Claude Opus

Ever since people got a taste of Claude Opus 5.2, the Anthropic hatemaxxing has gone very quiet lol. Now there are rumours everywhere about Opus 5.2, Fable 5.2 and other new Claude models. Feels like Anthropic might be preparing a whole fleet of AI model releases ahead of its IPO

One of the clearest examples of what model specialization can buy you. At 2.6B and 1.2B parameters, these models are also small enough to run locally on mobile devices.

@liquidai

In a new article published today on the cover of @CellCellPress, we obtained Liquid Foundation Model instances that establish state-of-the-art performance on biological longevity tasks, outperforming the best frontier models such as Gemini-3.1-Pro, GPT-5, and Claude Opus. > In partnership with @InSilicoMeds, we built and released: > A comprehensive eval suite of 17 biological longevity tasks (i.e., LongevityBench), to assess whether a general-purpose language model can interpret aging data spanning clinical records, DNA methylation, transcriptomics, plasma proteomics, and genetic evidence. > LFM2-1.2B-Longevity and LFM2-2.6B-Longevity: two compact models specialized for interpreting structured aging data across these tasks. > These results are important! 🧵

OK, this is a big deal: 3 researchers used Claude Opus 5 to turn an image upload bug into an OpenAI employee account takeover, then had the compromised employee’s Codex open a PR in OpenAI’s internal monorepo. Their entire hacking cost less than $3000 in tokens. Opus 4.8 struggled with the exploit. Then Opus 5 dropped and cracked it within hours. AI-powered cyberattacks are becoming common and cheap. The best defense is to put the best AI in the hands of defenders too.

Claude Opus 5.2 spotted on Microsoft Foundry

The performance numbers are what make this one hard to ignore. It is landing close to GPT-6 Astra and Claude Opus 5 on coding benchmarks. It is doing that at roughly 18 times lower expected cost than either of them. If that holds up under real independent testing, this is not a small gap. This is the kind of cost difference that changes which model teams actually choose to run agents on all day, every day. Whoever is behind Union Alpha clearly optimized for being cheap enough to use constantly, not just for winning one leaderboard screenshot.

@cline

Union Alpha (stealth model) is now free in Cline. > 256k context, multimodal, built for agentic coding. > It is near GPT-6 Astra and Opus 5 performance for ~18x lower expected cost.

We rolled out GPT-6 Astra to every Databricks engineer today. It beats Claude Opus 5 on the hardest, long-horizon tasks and increased our coding spend by 60%. I think it’s the strongest model. Expensive. But hopefully worth it.

@pwendell

Today we rolled out Astra to every engineer at Databricks (N=~3500). Some notes that may be helpful to others: > 1. Astra unambiguously out performs our previous highest-end models (Opus 5, Sol 5.6) on highly complex tasks, especially those related to high level system design or long range horizontal tasks. > 2. Engineers given Astra increased overall coding spend by around 60% compared to baseline. > 3. It is not clear Astra meaningfully improves on medium/low complexity coding tasks compared to earlier models. We suspect those tasks are mostly saturated (i.e. perfectly executed) by existing models. > 4. We learned above by piloting Astra with around 200 users to gain signal on both quality and cost. We use Unity Gateway to

Claude Opus 5.2 fails my AGI test miserably.

@R2Cdev_

Holy shit. GPT-6 just decoded this without being told how the cipher works: > “Dajjr, thd bfuthkf ctf Hrjjahk-Uhdutih.” → “Hallo, ich besitze die Collatz-Schrift.” (German for “Hello, I own the Collatz manuscript.”) > The cipher works by mapping each letter to its position in the alphabet (A=1, B=2, …), running that number through the Collatz sequence until it reaches 1, and using the number of steps as the encoded letter (0=A, 1=B, 2=C, …). > For example: H = 8 → 4 → 2 → 1 = 3 steps → D GPT-6 figured out the encoding rule and verified the entire sentence. > This feels like AGI.

this is the coolest thing i've seen created by AI.

@kevin_t_ngo

Claude Opus 5 drew every frame of this animation using JavaScript. The life of a fruit fly.

Anthropic Claude Opus 5.2 is live in testing and they skipped 5.1. - Opus 5.2 leaks: Beats Fable 5.1 - Opus 5.2 is already being tested inside Claude Code. - The slug “claude-opus-5-2” showed up in Microsoft Foundry. - Some live traffic is already being routed to it. - Reports say it beats Fable 5.1 and is a real leap over Opus 5. Anthropic’s real comeback incoming?

@0x0SojalSec

Elon just confirmed it: Grok 5 is the AGI model. > - Not the next one. - The one after that. - End of 2026 is looking very interesting.

🚨 Opus 5.2 < many people asked me where the name came from or why not opus 5.1

@chetaslua

🚨 Claude Opus 5.2 currently being tested inside claude code > opus 5 is routing to new opus 5.2 > this one shot < but opus was re iterating like it was trained on @mattshumer_ gauntlet loop without even asking it was looping

GPT 5.6 sol is routing to GPT 6 sol for users but for me looks like its back routing to previous models when i ask about latest opus model, it saying Claude Opus 4.1 🙂

🚨 Claude Opus 5.2 is coming soon then The "claude-opus-5-2" slug is in Microsoft Foundry: Tibo is also teasing Sol for this week too I believe, so this is going to be fun

You can Run Locally DeepSeek V4.1 Flash It beats GPT-5.6 Sol, Claude Opus 5 & can run with 4-GPU at your home locally No NVLink. - Jovian Judgement R37/TP4/DCP1: - 21,400 tok/s uncached 32K prefill - 280 tok/s C1 decode (budget 50) - 500 tok/s single-stream decode - 417 tok/s sieve - +44% prefill vs R36 - DSpark K7 + Engram (RAM or SSD) - 552B MoE, vision, 1M context Engram in pinned RAM or disk, DSpark K7. -

@0x0SojalSec

You don’t need a GPU-cluster to run a Uncensored DeepSeek-V4.1-Flash 763B model locally at home. > You need a Single RTX PRO 6000 Blackwell. > - 316 tok/s output - 9,351 tok/s prefill - FP8 + vLLM + DSpark - 64-96GB class machine.

• github.com

5,000,000 FREE TOKENS ON CLAUDE OPUS, GPT-5, CODEX AND GEMINI FOR VERIFYING A TELEGRAM ACCOUNT • @anymodelss > One OpenAI compatible endpoint at so switching model is a one-line change. > No subscription and no minimums, the balance drains by actual tokens spent. > Updates and promo codes land in the channel: and in shop @anyaccs_bot • the pricing detail nobody leads with > Output is billed at the same rate as input, where every vendor charges five to six times more for it. > Their pricing page puts Codex at $0.20 per million against $5 in and $30 out direct. > Ghost Mode turns on zero retention per key at the same price, so prompts never hit disk. Coding agents are almost entirely output, which is exactly where the flat rate bites -> the heavier your usage, the wider the gap gets. Free to start and the usage counter moves in real time ↓

• anymodel.org
• t.me