I'm going to have to heavily disagree. Gemini 2.5 Pro has super impressive performance on large context problems. I routinely drive it up to 4-500k tokens in my coding agent. It's the only model where that much context produces even remotely useful results.

I think it also crushes most of the benchmarks for long context performance. I believe on MRCR (multi round coreference resolution) it beats pretty much any other model's performance at 128k at 1M tokens (o3 may have changed this).

Totally agreed on this. The context size is what made me switch to Gemini. Compared to Gemini, Claude's context window length is a joke.

Particularly for indie projects, you can essentially dump the entire code into it and with pro reasoning model, it's all handled pretty well.

I find that it consistently breaks around that exact range you specified. In the sense that reliability falls off a cliff, even though I've used it successfully close to the 1M token limit.

At 500k+ I will define a task and it will suddenly panic and go back to a previous task that we just fully completed.

OOI what coding agent are you managing to get to work nicely with G2.5 Pro?

Is that a codebase you're giving it?