Gemini
Google's answer to GPT-4
4.8•125 reviews•4.8K followers
Google's answer to GPT-4
4.8•125 reviews•4.8K followers
Google's largest and most capable AI model. Built from the ground up to be multimodal, Gemini can generalize and seamlessly understand, operate across and combine different types of information, including text, images, audio, video and code.
This is the 11th launch from Gemini. View more
Gemini 3.1 Pro
Launching today
3.1 Pro is designed for tasks where a simple answer isn’t enough. Building on the Gemini 3 series, 3.1 Pro represents a step forward in core reasoning. 3.1 Pro is a smarter, more capable baseline for complex problem-solving.
Launch Team
OpenAI
GPT-5
Humans in the Loop
The AI race continues. OpenAI launched GPT-5.3-Codex 2 weeks ago. Anthropic, Sonnet 4.6 this week. And Google? They just announced @Gemini 3.1 Pro, "a smarter, more capable model for complex problem-solving."
Available in products like @Google AI Studio, @Kilo Code, and @Raycast.
Game on!
VYVE
@fmerian I am now enjoying doing so much research work on Gemini, things that I used to be doing with deep research. It's like I'm swinging between capabilities.
Gemini is alwasy good at benchmarks, but usually not great at agentic behaviour. The models have very weird behaviour. Almost like the Gemini team is not really testing them themselves.
@peter_albert nailed it. I'm running Gemini models in production for Aitinery (AI travel planner) and this is exactly the gap.
Benchmarks say Gemini is world-class. My production logs say it sometimes hallucinates restaurant names that don't exist and occasionally generates itineraries with 16-hour driving days. Benchmarks don't test "can this model reliably plan a family trip to Puglia without suggesting a 3am dinner reservation?"
That said — 3.1 Pro feels like Google is finally closing the gap between benchmark performance and real-world agentic reliability. The reasoning improvements matter more for agent builders than the raw intelligence bump.
The uncomfortable truth about the AI model race: for 95% of real applications, the difference between GPT-5.3, Sonnet 4.6, and Gemini 3.1 Pro is negligible. What matters is reliability, cost, and speed — not who wins on ARC-AGI-2.
Curious to see how 3.1 Pro handles multi-step planning tasks. That's where Gemini has historically struggled compared to Claude for agentic workflows.
AgentReady
If you're building with Gemini 3.1 Pro and want to keep API costs under control as complexity scales, check out TokenCut by agentready.cloud — it helps reduce token usage without sacrificing output quality. Perfect companion for a reasoning-heavy model like this one!
vibecoder.date
Does google read these?
I'll give it a shot in gemini CLI and see what's up
I can't keep using Antigrativy, there is no update available; and I can't use the previous model.
Folderly
i like it