Horacio

La solución no está en la grada, es hora de bajar al campo y marcar goles.

[Horacio @horacio123]

@ivanuscom @zharion7 ¿Y? ¿Alguien va a hacer algo? Lo dudo. Por eso lo hacen.

[Horacio @horacio123]

@bitcoin_n_chill @GustavoBolsa Ni lo harán.

[Artificial Analysis @ArtificialAnlys]

GPT-5.6 Sol comes close second to Claude Fable 5 in the Artificial Analysis Intelligence Index at one third of the cost, and leads the Artificial Analysis Coding Agent Index in OpenAI’s Codex harness

We supported @OpenAI with pre-release evaluation of GPT-5.6 Sol, Terra, and Luna. GPT-5.6 Sol (max) scores 1 point below Claude Fable 5 (max) in the Artificial Analysis Intelligence Index at 59 points, at approximately one third of the cost. GPT-5.6 Terra (max) and Luna (max) score 55 and 51 respectively in the Intelligence Index, at ~50% and ~80% lower Cost per Task than Sol.

GPT-5.6 Sol (max) leads the Artificial Analysis Coding Agent Index at 80 points.

Congratulations @OpenAI and @sama on the launch!

Key takeaways:

➤ One third of the cost of Claude Fable 5: On max reasoning effort, GPT-5.6 Sol costs $1.04 per task in the Artificial Analysis Intelligence Index - offering a similar level of intelligence to Claude Fable 5 at approximately one third of the cost. Reasoning levels across GPT-5.6 Sol and Luna offer a range of options at the Pareto frontier of Intelligence vs Cost per Task. For example, GPT-5.6 Luna (max) matches or exceeds the intelligence of GLM-5.2 (max) and Gemini 3.5 Flash at a lower cost. GPT-5.6 Terra (max) and Luna (max) cost $0.55 and $0.21 per Intelligence Index task, ~50% and ~80% less than Sol. Across reasoning efforts, each new GPT-5.6 model pushes past GPT-5.5 on the Pareto frontier (excluding non-reasoning). Notably, Luna and Sol are always on the Pareto frontier ahead of Terra. This means that for any Terra effort level, there is a Luna or Sol effort level that is more intelligent at no extra cost, or as intelligent at lower cost.

➤ Leading in all Coding Agent evaluations: The new Artificial Analysis Coding Agent Index pairs models with agentic harnesses and features three frontier coding evaluations - DeepSWE, Terminal-Bench v2, and SWE-Atlas-QnA. GPT-5.6 Sol (max) in Codex scores 80 in the Index, leading in all three evaluations (tying Grok 4.5 in Grok Build for SWE-Atlas-QnA). In addition to scoring higher, its per task cost is ~40% and ~10% cheaper than Claude Fable 5 (max) and Opus 4.8 (max) respectively in Claude Code. GPT-5.6 Terra (max) and Luna (max) score 77 and 75 in the Coding Agent Index respectively, with ~60% and ~80% per-task cost reductions compared to Sol.

➤ Highest Presentation Elo in AA-Briefcase: GPT-5.6 Sol (max) ranks second only to Claude Fable 5 (max) in AA-Briefcase, and has the highest Presentation Elo of any model. AA-Briefcase is a new benchmark for testing models on realistic knowledge work tasks in complex projects built by industry experts. GPT-5.6 Sol (max) has the highest recorded Presentation Elo - its outputs across various file types, including PowerPoint and Excel, are the most visually attractive of any model. Fable 5 (max) still leads AA-Briefcase, largely due to its Rubric Score of 56% vs 42% for GPT-5.6 Sol (max). Fable 5 (max) also scores 1764 in Analytical Quality Elo vs GPT-5.6 Sol (max) at 1592.

➤ First OpenAI models with cache-write pricing: GPT-5.6 introduces cache-write pricing for the first time at OpenAI. Sol, Terra, and Luna are priced at $5/$30, $2.5/$15, and $1/$6 respectively per million input/output tokens. OpenAI has retained its previous discount of 90% for cache reads, but joins Anthropic in introducing a cost premium for cache writes, at 1.25x the price of input tokens. Cache writes occur when input tokens are committed to memory. Charging for a cache write more accurately reflects the model’s cost to serve, as cached tokens occupy memory whether or not they are reused. Also in line with Anthropic's models, GPT-5.6 introduces a max reasoning effort level.

➤ Low token use: GPT-5.6 Sol (max) uses fewer output tokens than most models of comparable intelligence, and defines a new Pareto frontier of Intelligence vs Output Tokens per Task. GPT-5.6 Sol (max) offers a slight improvement in token efficiency with 15k tokens per Intelligence Index task, vs GPT-5.5 at 16k. Notably, it uses fewer tokens and is more intelligent than Claude Opus 4.8 (max), GLM-5.2 (max), and Gemini 3.5 Flash (high).

[OpenAI @OpenAI]

Introducing ChatGPT Work, a new agent in ChatGPT powered by Codex and GPT-5.6.

It can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work.

It’s a whole new way to get work done.

[komet💫 @jonkomet]

@sama bro the costs are beautiful

[MΛRC VIDΛL @marcvidal]

Pongamos que en este hemiciclo se vota una de las propuestas más agresivas y lesivas hacia un derecho fundamental como es la privacidad. Pongamos que eso afectará a 450 millones de europeos.

Este es el quorum de la sesión...

[Google AI Studio @GoogleAIStudio]

bringing your code from @github into ai studio build is as easy as clicking 'import from github'

[OpenAI Developers @OpenAIDevs]

GPT-5.6 comes in three model tiers.

→ Sol handles long-horizon coding and agentic work that demands planning, tool use, and follow-through.
→ Terra balances performance and cost for everyday work.
→ Luna brings speed to well-defined, high-volume work.

