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Meet Gen-1 Slides, Genspark’s first model designed for knowledge work. Trained with Fireworks from an open-weight base, Gen-1 Slides now powers Standard mode in Genspark AI Slides, delivering frontier quality decks at roughly 1/17th of Opus 5’s price. Fewer midnight fixes. Better decks by default. Read the full blog:

Genspark

61,745 subscribers

66,674 次观看 • 7 天前 •via X (Twitter)

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16 条评论

Jordan Zaby 的头像

Jordan Zaby7 天前

@FireworksAI_HQ Because Genspark has always been the best tool for Slides!

Genspark 的头像

Genspark7 天前

@FireworksAI_HQ THank you!

Vivek Chauhan 的头像

Vivek Chauhan7 天前

@FireworksAI_HQ Congratulation ! it has been great collaborating with your team on this

Vivian Clark 的头像

Vivian Clark7 天前

@FireworksAI_HQ Genspark is such an amazing company. Really impressed by what the team has built.

Genspark 的头像

Genspark7 天前

@FireworksAI_HQ Thank you, this means a lot!

Tanvir Anjum 的头像

Tanvir Anjum7 天前

@FireworksAI_HQ Affordable frontier-quality slides could change knowledge work.

Pranay Bhatia 的头像

Pranay Bhatia7 天前

@FireworksAI_HQ Congrats @genspark_ai, amazing to partner with you in training a model that matches frontier quality!

Loukman 的头像

Loukman7 天前

@FireworksAI_HQ building slides with html will never solve this unfortunately

Aina Oluwatobi 的头像

Aina Oluwatobi7 天前

@FireworksAI_HQ Let’s lower the price of models, and still giving us good qualities 🙌🙌

Genspark 的头像

Genspark7 天前

@FireworksAI_HQ More models with great quality and cheaper price are on the way!

Punkesh 的头像

Punkesh7 天前

@FireworksAI_HQ I had been wasting so much time in building front end skills and hacking repos to solve deck slop! Is this open weights too?

Genspark 的头像

Genspark7 天前

@FireworksAI_HQ Let us know what you think! Gen-1 is not open-weight but does come standard with every plan on Genspark

Evelyn 的头像

Evelyn6 天前

@FireworksAI_HQ Gen-1 Slides looks like a powerful step forward for faster, high-quality knowledge work

Genspark 的头像

Genspark6 天前

@FireworksAI_HQ Try it out and let us know what you think!

pedro 的头像

pedro7 天前

@FireworksAI_HQ I have a question: why don't they integrate it into the chat and eliminate the GPT-5 Pro model family—which costs between $168 and $180 at launch—while Astra costs only $50?

Blake Thompson 的头像

Blake Thompson6 天前

@FireworksAI_HQ This is a huge step for AI-powered presentations. Better quality at a fraction of the cost is exactly what knowledge workers need.

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GEN-1 plays the 🐚 shell game, trained on just 1 hr of robot data. It also generalizes to unseen objects, like berkay 's car keys. Physical AI models should be capable of benchmark tasks like this one. It's interesting for the all the reasons Rhoda AI calls out -- requires visual memory, and the model must track the cups from the very start, at high frame rates. Interestingly, GEN-1 appears to exhibit a degree of "active perception." It's subtle; the hands can sometimes appear to "follow" the cups, using its own movements to help attend to where it thinks the object should be. Read more about GEN-1 in our blog post in the comments below ↓

GEN-1 plays the 🐚 shell game, trained on just 1 hr of robot data. It also generalizes to unseen objects, like berkay 's car keys. Physical AI models should be capable of benchmark tasks like this one. It's interesting for the all the reasons Rhoda AI calls out -- requires visual memory, and the model must track the cups from the very start, at high frame rates. Interestingly, GEN-1 appears to exhibit a degree of "active perception." It's subtle; the hands can sometimes appear to "follow" the cups, using its own movements to help attend to where it thinks the object should be. Read more about GEN-1 in our blog post in the comments below ↓

Generalist

862,623 次观看 • 4 个月前

Say hi to OK Computer, Kimi's agent mode 🤖🎸 Your AI product & engineering team, all in one. ✨ From chat → multi-page websites, mobile first designs, editable slides ✨ From up to 1 million rows of data → interactive dashboards ✨ Agency: self-scopes, surveys & designs ✨ Natively trained on tools: file system, browser, terminal ✨ More steps, tokens & tools than chat mode, with turbo K2 An agentic model with its own computer, K2 now has true agency.

