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Introducing Cognee v1.0: a major breakthrough in agentic intelligence. It is 145% better than Opus 4.8 and GPT 5.5 at long context memory retrieval. Cognee allows a 100 BILLION token context window 100,000x more than Claude. It's: - 6.9x cheaper than GPT 5.5 and Opus 4.8 - Cold starts... show more

Vasilije

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839,206 views • 17 days ago •via X (Twitter)

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Opus 4.8 for planning 🤝 GPT 5.5 for implementation Claude is a nicer conversation and /grilling partner than Codex in my experience, but GPT 5.5 on low cranks out higher quality code in fewer tokens. Here's how I divide up the work:

Opus 4.8 for planning 🤝 GPT 5.5 for implementation Claude is a nicer conversation and /grilling partner than Codex in my experience, but GPT 5.5 on low cranks out higher quality code in fewer tokens. Here's how I divide up the work:

Ben Holmes

23,010 views • 1 month ago

Long-running agents blow up context fast. So we built our own memory agent. Using it feels very cool and useful Twin starts to know you better over time, resurfaces old context when it matters, and makes agents more efficient with every task. It’s live today. Try it out!

Long-running agents blow up context fast. So we built our own memory agent. Using it feels very cool and useful Twin starts to know you better over time, resurfaces old context when it matters, and makes agents more efficient with every task. It’s live today. Try it out!

Hugo Mercier

18,606 views • 5 months ago

Grok 4.5 is a "Wow!" moment. 🤯 > Opus 4.8 & GPT-5.5 level on benchmarks > Costs less than Sonnet 5 Is that real? Hard to believe. Added Grok 4.5 as an implementer agent in fable-advisor. It replaces Sonnet 5. Use Fable as the orchestrator and a combo of: 1. Grok 4.5 2. Opus 4.8 3. GPT-5.5 As implementer agents. Uses the Grok Build CLI so if you log in with an X premium account you don't have to pay API fees.

Grok 4.5 is a "Wow!" moment. 🤯 > Opus 4.8 & GPT-5.5 level on benchmarks > Costs less than Sonnet 5 Is that real? Hard to believe. Added Grok 4.5 as an implementer agent in fable-advisor. It replaces Sonnet 5. Use Fable as the orchestrator and a combo of: 1. Grok 4.5 2. Opus 4.8 3. GPT-5.5 As implementer agents. Uses the Grok Build CLI so if you log in with an X premium account you don't have to pay API fees.

Dan McAteer

175,531 views • 4 days ago

$GOOGL launched Gemini 3.5 Flash which it says beats Gemini 3.1 Pro across coding, real-world agentic tasks & scaled tool use. Artificial Analysis shows it running at 289 output tokens/sec which is more than 4x faster than Claude Opus 4.7 & GPT-5.5.

$GOOGL launched Gemini 3.5 Flash which it says beats Gemini 3.1 Pro across coding, real-world agentic tasks & scaled tool use. Artificial Analysis shows it running at 289 output tokens/sec which is more than 4x faster than Claude Opus 4.7 & GPT-5.5.

Shay Boloor

56,188 views • 1 month ago

🚨 Build, Deploy And Host Anything Using The Abacus AI SuperComputer Build and Deploy - 3D game servers - always on agents - open-source LLMs - complex SaaS apps in any programming language - database and APIs All with ONE PROMPT using top models like Claude Fable, Opus 4.8 and GPT 5.5

🚨 Build, Deploy And Host Anything Using The Abacus AI SuperComputer Build and Deploy - 3D game servers - always on agents - open-source LLMs - complex SaaS apps in any programming language - database and APIs All with ONE PROMPT using top models like Claude Fable, Opus 4.8 and GPT 5.5

Abacus.AI

8,235,075 views • 1 month ago

Are AI agents shape rotators? In this new benchmark, we let the models play campaign puzzles in Opus Magnum, a puzzle game by Zachtronics. Ironically, Claude Opus 4.8 performed poorly, being beaten by GPT-5.5, Gemini 3.5 Flash, and GLM 5.2. Claude Fable 5 crushed them all.

