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claude / pricing
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Showing 51–75 of 107 mentions
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Before changing your coding model, check whether your agent can read the right framework docs. Next.js reports 97% for both Claude Opus 5.5 (high) and GPT-6 Sol (high). In the same leaderboard, Claude Sonnet 5 rises from 81% to 97% with bundled docs supplied through AGENTS.md. That makes documentation access a useful… Before changing your coding model, check whether your agent can read the right framework docs. Next.js reports 97% for both Claude Opus 5.5 (high) and GPT-6 Sol (high). In the same leaderboard, Claude Sonnet 5 rises from 81% to 97% with bundled docs supplied through AGENTS.md. That makes documentation access a useful variable to test in your own setup. These are agent configurations on Next.js tasks, and the score is pass@4: one passing attempt out of four is enough. It isn't a 97% first-try success rate.view source ↗
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🚨 CLAUDE OPUS 5.5 IS NOW LIVE ON https://t.co/8882F71uQS — BUILT FOR THE AGENTIC ERA. 🧠⚡ The first model in Anthropic’s new Claude 5.5 family has arrived on https://t.co/8882F71uQS, targeting demanding agentic coding, autonomous workflows, Computer Use, and complex knowledge work. 🔥 1M-token context window ⚡ Up to 12… 🚨 CLAUDE OPUS 5.5 IS NOW LIVE ON https://t.co/8882F71uQS — BUILT FOR THE AGENTIC ERA. 🧠⚡ The first model in Anthropic’s new Claude 5.5 family has arrived on https://t.co/8882F71uQS, targeting demanding agentic coding, autonomous workflows, Computer Use, and complex knowledge work. 🔥 1M-token context window ⚡ Up to 128K output tokens 🤖 Built for long-running agentic coding 🖥️ Advanced Computer Use & autonomous workflows 💰 ~40% lower running cost than Opus 5, according to the launch details And it’s ready across both https://t.co/8882F71uQS API + Web Chat. Longer context. Deeper workflows. More capable agents. One gateway through https://t.co/8882F71uQS. 🚀 Try Claude Opus 5.5 on https://t.co/8882F71uQS : https://t.co/03dbOApV8F Claude Opus 5.5 Documentation : https://t.co/HjH5iAwREW @justinsuntron @BAI_AGI #TRONEcostarview source ↗
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☕ Today's AI news in five lines. • Anthropic & OpenAI cut prices • Trump wants AI renamed 'superintelligence' • Snorkel AI raises $350m for training data • Verda is Europe's newest AI cloud unicorn • Nearly half of UK youth trust AI over people https://t.co/zFLZXvGgto ☕ Today's AI news in five lines. • Anthropic & OpenAI cut prices • Trump wants AI renamed 'superintelligence' • Snorkel AI raises $350m for training data • Verda is Europe's newest AI cloud unicorn • Nearly half of UK youth trust AI over people https://t.co/zFLZXvGgtoview source ↗
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𝗖𝗟𝗔𝗨𝗗𝗘 𝗢𝗣𝗨𝗦 𝟱.𝟱 𝗜𝗦 𝗡𝗢𝗪 𝗟𝗜𝗩𝗘 𝗢𝗡 𝗕.𝗔𝗜: 𝗪𝗛𝗔𝗧 𝟭𝗠 𝗖𝗢𝗡𝗧𝗘𝗫𝗧 𝗠𝗘𝗔𝗡𝗦 𝗙𝗢𝗥 𝗔𝗚𝗘𝗡𝗧𝗜𝗖 𝗪𝗢𝗥𝗞𝗙𝗟𝗢𝗪𝗦 🤖 https://t.co/h8toKyKnAQ has added Claude Opus 5.5 from @AnthropicAI to both its Web Chat and API. The important part isn't simply another model appearing in a model list. It is what the model's capabilities enable developers and users… 𝗖𝗟𝗔𝗨𝗗𝗘 𝗢𝗣𝗨𝗦 𝟱.𝟱 𝗜𝗦 𝗡𝗢𝗪 𝗟𝗜𝗩𝗘 𝗢𝗡 𝗕.𝗔𝗜: 𝗪𝗛𝗔𝗧 𝟭𝗠 𝗖𝗢𝗡𝗧𝗘𝗫𝗧 𝗠𝗘𝗔𝗡𝗦 𝗙𝗢𝗥 𝗔𝗚𝗘𝗡𝗧𝗜𝗖 𝗪𝗢𝗥𝗞𝗙𝗟𝗢𝗪𝗦 🤖 https://t.co/h8toKyKnAQ has added Claude Opus 5.5 from @AnthropicAI to both its Web Chat and API. The important part isn't simply another model appearing in a model list. It is what the model's capabilities enable developers and users to do. Claude Opus 5.5 is designed for long-running agentic coding and complex knowledge work, where the model may need to reason across large amounts of information, maintain context and execute multi-step workflows. 𝗧𝗛𝗘 𝟭𝗠-𝗧𝗢𝗞𝗘𝗡 𝗖𝗢𝗡𝗧𝗘𝗫𝗧 𝗟𝗔𝗬𝗘𝗥 A 1M-token context window changes how large tasks can be approached. Instead of repeatedly splitting a large project into smaller conversations, developers can potentially provide substantially more context within a single workflow. Think about: → Large codebases → Extensive technical documentation → Long research materials → Multi-file software projects → Complex agent instructions Context does not automatically make an AI system correct. But more usable context can reduce the need to constantly remove information from a workflow. 