Was able to sign up for the Max plan & start using it via opencode. It does a way better job than Qwen3 Coder in my opinion. Still extremely fast, but in less than 1 hour I was able to use 7M input tokens, so with a single agent running I would be able easily to pass that 120M daily token limit. The speed difference between Claude Code is significant though - to the point where I'm not waiting for generation most of the time, I'm waiting for my tests to run.
For reference, each new request needs to send all previous messages - tool calls force new requests too. So it's essentially cumulative when you're chatting with an agent - my opencode agent's context window is only 50% used at 72k tokens, but Cerebra's tracking online shows that I've used 1M input tokens and 10k output tokens already.
> For reference, each new request needs to send all previous messages - tool calls force new requests too. So it's essentially cumulative when you're chatting with an agent - my opencode agent's context window is only 50% used at 72k tokens, but Cerebra's tracking online shows that I've used 1M input tokens and 10k output tokens already.
This is how every "chatbot" / "agentic flow" / etc works behind the scenes. That's why I liked that "you should build an agent" post a few days ago. It gets people to really understand what's behind the curtain. It's requests all the way down, sometimes with more context added, sometimes with less (subagents & co).
Many API endpoints (and local services for that matter) does caching at this point though, with much cheaper prices for input/outputs that were found in the caching. I know Anthrophic does this, and DeepSeek I think too, at the very least.
At those speeds, it's probably impossible. It would require enormous amounts of memory (which the chip simply doesn't have, there's no room for it) or rather a lot of bandwidth off-chip to storage, and again they wouldn't want to waste surface area on the wiring. Bit of a drawback of increasing density.
For reference, each new request needs to send all previous messages - tool calls force new requests too. So it's essentially cumulative when you're chatting with an agent - my opencode agent's context window is only 50% used at 72k tokens, but Cerebra's tracking online shows that I've used 1M input tokens and 10k output tokens already.