Are AI agents shape rotators? In this new benchmark, we let the models play campaign puzzles in Opus Magnum, a puzzle game by Zachtronics. Ironically, Claude Opus 4.8 performed poorly, being beaten by GPT-5.5, Gemini 3.5 Flash, and GLM 5.2. Claude Fable 5 crushed them all.

Rob Haisfield

495,984 views • 25 days ago

Introducing GPT-5.5 A new class of intelligence for real work and powering agents, built to understand complex goals, use tools, check its work, and carry more tasks through to completion. It marks a new way of getting computer work done. Now available in ChatGPT and Codex.

Introducing GPT-5.5 A new class of intelligence for real work and powering agents, built to understand complex goals, use tools, check its work, and carry more tasks through to completion. It marks a new way of getting computer work done. Now available in ChatGPT and Codex.

OpenAI

13,160,703 views • 2 months ago

$Microsoft just dropped a 17-page paper - "Less Context, Better Agents" - proving the thing nobody building agents wants to admit: Your agent isn't failing because it needs more context. It's drowning in the context it already has. They ran GPT-5 four ways on one 50-task benchmark (via MCP): Full history → bloated, pricey, more errors Trim to the last 5 tool calls → 79% done Add light summarization → 91.6%, on a fraction of the tokens Less context. Fewer tokens. Higher completion. Everyone's racing to cram MORE into the window. Microsoft just published the receipt that the opposite wins for long-running agents. Rewired how I build agents this week. Paper ↓$

Microsoft just dropped a 17-page paper - "Less Context, Better Agents" - proving the thing nobody building agents wants to admit: Your agent isn't failing because it needs more context. It's drowning in the context it already has. They ran GPT-5 four ways on one 50-task benchmark (via MCP): Full history → bloated, pricey, more errors Trim to the last 5 tool calls → 79% done Add light summarization → 91.6%, on a fraction of the tokens Less context. Fewer tokens. Higher completion. Everyone's racing to cram MORE into the window. Microsoft just published the receipt that the opposite wins for long-running agents. Rewired how I build agents this week. Paper ↓

Archive

18,242 views • 18 days ago

Claude Opus 4.8 beats Opus 4.7, GPT-5.5, and Gemini 3.1 Pro !! We ran a multimodal gaming comparison across these four closed source models. Opus 4.8 took the longest to generate, but it came out ahead, capturing the most elements from the prompt and successfully hitting the rival cars. GPT 5.5 is still good, but Gemini is no longer the best multimodal model now

Claude Opus 4.8 beats Opus 4.7, GPT-5.5, and Gemini 3.1 Pro !! We ran a multimodal gaming comparison across these four closed source models. Opus 4.8 took the longest to generate, but it came out ahead, capturing the most elements from the prompt and successfully hitting the rival cars. GPT 5.5 is still good, but Gemini is no longer the best multimodal model now

GMI Cloud

116,249 views • 1 month ago

Grok 4.5 operates at Opus-level intelligence and Sonnet-level pricing! We tested it against Claude Opus 4.8, Sonnet 5, and GLM 5.2 on a SpaceX mission: liftoff, stage sep, orbit insertion, satellite deploy. Grok 4.5 animates it more accurately and vividly than Sonnet 5 and GLM 5.2. Opus is the fastest and most expensive. Grok burns more tokens but still lands ~40% cheaper than Opus, and a bit under Sonnet 5. Time / tokens / cost: Grok 4.5 — / 35k / $0.69 Opus 4.8 — / 13.7k / $1.10 Sonnet 5 — / 22.1k / $0.78 GLM 5.2 — / 92.7k / $0.13 yet GLM did the whole mission for $0.13 😮

