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How fast is serv-swift? Runs roughly 9× faster than frontier models like GPT 5.4 Here's the proof 👇

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OpenServ

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26,200 просмотров • 4 месяцев назад •via X (Twitter)

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ScaleDown just dropped task-specific small models that are 15x cheaper, 63x faster, and more accurate than GPT-5.4 Mini. Built for the 70-80% of AI workloads that never needed a frontier model in the first place.
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ScaleDown just dropped task-specific small models that are 15x cheaper, 63x faster, and more accurate than GPT-5.4 Mini. Built for the 70-80% of AI workloads that never needed a frontier model in the first place.

0xMarioNawfal

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You can now run three frontier models at once and select your orchestrator model directly inside Perplexity Computer. Model Council automatically runs GPT-5.4, Claude Opus 4.6 and Gemini 3.1 Pro simultaneously. Three frontier models. One workflow. Best answer wins.
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You can now run three frontier models at once and select your orchestrator model directly inside Perplexity Computer. Model Council automatically runs GPT-5.4, Claude Opus 4.6 and Gemini 3.1 Pro simultaneously. Three frontier models. One workflow. Best answer wins.

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Codex got more speed. With /fast mode, GPT-5.4 runs 1.5x faster with the same intelligence and reasoning. Move through coding tasks, iteration, and debugging while staying in flow.
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The first real evidence that the days of LLM Scaling laws are over. Introducing SCOPE: the world's most efficient Neural Planner. 🔍📊 We tested SCOPE vs Frontier LLMs for planning tasks on TextCraft (text version of Minecraft) and here are the results: ⤵️ - SCOPE Runs 55x faster than GPT 3.5 (3 seconds vs 164 seconds) - SCOPE is 160,000 smaller than GPT 4o (11M parameters vs 1.8T parameters) - SCOPE is more accurate on Planning tasks (56%) than frontier LLM models The age of efficient AI models starts now. 🔗📌 Read the full write up here:
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The first real evidence that the days of LLM Scaling laws are over. Introducing SCOPE: the world's most efficient Neural Planner. 🔍📊 We tested SCOPE vs Frontier LLMs for planning tasks on TextCraft (text version of Minecraft) and here are the results: ⤵️ - SCOPE Runs 55x faster than GPT 3.5 (3 seconds vs 164 seconds) - SCOPE is 160,000 smaller than GPT 4o (11M parameters vs 1.8T parameters) - SCOPE is more accurate on Planning tasks (56%) than frontier LLM models The age of efficient AI models starts now. 🔗📌 Read the full write up here:

Skyfall AI

49,052 просмотров • 7 месяцев назад

Holy moly, what is happening inside those frontier labs?! - AGI very close - Superintelligence also not far off - watching "how fast the models accelerate internally" ASI is very close - a *even faster* take-off not very fast off
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Holy moly, what is happening inside those frontier labs?! - AGI very close - Superintelligence also not far off - watching "how fast the models accelerate internally" ASI is very close - a *even faster* take-off not very fast off

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Mr. Kaspa

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Matt Maher tested frontier models in Cursor v. other harnesses. Cursor boosted model performance by 11% on average: Gemini: 52% → 57% GPT-5.4: 82% → 88% Opus: 77% → 93% His benchmark measures how well models implement a 100-feature PRD. Cursor consistently outperformed.
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Matt Maher tested frontier models in Cursor v. other harnesses. Cursor boosted model performance by 11% on average: Gemini: 52% → 57% GPT-5.4: 82% → 88% Opus: 77% → 93% His benchmark measures how well models implement a 100-feature PRD. Cursor consistently outperformed.

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LTX 2.3 is out. Another big milestone for open-source video generation. Lightricks keeps pushing the frontier with faster, higher-quality video models the community can actually build with. Open video models are accelerating fast. Model:

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The latest models from OpenAI – GPT-5.4 and GPT-5.3-Codex – are already in your JetBrains IDE. See how @niklas_wortmann uses Codex with Skills to get task updates on his phone.

