Gemini 3 significantly worse thant 2.5 Pro at long context. Temperature likely to blame

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Based on several use cases, Gemini-3-Pro-preview is demonstrating substantially inferior performance compared to Gemini 2.5 Pro specifically when processing long context content interactions - particularly large file uploaded content.

The degradation is likely attributable to it’s inability to perform at low temperature settings - this is likely the culprit affecting the model’s ability to think critically and sharply and maintain coherence and accuracy across long context windows.

Is anyone else experiencing this?

This is likely only noticeable to those who were using 2.5 Pro at low temperature settings before (0.2 or less, and particularly 0.05 or less).

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Hi @JSON_B_Kidd ,

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Subject: Re: Real-world data on iPhone 15 Pro Max confirms thermal throttling issues with long-context usage

Hi there,

I strongly agree with your hypothesis regarding temperature affecting performance. I just experienced a concrete example of this while stress-testing Gemini on mobile.

Device Specs:

• iPhone 15 Pro Max (A17 Pro Chip)

• Environment: Mobile App

Scenario:

I was conducting a high-complexity system architecture planning session (involving multi-layered logic, frequent role-switching, and a very long context window).

Observations:

1. Initial State: Response times were fast and logic was sharp (consistent with Gemini’s standard performance).

2. Degradation: As the conversation lengthened and the device temperature rose significantly (the phone became physically hot to the touch), I noticed a distinct spike in latency. The model seemed to struggle with complex logical retrieval.

3. Failure Point: Eventually, the device triggered its thermal protection mechanisms, causing the App to crash/flashback immediately during a response generation.

Conclusion:

This real-world “stress test” confirms that on mobile hardware, thermal throttling is a major bottleneck for Gemini’s advanced models (like 3 or 2.5 Pro) when handling long contexts. The hardware heat dissipation simply can’t keep up with the compute demands over extended sessions.

Just wanted to share this data point from the field!