ivan_dev

Fullstack + Cloud + AI + IoT builder || Creative, Problem solver, Optimization & Cost reduction || Crypto & Stock enthusiast

[ivan_dev @ivandevm8]

@thsottiaux Thanks!

[ivan_dev @ivandevm8]

@codex_resets Nevermind, got my reset

[ivan_dev @ivandevm8]

@codex_resets No yet, plus plan, is there something wrong?

[ivan_dev @ivandevm8]

@araseb_ Because you can't vibe code infraestructure

[ivan_dev @ivandevm8]

@stylishdawg Try DSH

[ivan_dev @ivandevm8]

@pamelamorales__ Por que un dia un reclutador sin verguenza lo hizo y otros vieron que no paso nada y le siguieron el rollo

[ivan_dev @ivandevm8]

@sstvrgirl_ Ami tampoco me gusta el ingles, no me apetese aprenderlo, solo lo uso por compromiso(poder hablar con todo el mundo), lo aprendi indirectamente de la exposicion constante del idioma, nunca lo estudie como tal como lo estoy haciendo con el japones

[ivan_dev @ivandevm8]

@melvindvivas No reset yet

[0xSero @0xSero]

8,000$ can buy you a frontier model.

Most of you MFs are spending that much a year on AI anyway

[ivan_dev @ivandevm8]

@thsottiaux I didn't receive a reset yet, is something wrong?

[ivan_dev @ivandevm8]

@Deepusleepy I see no reset

[ivan_dev @ivandevm8]

@nadzi_mouad Reset? where lol

[ivan_dev @ivandevm8]

@MarcosHernanz Speed on a coding agent is not that relevant, is nice to have but there're other things like the hallucination rate, intelligence or the price per token that are more important

[Sad AlbertX @SadAlbert10]

GPT 6 ASTRA Usage for Plus users be like:

[ivan_dev @ivandevm8]

@rohit3a Yeah, I'm using Astra at light and the usage is acceptable now

[ivan_dev @ivandevm8]

@blueemi99

[ivan_dev @ivandevm8]

@StefanoGPT leave the weekly reset date unchanged

[Artificial Analysis @ArtificialAnlys]

Announcing Artificial Analysis Intelligence Index v4.3, upgrading Terminal-Bench to 4.0 and adding AutomationBench-AA, an agentic workflow automation benchmark with a private test set. This is a continuation of our rollout of Intelligence Index v5

Changelog (Index v4.2 → Index v4.3):
➤ Terminal-Bench: 2.1 → 4.0, completing our upgrade to the latest version of Terminal-Bench
➤ Replacing 𝜏³-Banking with AutomationBench-AA, our implementation of Zapier's business workflow automation benchmark

We are continuing to prioritize keeping Intelligence Index as useful as possible by bringing forward a subset of the changes we had planned for Index v5. Each change in v4.2 and v4.3 stands on its own merits and brings the Index closer to real-world problem solving, adds more private test sets to prevent gaming, and reduces saturation

Intelligence Index v4.3 raises the difficulty of agentic coding tasks and broadens the types of agentic workflows tested. Because we use a held-out test set for AutomationBench-AA, in collaboration with @zapier, the weight assigned to evaluations with private tasks or answers increases from 40% to 45%. Category weights are unchanged from v4.2: Agents 30%, Coding 20%, General 30%, Scientific Reasoning 20%

Detailed changes:
➤ Upgraded Terminal-Bench 2.1 to 4.0: 66 multi-step tasks testing agents on tasks run in agent sandboxes driven via the terminal, including tasks involving software engineering, machine learning, science, and operations. The 4.0 update recalibrates compute and time allowances, and improves task instructions and verification. We have changed from the Terminus 2 harness to mini-SWE-agent, a minimal, model-agnostic harness. We will also be updating our Coding Agent Index, where we test model and harness pairs, to include Terminal-Bench 4.0 soon

➤ Replaced 𝜏³-Banking with AutomationBench-AA: Our implementation of Zapier’s AutomationBench tests agents on 657 business workflows across simulated applications such as Gmail, Slack, Salesforce, and Jira. Agents must complete task objectives while following business rules. AutomationBench-AA uses Zapier’s private set of 657 tasks, and is built on v1.0.6

Key results:
➤ Claude Fable 5.1 and GPT-6 Astra lead the Intelligence Index: Both Claude Fable 5.1 (max with fallback) and GPT-6 Astra (max) score 53 on Intelligence Index v4.3, followed by Claude Opus 5 (max, 51), Claude Fable 5 (with fallback, 50), Muse Spark 1.3 (max, 48) and GPT-5.6 Sol (max, 47)
➤ GLM-5.3 and Kimi K3 continue to lead open weights models (both at 44): GLM-5.3-Flash (42) is the third strongest open weights model, followed by Qwen3.8 2.4T A95B (40) and DeepSeek V4 Pro 0813 (max, 36)
➤ 4 labs occupy the Intelligence vs. Cost per Task Pareto frontier: OpenAI occupies the majority of the cost-efficiency frontier, with all five reasoning efforts of the recently released GPT-6 Astra offering the lowest Cost per Task at their respective levels of intelligence. Claude Fable 5.1 (xhigh, max, 53), GLM-5.3-Flash (42) and MiMo-V2.5-Pro (26) round out the rest of the frontier

[ivan_dev @ivandevm8]

@melvindvivas Man, having Plus plan and trying to use Astra is like playing a resource management game at legendary difficult

[ivan_dev @ivandevm8]

@StefanoGPT Codex version 0.153.4 on Chatgpt Linux App (26.901.41123v)