JetBrains

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GPT 5.4 Computer Use is wild! 🤯 it's completely free if you're subscribed and unlocks tons of new things here's how you can use it 👇🏻
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GPT 5.4 Computer Use is wild! 🤯 it's completely free if you're subscribed and unlocks tons of new things here's how you can use it 👇🏻

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The strongest models are gated and access is granted only to a select few. Hermes Agent now exposes MoA presets as virtual models, giving you capabilities beyond the publicly available frontier: 8% higher than Opus 4.8 and 11% higher than GPT 5.5 on our upcoming benchmark.
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The strongest models are gated and access is granted only to a select few. Hermes Agent now exposes MoA presets as virtual models, giving you capabilities beyond the publicly available frontier: 8% higher than Opus 4.8 and 11% higher than GPT 5.5 on our upcoming benchmark.

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Here's how I'm generating game ready art assets for my vibe coded game; → No coding → No photoshop. → No asset packs. Instead I'm using → Codex CLI → GPT 5.4 → GPT Image 1.5 → Sora 2 Idle anims, walk cycles, attack, crouch, jump ... Full video tutorial + breakdown👇
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Here's how I'm generating game ready art assets for my vibe coded game; → No coding → No photoshop. → No asset packs. Instead I'm using → Codex CLI → GPT 5.4 → GPT Image 1.5 → Sora 2 Idle anims, walk cycles, attack, crouch, jump ... Full video tutorial + breakdown👇

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The value produced by models is getting so much better so fast that old hardware is actually getting *more* expensive to rent. 3 years ago, the best model you could run on a H100 chip was GPT-4. Now, you can run GPT-5.4 on it, which is smaller and cheaper to run while producing much more valuable tokens. w. Dylan Patel
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The value produced by models is getting so much better so fast that old hardware is actually getting *more* expensive to rent. 3 years ago, the best model you could run on a H100 chip was GPT-4. Now, you can run GPT-5.4 on it, which is smaller and cheaper to run while producing much more valuable tokens. w. Dylan Patel

Dwarkesh Patel

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Stop using frontier models for your entire OpenClaw stack. It's expensive and wastes your quota. The first step is identifying which use cases CAN be moved to local models. Here's how I do that:
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Stop using frontier models for your entire OpenClaw stack. It's expensive and wastes your quota. The first step is identifying which use cases CAN be moved to local models. Here's how I do that:

Matthew Berman

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Sam Altman says most people still think AI is just ChatGPT, but the frontier is far ahead Models now beat humans on the hardest contests; GPT-5 is yielding small, real discoveries The cost of intelligence is falling fast, while capabilities are rising "the world is just catching up"
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Sam Altman says most people still think AI is just ChatGPT, but the frontier is far ahead Models now beat humans on the hardest contests; GPT-5 is yielding small, real discoveries The cost of intelligence is falling fast, while capabilities are rising "the world is just catching up"

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Silico, the platform for ambitious AI research, is publicly available today. AI is advancing fast. The tools to understand it need to advance even faster. Silico lets you interpret and train your models at frontier scale. Learn more + get access 🧵

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Opus 4.7 cs GPT 5.4 “make a flappy bird clone” I’ve been running this test for a few models now and this test was the hardest to objectively say who did better. Opus grabbed another version game assets compared to GPT 5.4, - GPT 5.4 however, grabbed the correct game assets. Opus 4.7 beat it on creativity where it grabbed assets (maybe unknowingly) that had a much more diverse set, including nighttime modes and different bird colors GPT 5.4 was able to get the pacing of the game the first shot, whereas Opus had the game running much too fast and then much too slow. But was able to place the metal perfectly in the game card at the end where GPT 5.4 struggled over 10 iterations. All in all both models had essentially made a near perfect game after three shots and are far ahead of the competition in terms of reasoning and effort.

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423,821 просмотров • 4 месяцев назад