Say hi to OK Computer, Kimi's agent mode 🤖🎸 Your AI product & engineering team, all in one. ✨ From chat → multi-page websites, mobile first designs, editable slides ✨ From up to 1 million rows of data → interactive dashboards ✨ Agency: self-scopes, surveys & designs ✨ Natively trained on tools: file system, browser, terminal ✨ More steps, tokens & tools than chat mode, with turbo K2 An agentic model with its own computer, K2 now has true agency.

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303,057 次观看 • 11 个月前

Introducing Genspark AI Slides 5.0. Our biggest upgrade to AI Slides yet. The biggest leap? Slide Skills. Reusable assets that bundle expert thinking and polished design, ready in one click. Here's everything new in 5.0: - 100+ Expert Skills built in. We've packed the thinking of the world's top experts, across consulting, sales, teaching, and more. Apply with one click, and their expertise becomes yours. - Build your own Skill. Upload a deck or PDF, describe the analysis steps, and lock in your team's style. - 5× faster, higher quality. Powered by next-gen architecture and the most powerful models. - Built-in data analysis. Crunches your Excel and Sheets data into presentation-ready insights. Every deck thinks like an expert. Try it now → 🎉 50% off AI Slides 5.0 credits, 14 days only

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Genspark

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GREG ISENBERG

62,172 次观看 • 11 个月前

Today at AGI Playground, GeekPark (GeekPark)'s first Singapore edition, Genspark (Genspark) open-sourced its full-featured AI Office, GenOffice. Co-Founder & CEO, Eric Jing (Eric Jing) sat down with GeekPark Founder Jack Zhang (Jack Zhang) to talk through the thinking behind it, and for the first time, the story of how Genspark got here. The moments worth the timestamp: 04:08 "Sonnet 3.7 was the first model that enabled an end-to-end full agent." 11:20 "All-in-one is the future. It is about all-in-one context, not one interface with many features." 17:54 "People questioned who makes business decks in HTML. But HTML is the most familiar format for large language models." 28:17 "We're not an agent company. We're an AI company." 32:21 "The price of today's intelligence will drop a hundred times in two years. AI models will become a commodity." Full episode:

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GeekPark

346,930 次观看 • 1 个月前

he tested 5760 architectures at Google for a full year. the winner was the original Transformer from 2017. Hyung Won Chung told that story at MIT with a small smile. then went to OpenAI and trained o1. 1 hour. free. by one of the few people on earth who actually moves the frontier. meanwhile your feed is full of guys writing architecture threads who have never trained a model anyone uses. he just told MIT that 99% of AI research is theater. your AI worldview was built by men who read his papers. badly. now you can read him directly. you will rewatch this. save it now.

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Raytar

107,152 次观看 • 3 个月前

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Shensi Ding

523,051 次观看 • 1 个月前

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Anthropic's in trouble, again. The entire Claude experience is now available at 1/6th the price. Kimi now does everything Claude does, powered by K2.6, a 1-trillion-parameter MoE model that activates only 32B parameters per token. It covers all three features Claude has (Chat, Code, and Cowork): 1) Kimi Chat runs in four modes - Instant for fast responses - Thinking for deep reasoning - Agent for multi-step execution - and Agent Swarm for parallel workloads. There's a 262K context window across all of them. 2) Kimi Code is the open-source CLI coding agent with K2.6 as the default backend. K2.6 ranked #1 on OpenRouter's programming leaderboard by weekly usage. 3) Kimi Agent is the Cowork equivalent. It generates: - full websites with database and auth - presentation decks (editable PPTX output) - spreadsheets with formulas and charts - word docs and structured research reports. On top of this, Kimi K2.6 is also trained to decompose tasks into up to 300 parallel sub-agents. This helps it retain coherence even across 4,000+ tool calls in a single run, with sessions sustaining up to 13 hours. On SWE-Bench Pro: - Kimi K2.6 → 58.6 - GPT-5.4 xhigh → 57.7 - Gemini 3.1 Pro → 54.2 - Claude Opus 4.6 → 53.4 Kimi K2.6 model is open weights and self-hostable on 4x H100s in INT4. Find the link to the HuggingFace model page in the replies!

