
a11
377 posts

a11
@StreamVC_
run + serve LLMs on hardware you already own. benchmarks, configs, teardowns.


Yes - the correct view here is that this is extremely exciting and we are directing our attention on figuring out how to attract liquidity to the vault & open up this leveraged yield farming strategy to much larger pools of capital


ran the wstDIEM loop numbers for anyone eyeing it. what stands out: at current pool utilization morpho borrow is ~0.5%, basically free. so once there's depth to loop into, the returns hold up even at today's realized yield - ~10% at 2x, 15% at 3.3x, 19% at 4.4x. if the inference yield ramps toward 11–16%, you're at 20–64%. the cheap borrow is a function of low utilization though. as people loop in it climbs and the spread tightens, so the edge is front-loaded. but overall really excited by this, lets build loop sizing as CLI?





Today, Colosseum will host the inaugural MetaDAO Owners Meeting in San Francisco. Builders, founders, and investors from across the world have flown in to worship at the altar of decision markets, including futarchy’s inventor, @robinhanson. Doors open at 10am.

what a move by elon. everyone else spent two years scraping github for code, xai went and trained the model with cursor, directly inside the place where real engineering happens. distribution and training data in one deal. and the economics are the actual announcement. $2/$6 per million tokens, ~4x fewer output tokens than opus on the same swe-bench tasks, 80 tok/s. the intelligence board is honestly mixed, it takes terminal-bench and deepswe off opus 4.8, drops swe-bench pro and multilingual. elon himself called it opus 4.7 level. that's the right read. but here's the thing, if opus level intelligence gets this cheap, the calculus changes. grok 4.5 takes the everyday agent work and my claude code subscription quietly turns into a fable subscription, the button i press when the task is actually hard. the coding model war just became a price war. price wars are won by users.


Announcing Grok 4.5, our first model trained specifically for coding and agents. It was trained with Cursor and offers frontier intelligence at leading speeds and cost efficiency. x.ai/news/grok-4-5







Local AI just got faster. ⚡️ We worked with @ggerganov to add DFlash support in llama.cpp delivering ~2x faster inference.





@cocktailpeanut This is great thank you! Been trying to access through LAN for longer than care to admit, could always connect to Pinokio but not running apps.


Goodbye @AnthropicAI. All comma dollars go towards the mission and our values. Our dollars come from customers buying hardware they own. And we spend them on GPUs and engineers to write MIT-licensed software.



