Google now offers two research agents: Deep Research, replacing its December preview release, and Deep Research Max, both available via Gemini API paid tiers
Built with Gemini 3.1 Pro, the new Deep Research agents bring MCP support, native visualizations and unprecedented analytical quality …
The Keyword
Context & Ripple Effects
Deep Research began as an English-language Gemini Advanced feature designed to search the web and produce detailed reports. It was subsequently upgraded from a Gemini 2.0 Flash Thinking experimental model to Gemini 2.5 Pro Experimental for Gemini Advanced subscribers.
Google has since expanded higher-end reasoning capabilities through Gemini API access for some researchers and an Ultra-tier Deep Think offering. The new split between Deep Research and Deep Research Max moves research agents from a preview-style chatbot feature toward a tiered API product family.
First-order effects
Google replaces the December preview release with two Gemini 3.1 Pro-based research agents, giving paid Gemini API customers a standard and a higher-end Max option.
MCP support and native visualizations make the agents more immediately usable in tool-connected research workflows rather than only as report-generation features.
Second-order effects
Developers using Gemini API can differentiate research workflows by capability tier, while Google can package more demanding agent behavior separately from the base research product.
The MCP support raises the value of interoperable tool connections around research tasks, pressuring competing agent offerings to match both model quality and workflow integration.
Third-order effects
If this packaging persists, research agents are likely to become a metered, tiered API category, with providers competing on the combination of reasoning quality, tool access, and output formats rather than on chat interfaces alone.
The split also points to a more modular enterprise-agent market: a general research capability can be embedded into other software, while premium variants concentrate the highest-cost or highest-value tasks.
The trend: AI vendors are productizing advanced reasoning as tiered, tool-connected agents that developers can embed in operational workflows.
We are launching two powerful updates to Deep Research in the Gemini API, now with better quality, MCP support, and native chart/infographics generation. Use Deep Research when you want speed and efficiency, and use Max when you want the highest quality context gathering & [image…
Deep Research was our first hosted agent in the API and has gained a ton of traction over the last 3 months, very excited for folks to test out the new agents and all the improvements, this is just the start of our agents journey : ) Read more: https://blog.google/...
what i need is a deep research / agent swarm to continuously integrate all these frontier lab releases, as the job of keeping up to this all manually is clearly hitting the bio-danielle / bio-@TheZvi limit here. that's ok tho
$GOOGL, this is super smart. They built MCP/API calls directly into their Deep Research tool. The LLM no longer needs to randomly scrape websites for research-related data; you can feed it specifically what you want.
So many exciting updates here: 1. Deep research just got a refresh with better quality and a new “Max” version. 2. It now supports MCP, visualizations, collaborative planning. 3. AI Studio has now first-class support for agents, starting with deep research. Watch this space
The fact that there is no comparison to GPT Pro... also Google doesn't test FrontierMath (arguably because oai was involved in creation)... Perhaps they should give tokens to run evals on https://matharena.ai/ this would be independent math evaluation @j_dekoninck
Introducing our biggest upgrades to the Deep Research API yet... including Deep Research Max (our SOTA system), MCP support, Native charts & infographics, planning mode, full tool support (including Google tools), full multi-modal input support, & real-time progress streaming! [i…
we're reaching new heights of chart crimes. the browsercomp comparision makes it look like it's twice as better as the competition when this is very much not the case