Avi Chawla

110,057 次观看 • 4 个月前

I couldn't believe the results of this benchmarking test. I blind-tested 6 frontier models — Sonnet 5, Opus 4.8, Fable 5, GPT 5.5, GLM 5.2, and Kimi 2.5 — on knowledge work, not engineering. Writing. Analysis. Design. Vibe coding. Subagent simulations. The stuff we actually do all day. Same prompts, each model running its own subagent, every output graded blind before the labels were revealed. The results: → GLM 5.2 (the dirt-cheap open-source model from China) took first → Sonnet 5 took second, beating Fable 5 for knowledge work → Opus 4.8 got whooped Then I had Composer 2.5 judge every output independently — and it picked Fable 5 almost across the board. My blind picks and the AI judge completely disagreed. Full breakdown, method, and prompts in the video below. Which model are you running as your daily driver right now?

I couldn't believe the results of this benchmarking test. I blind-tested 6 frontier models — Sonnet 5, Opus 4.8, Fable 5, GPT 5.5, GLM 5.2, and Kimi 2.5 — on knowledge work, not engineering. Writing. Analysis. Design. Vibe coding. Subagent simulations. The stuff we actually do all day. Same prompts, each model running its own subagent, every output graded blind before the labels were revealed. The results: → GLM 5.2 (the dirt-cheap open-source model from China) took first → Sonnet 5 took second, beating Fable 5 for knowledge work → Opus 4.8 got whooped Then I had Composer 2.5 judge every output independently — and it picked Fable 5 almost across the board. My blind picks and the AI judge completely disagreed. Full breakdown, method, and prompts in the video below. Which model are you running as your daily driver right now?

JJ Englert

10,737 次观看 • 2 个月前

Chamath is making one of the most important business arguments of 2026. Half of large US companies right now cannot generate returns that exceed their cost of capital, which has normalized back to its long run average of 8 to 11%. Another one in seven companies globally is stuck generating persistent returns between 1 and 5% and most businesses don't have room for error and in this environment walks every frontier AI lab saying the same thing, give us your data, your workflows, your processes and our model will make everything better. And companies by the millions said yes. What they didn't fully account for is what happens on the other side of that door. Every time an employee runs a query through a frontier model API, the prompt goes through external servers, workflows, customer data, pricing logic, internal processes, all of it transmitted through a third party. As Alex Karp said companies are spending on tokens while handing over the exact proprietary advantages that make their business worth owning. Microsoft blocked internal use of Anthropic's Claude Fable 5 but over its 30-day data retention policy and the largest software company in the world decided a frontier model's data handling was too risky for its own employees. A US government action revoked access to another frontier model for foreign nationals overnight. Now here's where the cost math becomes impossible to ignore. Deutsche Bank calculated a roughly 65x cost gap between frontier models like Claude Fable 5 at ~$3.25 per task and open-source alternatives at ~$0.05. For 90% of everyday enterprise tasks, performance is comparable. Open-weight models now match closed frontier systems on core agent tasks at roughly one-tenth the cost, a high-volume deployment that costs $250/day on Claude runs at $12/day on an open-source equivalent. Chamath Palihapitiya tested this directly by running a standard enterprise code migration task through an orchestration layer wrapping an open-source model came in 16.4x cheaper than using a frontier model directly.

