Pricing attributeGemini Deep ResearchLlama 3.2 11B Instruct
Input price-$0.20/1M tokens
Output price-$0.27/1M tokens
Providers

Capabilities

CapabilityGemini Deep ResearchLlama 3.2 11B Instruct
VisionNoYes
MultimodalNoYes
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Llama 3.2 11B Instruct, multimodal input: Llama 3.2 11B Instruct, function calling: Gemini Deep Research, and tool use: Gemini Deep Research. Both models share structured outputs, 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: Gemini Deep Research has no token price sourced yet and Llama 3.2 11B Instruct has $0.20/1M input tokens. 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 Gemini Deep Research when provider fit are central to the workload. Choose Llama 3.2 11B Instruct when vision-heavy evaluation 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, Gemini Deep Research or Llama 3.2 11B Instruct?

Gemini Deep Research supports 128k tokens, while Llama 3.2 11B Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Gemini Deep Research or Llama 3.2 11B Instruct open source?

Gemini Deep Research is listed under Proprietary. Llama 3.2 11B Instruct is listed under Llama 3 Community. 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, Gemini Deep Research or Llama 3.2 11B Instruct?

Llama 3.2 11B Instruct 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, Gemini Deep Research or Llama 3.2 11B Instruct?

Llama 3.2 11B Instruct 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, Gemini Deep Research or Llama 3.2 11B Instruct?

Gemini Deep Research 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 Gemini Deep Research and Llama 3.2 11B Instruct?

Gemini Deep Research is available on Google AI Studio. Llama 3.2 11B Instruct is available on AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.