Grok 4.5 operates at Opus-level intelligence and Sonnet-level pricing! We tested it against Claude Opus 4.8, Sonnet 5, and GLM 5.2 on a SpaceX mission: liftoff, stage sep, orbit insertion, satellite deploy. Grok 4.5 animates it more accurately and vividly than Sonnet 5 and GLM 5.2. Opus is the fastest and most expensive. Grok burns more tokens but still lands ~40% cheaper than Opus, and a bit under Sonnet 5. Time / tokens / cost: Grok 4.5 — / 35k / $0.69 Opus 4.8 — / 13.7k / $1.10 Sonnet 5 — / 22.1k / $0.78 GLM 5.2 — / 92.7k / $0.13 yet GLM did the whole mission for $0.13 😮

GMI Cloud

148,431 views • 4 days ago

Introducing HydraDB. The graph native context infrastructure for agents. Purpose built to deliver precise context & observability into why agents act the way they do. We've always believed graphs are the best way to manage AI context, but they've been too expensive to scale or impractical for storing full context. Until now. HydraDB combines in memory, NVMe, and object storage into a single graph layer, making context delivery faster, cheaper, and more precise. We want context delivery to be extremely fast, 1000x cheap, and highly precise. Give your agents a brain.

Introducing HydraDB. The graph native context infrastructure for agents. Purpose built to deliver precise context & observability into why agents act the way they do. We've always believed graphs are the best way to manage AI context, but they've been too expensive to scale or impractical for storing full context. Until now. HydraDB combines in memory, NVMe, and object storage into a single graph layer, making context delivery faster, cheaper, and more precise. We want context delivery to be extremely fast, 1000x cheap, and highly precise. Give your agents a brain.

Nishkarsh

2,294,071 views • 1 month ago

Claude fable 5 is operating in a completely different dimension 🤯 Compared it with Claude Opus 4.8, Gemini 3.1 Pro, and GPT 5.5, the visual gap is insane. From 3D fluid dynamics to volumetric animation and complex physics, Fable 5 crushes the game. It’s not even close.

Claude fable 5 is operating in a completely different dimension 🤯 Compared it with Claude Opus 4.8, Gemini 3.1 Pro, and GPT 5.5, the visual gap is insane. From 3D fluid dynamics to volumetric animation and complex physics, Fable 5 crushes the game. It’s not even close.

GMI Cloud

319,114 views • 1 month ago

🚨 Multi-Agent - Lite Agent Swarms - Optimize Cost On Large Agentic Loops After a lot of experimentation we have open-source AI agent swarms live!! - Opus 4.8 and GPT 5.5 do the planning - Deepseek flash and Gemma do the work - Perfect for multiple parallel tasks - 10x cheaper than Opus 4.8 - 2x faster and comparable performance Try prompts like - fix all known bugs in my repo, code review the last 10 PRs etc.

🚨 Multi-Agent - Lite Agent Swarms - Optimize Cost On Large Agentic Loops After a lot of experimentation we have open-source AI agent swarms live!! - Opus 4.8 and GPT 5.5 do the planning - Deepseek flash and Gemma do the work - Perfect for multiple parallel tasks - 10x cheaper than Opus 4.8 - 2x faster and comparable performance Try prompts like - fix all known bugs in my repo, code review the last 10 PRs etc.

Bindu Reddy

20,175,002 views • 1 month ago

Stop saying that Opus 4.6 is better than Opus 4.8. I just tested Claude Opus 4.8 (Right) and Claude Opus 4.6 (Left) on the same exact prompt. Claude Opus 4.8 completed it in less than 2 minutes. Claude Opus 4.6 "Garnished" for over 7 minutes. Stop using Opus 4.6.

Stop saying that Opus 4.6 is better than Opus 4.8. I just tested Claude Opus 4.8 (Right) and Claude Opus 4.6 (Left) on the same exact prompt. Claude Opus 4.8 completed it in less than 2 minutes. Claude Opus 4.6 "Garnished" for over 7 minutes. Stop using Opus 4.6.

BridgeMind

52,868 views • 1 month ago

There is no better place on the internet to learn about Context Engineering than this repo. It's literally a course with a learning path. It gathers the best resources and covers the theory + code for anything related to context, RAG, memory, and agentic systems and more.