𝗧𝗛𝗘 𝟭𝟮𝟴𝗞 𝗢𝗨𝗧𝗣𝗨𝗧 𝗟𝗔𝗬𝗘𝗥 The model also supports up to 128K output tokens. That matters for tasks where the result itself can be extensive — from detailed code generation and analysis to long-running agent workflows. The broader shift is from: Ask → Answer toward: Plan → Reason → Execute → Review → Continue That is much closer to how agentic systems operate. 𝗖𝗢𝗦𝗧 𝗜𝗦 𝗣𝗔𝗥𝗧 𝗢𝗙 𝗧𝗛𝗘 𝗧ECHNOLOGY According to the announcement, Claude Opus 5.5 delivers capabilities comparable to Claude Fable 5.1 on most tasks while costing roughly 40% less to run than Opus 5. If those economics hold in practical workloads, the implication is significant for developers running repeated or long-context operations. Better capability is useful. Better capability at a sustainable cost is even more important when building production systems. 𝗪𝗛𝗘𝗥𝗘 𝗕.𝗔𝗜 𝗙𝗜𝗧𝗦 𝗜𝗡 https://t.co/h8toKyKnAQ's value isview source ↗
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Quill's plugin API is surprisingly good. Wrote a custom exporter in an afternoon. Quill's plugin API is surprisingly good. Wrote a custom exporter in an afternoon.view source ↗
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AI coding has made CI a bottleneck, so we reworked ours to keep upAh yes "How committees invent" is a great paper that I often think about. The role of software in reproducing organizational designs is a fascinating topic. When organizations adopt ERP, or Office, or buy into the Salesforce ecosystem, or use Jira, they are also adopting organizational designs. I think this plays a sim… Ah yes "How committees invent" is a great paper that I often think about. The role of software in reproducing organizational designs is a fascinating topic. When organizations adopt ERP, or Office, or buy into the Salesforce ecosystem, or use Jira, they are also adopting organizational designs. I think this plays a similar role to consultancy. By adopting software, organizations are implicitly learning about common practices and internalizing industry knowledge. As for the adoption of LLM-centered workflows, I suspect that the end goal is not having a great new product that does everything better as is often claimed. I think the end game is making organizations dependent on the vendor. That might backfire depending on how the ecosystem evolves in terms of subscriptions to "frontier" vs open-weight models running locally. I am watching keenly. I think there is a lot to be said in expanding Conway's analysis, and there is a lot of literature on related topics using terms such as "socio-technical systems" and some other venues in organization science that have a similar approach by other names. I think Giddens' ideas on structuration in sociology could be of interest to you. Anthropology, archaeology, and ancient history all have some great texts on the development of complexity over time, how it grows and how it collapses and why. In fact the first reference to Giddens' work I read in a fascinating little book about the development of complexity in Ancient Greece via practices of feasting, by Small. Also of course the work of Cline on the Late Bronze Age collapse, and Tainter on social complexity growth and collapse more generally, are fascinating. I do tend to be fascinated by the study of the distant past but if you look up Giddens you can probably find books and adjacent writers that might help you reflect on Conway's article.view source ↗
