u/andrewaltair

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So Google announced Gemini 3.5 Flash this week. I was looking over the Artificial Analysis numbers and the cost jump is pretty crazy. It's basically 5.5 times more expensive to run than the older 3.0 Flash model.

They tripled the input token price to $1.50 per million, and output tokens are sitting at $9.00 now. The weirdest part is that 3.5 Flash takes a lot more steps to handle complex tasks. It averages around 49 steps compared to just 23 for 3.1 Pro, so in practical terms it actually ends up being about 75% more expensive to run than the heavier Pro model. It is really fast though, pumping out 280 tokens a second which is a 70% speed bump. On the benchmark side it scored a 55 on the IQ index, beating out Grok 4.3 and Claude Sonnet 4.6, but its coding is still kind of weak at a 45. At least hallucinations dropped by 31 points down to 61%. Honestly this seems to be a trend everywhere right now. OpenAI's GPT-5.5 is 50 to 90% more expensive than their last one, and Claude Opus 4.7 is up by 30 to 40% too.

Basically the whole market is shifting towards these autonomous multi-step systems and they just eat up massive amounts of compute. Definitely going to force everyone to rethink their API budgets and how they handle AI spending going forward.

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So Mark Zuckerberg admitted during a staff meeting that Meta was actively training their internal AI models on the work of people they were already planning to fire. A leaked audio recording published by More Perfect Union on Wednesday ended up perfectly coinciding with the actual start of them letting 7,800 people go.

Back in April Meta made it official that they were cutting 10% of their workforce. They gave the staff a one month notice period but kept the names of who was actually getting the axe a secret until the last minute. In the leaked tape Zuckerberg goes into detail about how they decided to skip hiring outside contractors to save cash. Instead they just used the expertise of their own highly skilled employees to feed the models. His reasoning was that Meta employees have a much higher average intelligence than standard contractors anyway. Because of that, having the models learn to write code by directly observing the company's own engineers every day was way faster and more effective than other industry alternatives.

Seeing major tech companies train next gen AI systems on the data and skills of their own workforce is a pretty clear indicator of current strategies. It points directly at them slashing operating costs and actively working to replace human roles with artificial intelligence.

Andrej Karpathy, co-founder of OpenAI and former Director of AI at Tesla, announced on Monday that he is joining Anthropic. After focusing on AI education for the past two years via his startup Eureka Labs, Karpathy will now work within Anthropic’s pre-training unit under the leadership of Nick Joseph.

Karpathy’s career has been central to major AI milestones, including a tenure at OpenAI (2015-2017) and leading Tesla’s Autopilot team until 2022. In January 2026, he famously identified a "phase shift" in software engineering, coining the term "vibe-coding" to describe the transition to agent-led development. He noted that AI coding agents crossed a critical coherence threshold in December 2025.

This move follows a series of high-profile transitions from OpenAI to Anthropic, including co-founder John Schulman in August 2024. Karpathy stated that the next few years at the frontier of Large Language Models (LLMs) will be "especially significant," citing this as the primary reason for his return to active research and development.

Andrej Karpathy, co-founder of OpenAI and former Director of AI at Tesla, announced on Monday that he is joining Anthropic. After focusing on AI education for the past two years via his startup Eureka Labs, Karpathy will now work within Anthropic’s pre-training unit under the leadership of Nick Joseph.

Karpathy’s career has been central to major AI milestones, including a tenure at OpenAI (2015-2017) and leading Tesla’s Autopilot team until 2022. In January 2026, he famously identified a "phase shift" in software engineering, coining the term "vibe-coding" to describe the transition to agent-led development. He noted that AI coding agents crossed a critical coherence threshold in December 2025.

This move follows a series of high-profile transitions from OpenAI to Anthropic, including co-founder John Schulman in August 2024. Karpathy stated that the next few years at the frontier of Large Language Models (LLMs) will be "especially significant," citing this as the primary reason for his return to active research and development.

OpenAI CEO Sam Altman stated the company must transition into an AI inference business, reflecting an industry shift as GitHub announced it will move Copilot from fixed-rate to consumption-based billing on June 1, 2026. The change is driven by the massive surge in compute usage caused by autonomous AI agents.

Major AI providers are currently heavily subsidizing corporate subscriptions. Microsoft lost over $20 per user monthly on GitHub Copilot, with heavy users costing up to $80 on a $10 subscription. Similarly, a $20 Claude Pro subscription can consume $200 to $400 worth of compute at standard API rates, and Anthropic users reportedly burn $8 in compute for every $1 in revenue. To support this scale, OpenAI projects a $115 billion cash burn by 2029, while Oracle took on $43 billion in debt in a single year to build infrastructure.

As AI laboratories prepare for public offerings, the pressure to achieve profitability will force an end to subsidized pricing, requiring corporate clients to drastically recalculate their IT budgets.