Chamath is making one of the most important business arguments of 2026. Half of large US companies right now cannot generate returns that exceed their cost of capital, which has normalized back to its long run average of 8 to 11%. Another one in seven companies globally is stuck generating persistent returns between 1 and 5% and most businesses don't have room for error and in this environment walks every frontier AI lab saying the same thing, give us your data, your workflows, your processes and our model will make everything better. And companies by the millions said yes. What they didn't fully account for is what happens on the other side of that door. Every time an employee runs a query through a frontier model API, the prompt goes through external servers, workflows, customer data, pricing logic, internal processes, all of it transmitted through a third party. As Alex Karp said companies are spending on tokens while handing over the exact proprietary advantages that make their business worth owning. Microsoft blocked internal use of Anthropic's Claude Fable 5 but over its 30-day data retention policy and the largest software company in the world decided a frontier model's data handling was too risky for its own employees. A US government action revoked access to another frontier model for foreign nationals overnight. Now here's where the cost math becomes impossible to ignore. Deutsche Bank calculated a roughly 65x cost gap between frontier models like Claude Fable 5 at ~$3.25 per task and open-source alternatives at ~$0.05. For 90% of everyday enterprise tasks, performance is comparable. Open-weight models now match closed frontier systems on core agent tasks at roughly one-tenth the cost, a high-volume deployment that costs $250/day on Claude runs at $12/day on an open-source equivalent. Chamath Palihapitiya tested this directly by running a standard enterprise code migration task through an orchestration layer wrapping an open-source model came in 16.4x cheaper than using a frontier model directly.

Milk Road AI

281,771 次观看 • 2 个月前

DELL ASUS ACER AND GIGABYTE ALL SHIPPED $2,999 DGX SPARK CLONES IN THE SAME QUARTER, SAMSUNG GEN 5 SSD CHOICE CAUSES 2X PERFORMANCE GAPS, THE LOCAL AI HARDWARE MAP JUST GREW BY FOUR FRONTIER TIER OPTIONS 02:13 the reviewer flips through the spec sheets, "we saw major differences in the SSD, some are using Gen 4 SSDs which will slow these platforms down, others have Gen 5 Samsung drives, Samsung is the leader by almost a factor of two" NVIDIA's GB10 Grace Blackwell reference board got picked up by Dell, Asus, Acer and Gigabyte in the same quarter, four $2,999 mini boxes with 128GB unified memory and 1 PFLOP of AI throughput from competing OEMs the Asus version runs coolest across GPU, CPU and SSD thanks to an unpainted bottom plate and a copper heatsink element, the Acer leads on price-to-perf, the Dell honeycomb intake actually restricts airflow slightly, the gigabyte sits middle of pack Samsung Gen 5 versus Gen 4 inside the same chassis causes a 2x read-write gap for the exact same $2,999 sticker, the buyer who reads the SSD spec sheet gets a 70B model loading in 4 seconds, the one who doesn't waits 8 your serie's frontier tier was the $1,700 EVO-X2, four DGX Spark OEM clones at $2,999 extend the map upward, the local AI hardware boom is now staffed by every major PC vendor not just AMD and apple, the category fully arrived bookmark this and read the article below

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starmex

17,573 次观看 • 2 个月前

Today we’re announcing @kodezi Chronos-1. After years of research, iteration, and failure, we’ve built something radically new. Chronos-1 is the world's first large language model purpose-built for debugging. Unlike LLMs that just autocomplete, Chronos-1 understands, diagnoses, and heals code.While most LLMs are trained to generate code, Chronos-1 is trained to investigate, remember, and resolve it. What makes Chronos-1 different: - Debugging-first architecture - Multi-level memory engine trained on millions of bugs, logs, and test cases - Adaptive retrieval that scales to entire codebases - 23% better bug detection and 40% fewer debugging cycles in real-world evaluation - Native integrations with IDEs, CI/CD, and observability workflows Chronos-1 powers Kodezi OS, your AI-native CTO that autonomously maintains, evolves, and governs your codebase. Kodezi OS exits beta in Q1 of 2026. We’ve raised a fresh round of funding and are focused on becoming the leader in code maintenance. We’re hiring cracked engineering and product talent, with base starting at $200K. If you’re interested in building the future of code maintenance and helping shape how software heals and improves itself, message me.

