Las GPUs de Zuckerberg went brrrrr brrrrr para dar un salto necesario por estar en la carrera. Ahora toca mantener el ritmo!
BIG TECH
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Model Performance Near Opus, Gemini, GPT5 Without Notable Advantage
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El rendimiento del modelo lo coloca cerca de Opus 4.6, Gemini 3.1 y GPT 5.4 sin sobresalir notablemente en ninguna dimensión.
— Carlos Santana (@DotCSV) 8 avril 2026
Mi sensación es que han metido prisa para sacar y estar en la carrera a la vista de los movimientos de Anthropic y OpenAI.https://t.co/oHyzbjpSLXEl rendimiento del modelo lo coloca cerca de Opus 4.6, Gemini 3.1 y GPT 5.4 sin sobresalir notablemente en ninguna dimensión. Mi sensación es que han metido prisa para sacar y estar en la carrera a la vista de los movimientos de Anthropic y OpenAI.
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Anthropic Reaches $30B ARR Before Mythos Launch
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Amol (Head of Growth at @AnthropicAI
) just joined Twitter. Follow for free alpha. BTW, can you believe they hit $30B ARR before they even released Mythos? -
Meta Launches Muse AI Model Line After Llama 4 Setback
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META RETURNS TO THE BATTLE! After the failure of Llama 4, Meta has spent the last year completely reorienting its entire AI strategy, and today it finally unveils its first (private) model, aiming to go head-to-head with the big players through its new Muse model line
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Meta’s Muse Spark: Multimodal AI Model with Impressive Reasoning Benchmarks
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Meta Superintelligence Labsjust dropped Muse Spark, their first model after a full nine-month rebuild of their AI stack. the tl;dr (summary) It's a natively multimodal reasoning model that now powers Meta AI. It's competitive on reasoning and multimodal benchmarks, introduces a multi-agent "Contemplating mode," and Meta frames it as step one on a scaling ladder toward "personal superintelligence." Where it's strong: -Multimodal perception and visual reasoning (visual STEM, entity recognition, localization) -Health reasoning, built with input from 1,000+ physicians -Test-time reasoning efficiency, using thinking time penalties to compress reasoning tokens -Contemplating mode hits 58% on Humanity's Last Exam and 38% on FrontierScience Research, putting it in the ballpark of Gemini Deep Think and GPT Pro -Pretraining efficiency: reaches the same capability as Llama 4 Maverick with over 10x less compute Where it's weaker (Meta's own admission): -Long-horizon agentic systems -Coding workflows Key scaling findings: -RL compute scales smoothly with log-linear growth on pass@1 and pass@16 -Multi-agent orchestration scales performance without proportional latency increase -Phase transition behavior on AIME: the model first extends reasoning, then compresses it under length penalties, then extends again for higher accuracy My take: very good model, really surprised what meta offered here. And keep in mind: 99% of all instagram / facebook user dont need an LLM for doing academic reserach but for everyday reasoning. Well done, meta! Chubby♨️ (@kimmonismus) Lol what?! Meta has been cooking! These benchmarks are really freaking good holy!! — https://nitter.net/kimmonismus/status/2041918006779957407#m
→ View original post on X — @kimmonismus, 2026-04-08 16:42 UTC
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OpenAI and X: Concerns Over AI Safety Restraint
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the biggest fear as noted is that openai and x (and perhaps others) would not show the same restraint.
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Meta’s New Muse Spark Model Delivers Impressive Benchmark Results
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Lol what?! Meta has been cooking! These benchmarks are really freaking good holy!! Alexandr Wang (@alexandr_wang) 1/ today we're releasing muse spark, the first model from MSL. nine months ago we rebuilt our ai stack from scratch. new infrastructure, new architecture, new data pipelines. muse spark is the result of that work, and now it powers meta ai. 🧵 — https://nitter.net/alexandr_wang/status/2041909376508985381#m
→ View original post on X — @kimmonismus, 2026-04-08 16:36 UTC
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Meta’s Muse Spark Rises to 4th in AI Arena
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Meta jumped from last to the 4th place on Artificial Analysis arena with its newly released Muse Spark model. It also appears to be token efficient for its level of intelligence.
