CPU supercyle, Finally DeepSeek v4, GPT-5.5, & More

TLDR;

Hello from Washington DC, my home again for another three weeks. This week, we have several huge announcements across all layers: technology, with releases like GPT-5.5 or DeepSeek v4, and one of the coolest AI projects I’ve ever seen in FlipBook, markets, and product.

Enjoy!

FRONTIER

OpenAI Launches GPT-5.5, New SOTA?

OpenAI has finally launched GPT-5.5, describing it as its most capable model yet and positioning it around longer, more agentic work rather than simple chat interactions.

The model is designed to handle coding, research, document creation, spreadsheet work, computer use, and multi-step workflows with less user guidance. It is available in ChatGPT and Codex for paid users, and in the API, where GPT-5.5 is priced at $5 per million input tokens and $30 per million output tokens.

Surprise, a price hike! Who would have expected? Well, if you’re a reader of this newsletter, you knew this was coming.

OpenAI reports gains across coding, tool use, professional work, and browser-based tasks. It says GPT-5.5 scores 82.7% on Terminal-Bench 2.0, 84.4% on BrowseComp, 75.3% on MCP Atlas, and 84.9% on GDPval, all focused on agentic and real-world tasks.

The company frames the model as better at understanding ambiguous requests, using tools, checking its own work, and completing complex tasks across several steps.

TheWhiteBox’s takeaway:

I’ve been using this model for the past day or so, and the feedback is great. It’s snappier, thinking adaptiveness has improved a lot (i.e., it knows when to think for longer and when it can answer directly), and the model is a blessing to use for coding.

The big question here is how this model compares to Anthropic’s Mythos. And the answer is that it depends.

While GPT-5.5 seems to be somewhat above Opus 4.7 (haven’t seen per-prediction comparisons, meaning GPT-5.5 might be smarter simply because it has higher thinking budgets), it’s not quite at the level of Mythos, as seen in the thumbnail.

However, GPT-5.5 Pro is another story: it's basically Mythos-level, but is actually available to use today. The flip side is that this isn’t a fair comparison. The reason is that, unbeknownst to many, OpenAI’s Pro family isn’t a different model at all; it’s a best-of-N sampling of the base model.

In other words, GPT-5.5 Pro is GPT-5.5 run multiple times on the task, and the answer you get is the “best” response, with “best” being the most common answer across the multiple tryouts. This is unfair to Mythos, which gets similar results after a single run.

On the flip side, this is also probably unfair to OpenAI, which has released GPT-5.5 again as a distillation of a larger model (they call it ‘Spud’ instead of Mythos) but did so more effectively than Anthropic with Opus 4.7. So the true equivalent to Mythos is almost certainly not GPT-5.5, which feels more like a model of Opus 4.7’s size.

In a nutshell, you can already tell by how confusing my explanation is that it’s really almost never an apples-to-apples comparison, and knowing who’s…

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