Today we’re announcing @kodezi Chronos-1. After years of research, iteration, and failure, we’ve built something radically new. Chronos-1 is the world's first large language model purpose-built for debugging. Unlike LLMs that just autocomplete, Chronos-1 understands, diagnoses, and heals code.While most LLMs are trained to generate code, Chronos-1 is trained to investigate, remember, and resolve it. What makes Chronos-1 different: - Debugging-first architecture - Multi-level memory engine trained on millions of bugs, logs, and test cases - Adaptive retrieval that scales to entire codebases - 23% better bug detection and 40% fewer debugging cycles in real-world evaluation - Native integrations with IDEs, CI/CD, and observability workflows Chronos-1 powers Kodezi OS, your AI-native CTO that autonomously maintains, evolves, and governs your codebase. Kodezi OS exits beta in Q1 of 2026. We’ve raised a fresh round of funding and are focused on becoming the leader in code maintenance. We’re hiring cracked engineering and product talent, with base starting at $200K. If you’re interested in building the future of code maintenance and helping shape how software heals and improves itself, message me.

Ishraq Khan

125,422 次观看 • 9 个月前

5 patterns in Text Arena's price–performance Pareto frontier since 2023: 1. GPT-4-level quality is now ~500x lower cost. - From a ~$50 blended price per million tokens in 2023 to ~$0.10 today. 2. The higher-price end is both better and lower-priced since 2023. - The leading Arena score has climbed ~170 points (1,330 → 1,500). While the price of the higher-end frontier models dropped from ~$50 to ~$20 per million tokens. 3. The low-cost end gained the most. - Under $0.20 per million tokens, the best available model went from ~1,000 Arena score in 2023 to ~1,440 today. 4. The low-cost/top performance gap has nearly closed. - In 2023, sub-$0.20 models trailed the leader by ~350 Arena points. Today, ~60. 5. The cast has rotated quite a bit. - - OpenAI set the 2023–24 benchmark. - AI at Meta strengthened the low-cost end in 2024. - Google DeepMind drove the 2025 jump. - Anthropic holds the peak in 2026. - xAI and Chinese labs like DeepSeek AI, Z.ai, Kimi.ai, Xiaomi MiMo, and Qwen are continuing to push the mid-price frontier.

5 patterns in Text Arena's price–performance Pareto frontier since 2023: 1. GPT-4-level quality is now ~500x lower cost. - From a ~$50 blended price per million tokens in 2023 to ~$0.10 today. 2. The higher-price end is both better and lower-priced since 2023. - The leading Arena score has climbed ~170 points (1,330 → 1,500). While the price of the higher-end frontier models dropped from ~$50 to ~$20 per million tokens. 3. The low-cost end gained the most. - Under $0.20 per million tokens, the best available model went from ~1,000 Arena score in 2023 to ~1,440 today. 4. The low-cost/top performance gap has nearly closed. - In 2023, sub-$0.20 models trailed the leader by ~350 Arena points. Today, ~60. 5. The cast has rotated quite a bit. - - OpenAI set the 2023–24 benchmark. - AI at Meta strengthened the low-cost end in 2024. - Google DeepMind drove the 2025 jump. - Anthropic holds the peak in 2026. - xAI and Chinese labs like DeepSeek AI, Z.ai, Kimi.ai, Xiaomi MiMo, and Qwen are continuing to push the mid-price frontier.

Arena.ai

58,356 次观看 • 3 个月前

Introducing Modern Claudefare Built fully with Opus 5 on High Mode over a few days using principles from Matt Shumer’s Gauntlet Loop - 84,100 lines of code Includes remakes of 4 beloved maps: 0:00 - Rust 0:40 - Highrise 0:57 - Nuketown 1:26 - Terminal Solo & multiplayer (w/ voice chat), bots included Tools used: - Three.js as core Javascript 3D library (all 20 guns and 4 maps generated by the model in code) - MeshyAI for 3D models + rigging + animations of 8 soldiers, 1 helicopter (highrise) and 1 bus (nuketown) - ElevenLabs for 430+ SFX, Music & TTS generations Play it now at (More details in thread)

Introducing Modern Claudefare Built fully with Opus 5 on High Mode over a few days using principles from Matt Shumer’s Gauntlet Loop - 84,100 lines of code Includes remakes of 4 beloved maps: 0:00 - Rust 0:40 - Highrise 0:57 - Nuketown 1:26 - Terminal Solo & multiplayer (w/ voice chat), bots included Tools used: - Three.js as core Javascript 3D library (all 20 guns and 4 maps generated by the model in code) - MeshyAI for 3D models + rigging + animations of 8 soldiers, 1 helicopter (highrise) and 1 bus (nuketown) - ElevenLabs for 430+ SFX, Music & TTS generations Play it now at (More details in thread)