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Meta’s Muse Spark Returns Company to Frontier AI Race
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Meta is back! Muse Spark scores 52 on the Artificial Analysis Intelligence Index, behind only Gemini 3.1 Pro, GPT-5.4, and Claude Opus 4.6. Muse Spark is the first new release since Llama 4 in April 2025 and also Meta's first release that is not open weights Muse Spark is a new model from @Meta evaluated on Artificial Analysis. We were given early access by Meta to independently benchmark the model. It is the first frontier-class model from Meta since Llama 4 Maverick was released in April 2025, and notably the first @AIatMeta model that is not being released as open weights. The release follows Meta's reorganization of its AI efforts under Meta Superintelligence Labs, and signals that Meta is re-entering the frontier race after roughly a year of relative quiet. For context, Llama 4 Maverick and Scout scored 18 and 13 respectively on the Artificial Analysis Intelligence Index as non-reasoning models at the time of their release, while Muse Spark scores 52. Muse Spark essentially closes the gap between to the frontier in a single release. The model is not open source and is not yet accessible via an API but Meta has shared they expect this to come soon. Meta is also integrating Muse Spark into their first party products including their Meta AI chat product, Facebook, Instagram and Threads. Key takeaways from our benchmarks: ➤ Muse Spark scores 52 on the Artificial Analysis Intelligence Index, placing it within the top 5 models we have benchmarked. It sits ahead of Claude Sonnet 4.6, GLM-5.1, MiniMax-M2.7, Grok 4.20 and behind Gemini 3.1 Pro Preview, GPT-5.4 and Claude Opus 4.6 ➤ Muse Spark is notably token efficient for its intelligence level. It used 58M output tokens to run the Intelligence Index, comparable to Gemini 3.1 Pro Preview (57M) and notably lower than Claude Opus 4.6 (Adaptive Reasoning, max effort, 157M), GPT-5.4 (xhigh, 120M) and GLM-5 (110M) ➤ Muse Spark is the second-most capable vision model we have benchmarked. It scores 80.5% on MMMU-Pro, behind only Gemini 3.1 Pro Preview (82.4%) ➤ Muse Spark performs strongly on reasoning and instruction-following evaluations. It scores 39.9% on HLE, trailing only Gemini 3.1 Pro Preview (44.7%) and GPT-5.4 (xhigh, 41.6%). The model also achieved 5th highest in CritPT with a score of 11%, an eval that is focused on difficult physics research questions. This is substantially above above Gemini 3 Flash (9%) and Claude 4.6 Sonnet (3%) ➤ Agentic performance does not stand out. On GDPval-AA, our evalaution focused on real world work tasks, Muse Spark scores 1427, behind both Claude Sonnet 4.6 at 1648 and GPT-5.4 at 1676, but ahead of Gemini 3.1 Pro Preview at 1320. On On TerminalBench Hard, Muse Spark trails Claude Sonnet 4.6, GPT-5.4, and Gemini 3.1 Pro. Muse Spark joins others in achieving a high τ²-Bench Telecom score of 92% Key model details: ➤ Modalities: Multimodal including text and vision input, text output ➤ License: Proprietary, Meta's first frontier model not released as open weights ➤ Availability: No public API at the time of publishing. Meta expects to provide API access soon. Meta has started integration into their first party AI offering Meta AI and inside Facebook, Instagram, and Threads
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Meta Unveils Muse Spark and Contemplating Mode
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BREAKING : META ANNOUNCED MUSE SPARK, THE FIRST MSL MODEL, AND A NEW MUSE SPARK CONTEMPLATING MODE! Muse Spark Contemplating mode scored 58.4% on HLE with tools! "We’re also releasing Contemplating mode, which orchestrates multiple agents that reason in parallel. This allows