There is no better place on the internet to learn about Context Engineering than this repo. It's literally a course with a learning path. It gathers the best resources and covers the theory + code for anything related to context, RAG, memory, and agentic systems and more.

ℏεsam

48,999 views • 11 months ago

we asked GLM 5.2 and Claude Opus 4.8 to find and fix the bugs in two different scripts while Opus 4.8 finished a few seconds faster in both tests, GLM 5.2 burned roughly 17k–38k fewer tokens and absolutely crushed it on cost, coming in 15x to 22x cheaper! Test 1: GLM 5.2 ($0.068) vs. Opus 4.8 ($1.06) Test 2: GLM 5.2 ($0.045) vs. Opus 4.8 ($1.02)

we asked GLM 5.2 and Claude Opus 4.8 to find and fix the bugs in two different scripts while Opus 4.8 finished a few seconds faster in both tests, GLM 5.2 burned roughly 17k–38k fewer tokens and absolutely crushed it on cost, coming in 15x to 22x cheaper! Test 1: GLM 5.2 ($0.068) vs. Opus 4.8 ($1.06) Test 2: GLM 5.2 ($0.045) vs. Opus 4.8 ($1.02)

GMI Cloud

86,341 views • 17 days ago

🚨 INTRODUCING THE ABACUS AI SUPERCOMPUTER - literally build ANY cloud service with a prompt - host open-source LLMs & always-on agents - bring your own Codex, Claude or Anti-gravity - multi-agent architectures with Opus 4.8 and GPT 5.5 - run 3D games or any other server at scale - connect git and collaborate with teams Build a billion dollar business by simply prompting in english!!

🚨 INTRODUCING THE ABACUS AI SUPERCOMPUTER - literally build ANY cloud service with a prompt - host open-source LLMs & always-on agents - bring your own Codex, Claude or Anti-gravity - multi-agent architectures with Opus 4.8 and GPT 5.5 - run 3D games or any other server at scale - connect git and collaborate with teams Build a billion dollar business by simply prompting in english!!

Abacus.AI

11,919,989 views • 1 month ago

GPT-5.4 is here. Native computer-use capabilities. Up to 1M tokens of context in Codex and the API. Best-in-class agentic coding for complex tasks. Scalable tool search across larger ecosystems. More efficient reasoning for long, tool-heavy workflows.

GPT-5.4 is here. Native computer-use capabilities. Up to 1M tokens of context in Codex and the API. Best-in-class agentic coding for complex tasks. Scalable tool search across larger ecosystems. More efficient reasoning for long, tool-heavy workflows.

OpenAI Developers

1,074,161 views • 4 months ago

Here's OpenAI President Greg Brockman on the rumors that GPT 5.6 will be 3x cheaper than Fable, up to 1.5 million token context, stronger agentic coding workflows..

Here's OpenAI President Greg Brockman on the rumors that GPT 5.6 will be 3x cheaper than Fable, up to 1.5 million token context, stronger agentic coding workflows..

Alex Kantrowitz

61,566 views • 18 days ago

$Introducing SubQ - a major breakthrough in LLM intelligence. It is the first model built on a fully sub-quadratic sparse-attention architecture (SSA), And the first frontier model with a 12 million token context window which is: - 52x faster than FlashAttention at 1MM tokens - Less than 5% the cost of Opus Transformer-based LLMs waste compute by processing every possible relationship between words (standard attention). Only a small fraction actually matter. Subquadratic finds and focuses only on the ones that do. That's nearly 1,000x less compute and a new way for LLMs to scale.$

Introducing SubQ - a major breakthrough in LLM intelligence. It is the first model built on a fully sub-quadratic sparse-attention architecture (SSA), And the first frontier model with a 12 million token context window which is: - 52x faster than FlashAttention at 1MM tokens - Less than 5% the cost of Opus Transformer-based LLMs waste compute by processing every possible relationship between words (standard attention). Only a small fraction actually matter. Subquadratic finds and focuses only on the ones that do. That's nearly 1,000x less compute and a new way for LLMs to scale.

Alexander Whedon

13,184,794 views • 2 months ago