Rishi

283,306 次观看 • 1 个月前

Open-sourcing GenOffice, the world's first full-featured open-source AI Office for PC and Mac. GenOffice is free for everyone, ad-free. All the editing tools you'd expect, no strings attached. How it started? One engineer, one week, $10,000 in tokens. That's what it took to build the GenOffice Alpha. Help shape the AI office experience We invite you to build the rest of it with us. Join the GenOffice group chat on GenTeam and bring your requests straight to the agent. Not by writing code, but by telling it what you want. You say what you need, and every piece of your feedback becomes part of the product. What's in GenOffice? Docs, Sheets, Slides, and PDF, with all the editing tools you already know. And with Genspark Super Agent built in, powered by top-tier models, it digs into research, crunches your data, then writes the doc or builds the deck for you, using your Genspark credits. This is an Alpha, and we mean it. Come tell us what's broken and what's missing. Everyone who jumps in with real feedback gets 1,000+ Genspark credits as a thank you. GitHub 👉 Download it now 👉

Open-sourcing GenOffice, the world's first full-featured open-source AI Office for PC and Mac. GenOffice is free for everyone, ad-free. All the editing tools you'd expect, no strings attached. How it started? One engineer, one week, $10,000 in tokens. That's what it took to build the GenOffice Alpha. Help shape the AI office experience We invite you to build the rest of it with us. Join the GenOffice group chat on GenTeam and bring your requests straight to the agent. Not by writing code, but by telling it what you want. You say what you need, and every piece of your feedback becomes part of the product. What's in GenOffice? Docs, Sheets, Slides, and PDF, with all the editing tools you already know. And with Genspark Super Agent built in, powered by top-tier models, it digs into research, crunches your data, then writes the doc or builds the deck for you, using your Genspark credits. This is an Alpha, and we mean it. Come tell us what's broken and what's missing. Everyone who jumps in with real feedback gets 1,000+ Genspark credits as a thank you. GitHub 👉 Download it now 👉

Genspark

517,082 次观看 • 1 个月前

We’re releasing our Code Migration benchmark — and we managed to get Fable tested in time Code migration carries real economic weight. COBOL powers banks, payrolls, government services, and underpins nearly 95% of US ATM transactions. The danger with any migration is that a model ships code that looks right but quietly drops essential behaviors We evaluated models in three ways: modern to modern migrations, legacy to modern migrations and on their overall code quality. Each model rebuilds the program in an offline sandbox, then is scored on a hidden behavior test with anti-cheat checks that catch anything wrapping the original, copying reference files, or staying in the source language Fable 5 leads overall at 55%, but costs $115.43 per test, while Opus 4.8 (47%), and GPT 5.5 (45%) cost $30.51 and $6.44, respectively, making GPT 5.5 the most cost efficient model. Kimi K2.6 is the #1 open-weight model (28%) priced at $5.12, ranking above some frontier models

We’re releasing our Code Migration benchmark — and we managed to get Fable tested in time Code migration carries real economic weight. COBOL powers banks, payrolls, government services, and underpins nearly 95% of US ATM transactions. The danger with any migration is that a model ships code that looks right but quietly drops essential behaviors We evaluated models in three ways: modern to modern migrations, legacy to modern migrations and on their overall code quality. Each model rebuilds the program in an offline sandbox, then is scored on a hidden behavior test with anti-cheat checks that catch anything wrapping the original, copying reference files, or staying in the source language Fable 5 leads overall at 55%, but costs $115.43 per test, while Opus 4.8 (47%), and GPT 5.5 (45%) cost $30.51 and $6.44, respectively, making GPT 5.5 the most cost efficient model. Kimi K2.6 is the #1 open-weight model (28%) priced at $5.12, ranking above some frontier models