Across knowledge-work evaluations, GPT-5.6 Terra surpasses GPT-5.5 at lower cost, while GPT-5.6 Luna nearly matches GPT-5.5’s peak performance at well under half the estimated API cost.

https://t.co/XLGYkgiOlE

[Horacio @horacio123]

@atenea_esp @rubenmansolivar Solo me faltó eliminar totalmente el impuesto a la energía. 👏

[Atenea @atenea_esp]

«El documento elaborado por @rubenmansolivar propone una agenda de reformas estructurales para el período de 2026-2035 con el objetivo de reforzar la productividad, la competitividad, la sostenibilidad del Estado del bienestar y la capacidad de crecimiento de la economía española»

🗞️ @TheObjective_es
https://t.co/lnxDJinmwP

[ClaudeDevs @ClaudeDevs]

We've reset 5-hour and weekly rate limits for all users.

[Artificial Analysis @ArtificialAnlys]

SpaceXAI’s Grok 4.5 scores 54 to place fourth on the Artificial Analysis Intelligence Index following only Fable 5, GPT-5.5, and Opus 4.8. It scores on par with GPT-5.5 in Codex on the Artificial Analysis Coding Agent Index in the Grok Build harness, at much lower cost

Grok 4.5 improves 16 points over Grok 4.3 on the Intelligence Index, bringing SpaceXAI to the intelligence frontier behind only OpenAI and Anthropic, and outperforming all open weights models and notably Google’s Gemini models. Key standout areas of performance are agentic knowledge work and coding.

Grok 4.5 in Grok Build scores 76 on the Artificial Analysis Coding Agent Index, on par with GPT-5.5 (xhigh) in Codex and just below Fable 5 (max) in Claude Code, and at a small fraction of the token usage and price.

Congratulations to @SpaceXAI, @cursor_ai, and @elonmusk on the impressive release!

Key Takeaways:

➤ Grok 4.5 performs very strongly on agentic tasks. Grok 4.5 ranks #4 on GDPval-AA v2 with an Elo of 1543, between Claude Opus 4.8 (1600) and GLM-5.2 (1513). It achieves the top score on 𝜏³-Banking of 33%, above 31% from GPT-5.5 (xhigh), and sits on the cost vs performance Pareto frontier across all three agentic evaluations in the Intelligence Index
➤ Grok 4.5 is one of the most cost efficient models to run for near-frontier intelligence. It costs $0.31 per task on the Artificial Analysis Intelligence Index and $2.59 per task on the Artificial Analysis Coding Agent Index within Grok Build
➤ Low cost for Grok 4.5 is driven by both low pricing and token efficiency. Grok 4.5 has a headline price over 60% lower than Claude Opus 4.8 and GPT-5.5, and used ~14k output tokens per Intelligence Index Task - over 60% lower than Opus 4.8. On the Coding Agent Index, Grok 4.5 stands out on the Pareto frontier of Coding Agent Index score vs. Total Tokens, using only 1.9M tokens for the Coding Agent Index while scoring 76
➤ As a coding agent, Grok 4.5 in Grok Build is on par with GPT-5.5 and offers efficiency benefits: In our Artificial Intelligence Coding Agent Index that consists of DeepSWE, Terminal-Bench v2, and SWE-Atlas QnA, Grok 4.5 in Grok Build ranks third, on par with GPT-5.5 (Codex) and below Fable 5 (Claude Code). It is also very efficient in achieving this result: Grok 4.5 in Grok Build cost $2.49 per task while Fable 5 in Claude Code cost $11.80 and GPT-5.5 in Codex $5.07. This is driven by relatively low token pricing and the model using far fewer tokens than comparable models (1.9M average tokens used per task), significantly less than Fable 5 in Claude Code (7.2M) and GPT-5.5 in Codex (6.2M)

Other model details:

➤ Context window of 500k tokens - a reduction from Grok 4.3’s 1M token context, but retaining configurable reasoning and vision input

➤ Pricing of $2/$6 per 1M tokens of input/output; cache hits are discounted by 75% to $0.5 per 1M tokens, and costs still double with long (>200k token) inputs

➤ As Elon Musk has disclosed, Grok 4.5 is 3x larger than its predecessor at 1.5T parameters

[SpaceXAI @SpaceXAI]

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.

https://t.co/i8HpU7w64k

[ClaudeDevs @ClaudeDevs]

https://t.co/dxoI9Nna86

[Horacio @horacio123]

@sami_fc @EstefMolina_ @jafgaqt El problema es el de siempre. La censura. Un país amordazado hablando de problemas laterales porque del central no se puede. ¿Quién no sabe cuál es el problema real? ¿Por qué estamos llenos de leyes y más leyes que bloquean la construcción "casualmente" muy discrecionales?

[Horacio @horacio123]

@migarci2 @javilop Y cuando se lee la normativa absurda y asfixiante existente en Europa, quien arriesga ese dinero que casualmente nunca es quien dice en qué hay que invertir, sale corriendo a San Francisco. ¿Se entiende mejor?

[Horacio @horacio123]

@Aspizc @jose_basa @javilop ¿Qué significa fuerte para usted? Porque la información general a la que se tiene acceso muestra una inversión bajísima.

[Horacio @horacio123]

@jose_basa @javilop Si lee la normativa no empieza. Europa solo existe para prohibir y exaccionar a sus habitantes. En España sus “empresaurios” siguen viviendo del BOE. En Europa Central se leyeron la normativa y se largaron a San Francisco.

[Horacio @horacio123]

@lacort La diferencia radica en qué es “usar” la IA. Un prompt hecho por usuarios con limitados conocimientos de IA o quienes utilicen sistemas profesionales.

[Google AI Studio @GoogleAIStudio]

https://t.co/ohyGvAO3w8