Gemini Deep Research Preview
Gemini Deep Research Preview is worth evaluating for rag, agents, and long context when its provider route and context window match the workload.
Use it for
- Teams evaluating rag, agents, and long context
- Workloads that can use a 1m context window
- Buyers comparing 1 tracked provider route
Do not use it for
- Workloads where another current model has stronger sourced task evidence
- Family
- Gemini 3.1
- Released
- 2026-04-21
- Context
- 1m
- Max output
- 65,536
- Architecture
- Decoder Only
- Knowledge cutoff
- 2025-01
- Specialization
- general
- Openness
- Proprietary
- License
- ProprietaryCommercial use with conditions
- Training
- Pretrained
Cheapest of 1 route · Google AI Studio
About
Google's agentic deep research model built on Gemini 3.1 Pro, released April 21, 2026. Designed for speed and efficiency in autonomous multi-step research: ingests text, images, PDFs, audio, and video to produce comprehensive cited reports from public web sources and private workspace data. Supports collaborative planning, visualization, MCP servers, and File Search. Context window: 1M tokens; max output: 65,536 tokens. Runs at Gemini 3.1 Pro rates ($2.00/$12.00 per MTok). API ID: deep-research-preview-04-2026.
Gemini Deep Research Preview is a proprietary model in the Gemini 3.1 family. The structured metadata tracks a 1m-token context window, multimodal input, audio, function calling, tool use, and structured outputs. This page tracks provider routes through Google AI Studio, with the cheapest tracked route listed at $2 input and $12 output per 1M tokens. No headline benchmark score is tracked for Gemini Deep Research Preview yet.
Top use-case fit: coding, agents, and build tasks
RAG
Included by capability and metadata signals in the decision map.
Agents
Included by capability and metadata signals in the decision map.
Long context
Included by capability and metadata signals in the decision map.
Provider price ladder
Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| Google AI Studio | $2.00 | $12.00 | Serverless |
Available via routers & gateways(13)
AIRouter
RouterCommercial LLM router that analyzes incoming requests and routes to the optimal model for cost/quality/latency via a drop-in OpenAI-compatible API, with a privacy-preserving embedding mode that avoids sending prompt content.
Helicone
GatewayObservability-first AI gateway with routing, caching, rate limiting, and request tracing; Apache 2.0 open-source core with a managed hosted tier for logging and analytics.
Kong AI Gateway
GatewayMulti-LLM AI gateway built on Kong Gateway 3.x, adding semantic routing, load balancing, guardrails, and MCP traffic analytics as plugins over Kong's existing API management platform.
LiteLLM
GatewayOpen-source Python SDK and proxy server that unifies 100+ LLM APIs behind a single OpenAI-compatible interface, with load balancing, cost tracking, and configurable failover.
Martian
RouterAI-powered LLM router that analyzes each prompt in real-time to select the optimal model, targeting 20–97% cost reduction while maintaining quality; San Francisco startup reportedly nearing $1.3B valuation.
Neutrino AI
RouterCommercial LLM router that dynamically routes each query to the best-suited model with load balancing and fallback handling, charging 3% of underlying AI spend.
Capabilities
Benchmark peer barsfor RAG
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
Comparison and alternatives
Browse all comparisons →Cheapest of 1 route · Google AI Studio