According to DeepLearning.AI, Claude Sonnet 5.5 produced less mergeable code at its max reasoning setting than at xhigh while consuming more tokens, underscoring the need to benchmark settings before deployment.

According to satyanadella, Copilot on Windows adds Hybrid Intelligence to use local models, act on PC context, and cut token costs with user permission.

According to TheRundownAI, OpenAI’s top customer uses 100B tokens monthly, and Sam Altman says it is not the global leader, indicating massive demand.

According to gdb, OpenAI will grant $2M in tokens to every YC S24 and S25 startup, with YC extending the summer deadline to May 25.

According to @sama, OpenAI will invest $2M in tokens for every YC startup, signaling new AI funding mechanics and product velocity, per @bosmeny.

According to gdb, OpenAI offers discounted tokens and guaranteed compute for 1–3 year commits amid rising capacity constraints.

According to The Rundown AI on X, Sam Altman told the BlackRock U.S. Infrastructure Summit that OpenAI and other model providers will fundamentally monetize by “selling tokens,” framing inference usage as the core revenue unit and noting competitors may invest tens of millions to billions to match capability (source: The Rundown AI). As reported by The Rundown AI, this token-based model implies scale advantages for foundation model operators with optimized inference stacks, large-scale GPU capacity, and power-secure data centers, shaping pricing strategies around context length, latency tiers, and fine-tune throughput. According to The Rundown AI, enterprises should evaluate total cost of ownership across model quality per token, rate limits, and dedicated capacity contracts, while infrastructure investors can target GPU clusters, power procurement, and cooling to capture rising inference demand. As reported by The Rundown AI, Altman’s remarks underscore a shift from “model releases” to “usage economies,” where unit economics depend on tokens per task, hardware efficiency, and long-context workload mix.