Vals AI

16,990 次观看 • 3 个月前

fable 5.1 vs fable 5 vs opus 5 – three lord of the rings landmarks, built in 3d from one image the setup: one reference image per scene, one html file per build, everything procedural – no meshes, no textures, no image files, nothing past Three.js from a cdn. each model reads the picture, writes its own prompt from it, then builds to that prompt in the same turn. three named camera shots per scene on keys 1/2/3, so it can be screen-recorded. run through OpenRouter tasks: 1. bag end – hobbiton from two frames, outside and in. the round green door has to open onto the room you are standing in 2. barad-dûr – the tower and orodruin from one film still. the eye has to move and track the camera, the volcano erupts on a cycle, the clouds never stop 3. rivendell – jerry vanderstelt's painting. sun shafts that shimmer, water that falls without a break, trees that sway on a gust models: Anthropic fable 5.1, fable 5, opus 5 total cost, three builds #1 fable 5 – $14.97 #2 opus 5 – $18.53 #3 fable 5.1 – $22.38 wall clock, three builds #1 fable 5 – 38m #2 fable 5.1 – 92m #3 opus 5 – 122m output tokens #1 fable 5 – 298,592 #2 fable 5.1 – 439,435 #3 opus 5 – 724,418 lines of code shipped #1 fable 5 – 2,885 #2 fable 5.1 – 4,021 #3 opus 5 – 5,161 biggest single build, lines #1 opus 5, bag end – 2,410 #2 fable 5.1, barad-dûr – 1,375 #3 fable 5, bag end – 1,319 observations: • fable 5.1 is the only model that furnished the bag end interior – a live fire, panelling, books on the floor, leaded diamond windows, against fable 5's flat color and opus's dark tunnel. the round door outside opens onto that room, the hard part of the brief • what it costs is thinking room. the 128k output ceiling is a thinking budget in disguise: fable 5.1 burned 102,116 of it on reasoning and hit the wall mid-file. opus spent 109,241 and hit the same wall. fable 5 spent 61,240 and finished bag end in one call – the only one that did • fable 5.1's first pass is not the finished thing. its barad-dûr came back with three defects you only catch by looking at it – nothing a read of the code would have flagged • it is the best of the three at being corrected. handed a plain list of what was wrong, it returned 32 targeted patches over two rounds, every one applied first try, and it worked out one of the causes itself instead of guessing at constants conclusion: nine scenes, 12,067 lines and 1.46m output tokens for $55.88 all in – and the cheapest model was also the fastest, by 3.2x! follow thehype. for 24/7 ai news, analysis and breakdowns

fable 5.1 vs fable 5 vs opus 5 – three lord of the rings landmarks, built in 3d from one image the setup: one reference image per scene, one html file per build, everything procedural – no meshes, no textures, no image files, nothing past Three.js from a cdn. each model reads the picture, writes its own prompt from it, then builds to that prompt in the same turn. three named camera shots per scene on keys 1/2/3, so it can be screen-recorded. run through OpenRouter tasks: 1. bag end – hobbiton from two frames, outside and in. the round green door has to open onto the room you are standing in 2. barad-dûr – the tower and orodruin from one film still. the eye has to move and track the camera, the volcano erupts on a cycle, the clouds never stop 3. rivendell – jerry vanderstelt's painting. sun shafts that shimmer, water that falls without a break, trees that sway on a gust models: Anthropic fable 5.1, fable 5, opus 5 total cost, three builds #1 fable 5 – $14.97 #2 opus 5 – $18.53 #3 fable 5.1 – $22.38 wall clock, three builds #1 fable 5 – 38m #2 fable 5.1 – 92m #3 opus 5 – 122m output tokens #1 fable 5 – 298,592 #2 fable 5.1 – 439,435 #3 opus 5 – 724,418 lines of code shipped #1 fable 5 – 2,885 #2 fable 5.1 – 4,021 #3 opus 5 – 5,161 biggest single build, lines #1 opus 5, bag end – 2,410 #2 fable 5.1, barad-dûr – 1,375 #3 fable 5, bag end – 1,319 observations: • fable 5.1 is the only model that furnished the bag end interior – a live fire, panelling, books on the floor, leaded diamond windows, against fable 5's flat color and opus's dark tunnel. the round door outside opens onto that room, the hard part of the brief • what it costs is thinking room. the 128k output ceiling is a thinking budget in disguise: fable 5.1 burned 102,116 of it on reasoning and hit the wall mid-file. opus spent 109,241 and hit the same wall. fable 5 spent 61,240 and finished bag end in one call – the only one that did • fable 5.1's first pass is not the finished thing. its barad-dûr came back with three defects you only catch by looking at it – nothing a read of the code would have flagged • it is the best of the three at being corrected. handed a plain list of what was wrong, it returned 32 targeted patches over two rounds, every one applied first try, and it worked out one of the causes itself instead of guessing at constants conclusion: nine scenes, 12,067 lines and 1.46m output tokens for $55.88 all in – and the cheapest model was also the fastest, by 3.2x! follow thehype. for 24/7 ai news, analysis and breakdowns

