Gemini 3.2 Flash - Capitalizing on DeepMind's clever distillation techniques... Rumors are that benchmarks show it's hitting 92% of GPT 5.5's performance on coding and reasoning tasks while being 15-20x cheaper on inference costs. The latency improvements are insane - sub-200ms for most queries. Google's distillation + sparsity techniques are paying off massively. They've essentially compressed a frontier model into a flash variant without the usual quality cliff.

Open-source AI is ruthlessly out-innovating the trillion-dollar monopolies. 🚀 Big labs are burning billions brute-forcing AGI on massive GPU clusters. Meanwhile, the open ecosystem is structurally forced to innovate on inference—and it's working. Look at what just happened: - DeepSeek v4 using SSDs for KV cache. - Breakthroughs like TurboQuant and Kimi K2 are aggressively compressing memory and driving the cost of intelligence to near zero. When you don't have infinite compute, you actually have to engineer better solutions. Constraints breed miracles. By solving the KV cache bottleneck, scrappy open-source builders are creating vastly cheaper and more profitable AI than the bloated closed-source giants. Hacker culture > GPU monopolies. Period.

Human Programmers Will Stick Around…. While you can totally vibe code an app written by AI from scratch It’s a total nightmare to use AI coding on a complex human generated code base Humans typically generate more complexity and tech debt than AI can handle We still desperately need human programmers 😅

It’s no longer a given that the next generation model will be better - Opus 4.7 is legit worse than 4.6 - Gemini 3.1 worse than 2.5 - Sonnet 4.6 buggier than 4.5 The SOTA models are beginning to run around in circles

🚨 OPEN SOURCE AI IS LITERALLY UNSTOPPABLE 🚨 The legendary founder of Redis (Antirez) just dropped ds4 - a custom native inference engine built specifically for DeepSeek v4 Flash This is earth shattering! Here is why: DeepSeek v4 Flash is a quasi-frontier model with a massive 1M context window You can now run it LOCALLY on a 128GB Mac using specialized 2-bit quantization The architecture is reimagined—he moved the KV cache from RAM directly to the SSD disk! 🤯 We already know DeepSeek v4 Flash is insanely good for agentic loops - Now you don't even need the cloud to run it Closed-source labs are burning tens of billions on massive GPU clusters while single brilliant developers are running frontier-level AI on laptops! They told us open-source would be worthless against trillion-dollar monopolies Instead, pure hacker culture + incredible open-weight models are completely rewriting the rules Open Source will ALWAYS win 💕

Best models - May Edition Coding - GPT 5.5 xHigh Seeking truth - Grok 4.3 Video - SeeDance 2.0 Image - GPT Image 2.0 Voice - Gemini Live Hermes - m2.7 Cheap coding - Kimi 2.6 Cheap fast - Gemini Flash Best open source - DeepSeek v4 Pretty much everything will change after Google I/O

Running loops burning infinite tokens a day leads to extreme brain rot Once AI has generated 10k lines of code, engineers have zero idea of what is going on The bugs multiply, AI debt spins out of control and uptime drops

🚨 RIP FIGMA - CREATE PIXEL PERFECT DESIGNS AND MOCK-UPs Excited for Abacus AI's Design Vertical It's almost jaw dropping - create pixel perfect high fidelity mock-ups from prompts and sketches The one-click from the mock-ups to finished apps