LLM Reference

Gemini Deep Research vs GPT-4o Search Preview

Gemini Deep Research (2024) and GPT-4o Search Preview (2025) are compact production models from Google DeepMind and OpenAI. Gemini Deep Research ships a 128k-token context window, while GPT-4o Search Preview 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. It focuses on practical selection signals rather than broad model-family marketing.

GPT-4o Search Preview is safer overall; choose Gemini Deep Research when provider fit matters.

Decision scorecard

Local evidence first
SignalGemini Deep ResearchGPT-4o Search Preview
Best fortool-calling agentsgeneral production evaluation
Decision fitRAG, Agents, and Long contextRAG, Long context, and Classification
Context window128k128k
Cheapest output-$10/1M tokens
Provider routes1 tracked1 tracked
Shared benchmarks0 shared0 shared

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 GPT-4o Search Preview when...
  • Local decision data tags GPT-4o Search Preview for RAG, Long context, and Classification.

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

GPT-4o Search Preview

$4,500

Cheapest tracked route/tier: OpenRouter

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

Switch friction

Gemini Deep Research -> GPT-4o Search Preview
  • No overlapping tracked provider route is sourced for Gemini Deep Research and GPT-4o Search Preview; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Function calling and Tool use before moving production traffic.
GPT-4o Search Preview -> Gemini Deep Research
  • No overlapping tracked provider route is sourced for GPT-4o Search Preview and Gemini Deep Research; plan for SDK, billing, or endpoint changes.
  • Gemini Deep Research adds Function calling and Tool use in local capability data.

Specs

Specification
Released2024-12-112025-02-26
Context window128k128k
Parameters
ArchitectureDecoder OnlyDecoder Only
LicenseProprietaryProprietary
OpennessProprietaryProprietary
Commercial useCommercial use: conditionalCommercial use: conditional
Knowledge cutoff2025-012023-10

Pricing and availability

Pricing attributeGemini Deep ResearchGPT-4o Search Preview
Input price-$2.50/1M tokens
Output price-$10/1M tokens
Providers

Capabilities

CapabilityGemini Deep ResearchGPT-4o Search Preview
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on 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 GPT-4o Search Preview has $2.50/1M 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 GPT-4o Search Preview 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, Gemini Deep Research or GPT-4o Search Preview?

Gemini Deep Research supports 128k tokens, while GPT-4o Search Preview 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 GPT-4o Search Preview open source?

Gemini Deep Research is listed under Proprietary. GPT-4o Search Preview is listed under Proprietary. 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 function calling, Gemini Deep Research or GPT-4o Search Preview?

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.

Which is better for tool use, Gemini Deep Research or GPT-4o Search Preview?

Gemini Deep Research has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, Gemini Deep Research or GPT-4o Search Preview?

Both Gemini Deep Research and GPT-4o Search Preview expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run Gemini Deep Research and GPT-4o Search Preview?

Gemini Deep Research is available on Google AI Studio. GPT-4o Search Preview is available on OpenRouter. 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.

Continue comparing

Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.