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Exotic
@ex0t1clol
ai tomfoolery | playing your music with | making your computers talk to each other with
712 Following    427 Followers
babe wake up Tokenomics 101 just dropped
hi theo, an unreleased model (codenamed gpt 6.7 Interstellar) found the best optimization for this project, to reduce bugs to ZERO. it filed a pr for you!
Announcing tsc-rs (aka ts-rust), my complete rewrite of the Typescript compiler, type checker, and LSP, all in Rust. This is a project I've had agents working on for 5 months now. I burned ~$400k of Codex tokens and got nowhere. Burned ~$20k of Opus and got there in 2 weeks. I have not read a single line of the code. tsc-rs is an open source drop-in replacement for tsc, and it's available now.
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okay i’m building a harness harness harness
my favorite prompt of all time
we got le chaton fat before gta 6
Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.
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yeah because we all know t3 code is not free and closed source in fact, to get The People’s Deserved Revenge i managed to find their source code and leak it, here it is
Knowing it's the, it probably won't be free and open source but great idea to experiment with
i hate that i was right
I made Synara free and open source. And I’m starting to regret it.
if google was founded in 2026
remember when you couldn’t tab out of your ai chat because it would stop the stream
Introducing Glorp, the AI you raise. Pay child support, watch it make friends. None of them are employed. Attend its demo day. Take it to therapy and watch it start a podcast about how you traumatized it.
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Introducing Pickle, a personal AI you raise. It gets things done for you and makes friends of its own. Meet yours:
the @TIDAL app on ios is horrible, let me join for like a week, fix it and leave
“bro opus 5.5 is definitely better” “no what do you mean it’s sol 6.1” “have you even used opus?” “no, have you used sol?” “no”
we should stop using api cost estimates as a good way to express how much ai we're using raw token counts are literally better
Dario watching DevDay right now
Introducing 6.1 Sol, near Astra intelligence at one fifth of the price of Astra and 95% cache read discount. It is an absolute workhorse. Combined with ultrafast for 8X speeded available today for Astra and coming soon for 6.1 Sol.
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no usage limits for dots???? DAMN
im so glad i can stop using poke and instinct
these mfs tryharded the starting soon screen
new voice mode today on devday
can we get a new analysis index? why is sonnet better than astra lmao
Anthropic has launched Claude Sonnet 5.5: it scores 56 on the Artificial Analysis Intelligence Index, just 2 points behind Opus 5.5 (max), but at the highest Output Tokens per Task we’ve seen With max effort, Sonnet 5.5 gains 18 points over Sonnet 5 and to #2# on the Intelligence Index behind only Opus 5.5 (max). Anthropic has priced Sonnet 5.5 identically to Sonnet 5 at $0.2/$2/$10 per 1M cache input/input/output tokens, however it outputs a higher number of Output Tokens per Task and costs $7.60 per task (~50% higher than Sonnet 5’s Cost per Task) Key takeaways: ➤ Meets leading models on agentic terminal use and knowledge work: in Terminal-Bench 4.0, Claude Sonnet 5.5 reaches 64% against 60% for Opus 5.5 and GPT-6 Astra. On AA-Briefcase (1811 vs 1822 Elo), GDPval-AA (1844 vs 1846 Elo), and AutomationBench-AA (71% vs 70% headline score), Sonnet 5.5 reaches parity with Opus 5.5, albeit with significantly higher token usage to achieve it ➤ Heaviest token use we have measured: at max effort, where it reaches performance nearing that of Opus 5.5, Claude Sonnet 5.5 used ~193k Output Tokens per Intelligence Index Task. This is the highest token use we have measured on around 60% higher than Opus 5.5 (max) or Sonnet 5 (max) and ~7x GPT-6 Astra (max) ➤ Pricing remains at $2/$10 per million tokens of input/output, matching GPT-6 Sol. At this pricing Claude Sonnet 5.5 sits off the Intelligence vs. Cost per Task Pareto Frontier. At high effort levels it sits behind Opus 5.5, while lower efforts have GPT-6 Astra or Sol configurations delivering equivalent performance for lower cost. The high effort setting is the most competitive on this basis, sitting very narrowly behind GPT-6 Sol on Intelligence at effectively the same Cost per Task ➤ Behind Opus 5.5 on factual knowledge and scientific reasoning: as a smaller class model, Sonnet 5.5 still lags on factual knowledge in AA-Omniscience compared to Opus 5.5. It scores 54% against 66% for factual accuracy, though with a lower hallucination rate (47% against 59%). It also sits ~6 points lower on Humanity's Last Exam and SciCode compared to Opus These evaluations were conducted on a pre-release deployment of Claude Sonnet 5.5, which Anthropic found to have a bug that can degrade responses to requests that use structured outputs. This is fixed for the public release and Anthropic expects minimal change or slightly understated performance, but we will be re-running relevant evaluations soon. Other model details: ➤ Context window: 1 million tokens with image and text input, unchanged from Sonnet 5 ➤ Pricing: unchanged from Sonnet 5’s latest $2/$10 per 1M input/output tokens; cache writes at $2.5, cache reads $0.2 ➤ Effort settings: five (low, medium, high, xhigh, max). Intelligence Index evaluations were run at all five with Anthropic's default fallback enabled. We see Sonnet 5.5 fall back in ~0.1% of tasks across the Intelligence Index, primarily in TerminalBench 4.0, falling back to Sonnet 5 in all cases.
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anything but shipping v2
it takes two to tango day two