thehype.

18,509 次观看 • 15 天前

🎥 Today we’re premiering Meta Movie Gen: the most advanced media foundation models to-date. Developed by AI research teams at Meta, Movie Gen delivers state-of-the-art results across a range of capabilities. We’re excited for the potential of this line of research to usher in entirely new possibilities for casual creators and creative professionals alike. More details and examples of what Movie Gen can do ➡️ 🛠️ Movie Gen models and capabilities Movie Gen Video: 30B parameter transformer model that can generate high-quality and high-definition images and videos from a single text prompt. Movie Gen Audio: A 13B parameter transformer model that can take a video input along with optional text prompts for controllability to generate high-fidelity audio synced to the video. It can generate ambient sound, instrumental background music and foley sound — delivering state-of-the-art results in audio quality, video-to-audio alignment and text-to-audio alignment. Precise video editing: Using a generated or existing video and accompanying text instructions as an input it can perform localized edits such as adding, removing or replacing elements — or global changes like background or style changes. Personalized videos: Using an image of a person and a text prompt, the model can generate a video with state-of-the-art results on character preservation and natural movement in video. We’re continuing to work closely with creative professionals from across the field to integrate their feedback as we work towards a potential release. We look forward to sharing more on this work and the creative possibilities it will enable in the future.

🎥 Today we’re premiering Meta Movie Gen: the most advanced media foundation models to-date. Developed by AI research teams at Meta, Movie Gen delivers state-of-the-art results across a range of capabilities. We’re excited for the potential of this line of research to usher in entirely new possibilities for casual creators and creative professionals alike. More details and examples of what Movie Gen can do ➡️ 🛠️ Movie Gen models and capabilities Movie Gen Video: 30B parameter transformer model that can generate high-quality and high-definition images and videos from a single text prompt. Movie Gen Audio: A 13B parameter transformer model that can take a video input along with optional text prompts for controllability to generate high-fidelity audio synced to the video. It can generate ambient sound, instrumental background music and foley sound — delivering state-of-the-art results in audio quality, video-to-audio alignment and text-to-audio alignment. Precise video editing: Using a generated or existing video and accompanying text instructions as an input it can perform localized edits such as adding, removing or replacing elements — or global changes like background or style changes. Personalized videos: Using an image of a person and a text prompt, the model can generate a video with state-of-the-art results on character preservation and natural movement in video. We’re continuing to work closely with creative professionals from across the field to integrate their feedback as we work towards a potential release. We look forward to sharing more on this work and the creative possibilities it will enable in the future.

AI at Meta

2,266,493 次观看 • 1 年前

In the age of Gemini, we are reimagining how we work across Docs, Sheets, Slides and Drive. The new way of working evolves our digital digital work from compiling information to directing outcomes. Excited to bring more contextual, helpful and collaborative Google Workspace. Simply choose your sources and create a Doc draft in seconds, build complex Sheets 9X faster, or generate on-brand Slide layouts with a simple prompt. And, Google Drive now generates summarized answers right at the top of your search results (AIO!) and helps you have a multi-turn conversation with your files/folders. Available today in beta for Workspace Gemini Alpha customers and G1 AI Ultra and AI Pro subscribers. 1/6

Chandu Thota

45,716 次观看 • 6 个月前