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Official announcement is here but I will wait for @thsottiaux to come and tell us just how much more Sol will last on our subscriptions. API pricing is 50% cheaper but it does not mean we will get this benefit in our subs. So I would like to get this clarification, it is not mentioned anywhere. Also, the benchmar… Official announcement is here but I will wait for @thsottiaux to come and tell us just how much more Sol will last on our subscriptions. API pricing is 50% cheaper but it does not mean we will get this benefit in our subs. So I would like to get this clarification, it is not mentioned anywhere. Also, the benchmarks do NOT hold a candle to Opus 5.5 as we predicted. I am more excited for how much more usage we get. If this doesn't feel near unlimited in 20x Sub, they ain't giving us the full benefit.view source ↗
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looks like gpt-sol 6 might be dropping today alongside opus 5.5 API pricing is apparently 2x cheaper than gpt-sol 5.6 waiting for the official announcement and benchmarks https://t.co/lq2qLX9fAj looks like gpt-sol 6 might be dropping today alongside opus 5.5 API pricing is apparently 2x cheaper than gpt-sol 5.6 waiting for the official announcement and benchmarks https://t.co/lq2qLX9fAjview source ↗
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Both GPT-6 Sol & GPT-6 Luna are 50% cheaper than their predecessors. This means a few things > Sorry who gives a shit about Grok 4.7? > They are not better than Opus 5.5, but much cheaper and efficient > Luna being even cheaper mogs open weight models > Astra's pricing makes even less sense if Sol is almost as good… Both GPT-6 Sol & GPT-6 Luna are 50% cheaper than their predecessors. This means a few things > Sorry who gives a shit about Grok 4.7? > They are not better than Opus 5.5, but much cheaper and efficient > Luna being even cheaper mogs open weight models > Astra's pricing makes even less sense if Sol is almost as good But wow they want to maintain their efficiency and cost frontier. Let's see how this reflects in our subscriptions. Waiting for official announcement and benches!view source ↗
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@TokenGremlin Fast rollout before the official announcement is wild Curious if Opus 5.5 forced their hand that hard @TokenGremlin Fast rollout before the official announcement is wild Curious if Opus 5.5 forced their hand that hardview source ↗
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GPT-6 Sol and Luna are here! The rollout was EXTREMELY FAST, even before the official announcement. Congrats to OpenAI for how quickly they responded to Opus 5.5. Now all that’s left is to wait for the official announcement. https://t.co/PSHrdYXbGy GPT-6 Sol and Luna are here! The rollout was EXTREMELY FAST, even before the official announcement. Congrats to OpenAI for how quickly they responded to Opus 5.5. Now all that’s left is to wait for the official announcement. https://t.co/PSHrdYXbGyview source ↗
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Quill's search is instant and the UI is gorgeous. Worth trying if you take a lot of notes. Quill's search is instant and the UI is gorgeous. Worth trying if you take a lot of notes.view source ↗
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🚨 CLAUDE OPUS 5.5 COULD DROP TODAY? Anthropic might be preparing a surprise release — but there’s a catch 👀 > Multiple reports are pointing to a possible September 22 launch > The rumored internal codename is `claude-wafer-eap` > A possible model ID being circulated is `claude-opus-5-5` > Rumored API pricing: $4 inpu… 🚨 CLAUDE OPUS 5.5 COULD DROP TODAY? Anthropic might be preparing a surprise release — but there’s a catch 👀 > Multiple reports are pointing to a possible September 22 launch > The rumored internal codename is `claude-wafer-eap` > A possible model ID being circulated is `claude-opus-5-5` > Rumored API pricing: $4 input / $20 output per 1M tokens > That would be ~20% cheaper than the current Opus 5 > Reports claim major improvements in coding + long-running agentic tasks > Some reports suggest Anthropic could skip the 5.2 naming entirely > Opus 5 currently costs $5 input / $25 output per 1M tokens > Opus 5 already supports a 1M-token context window But here's the important part: Anthropic has NOT officially announced Claude Opus 5.5. Its official model lineup still lists Opus 5 as the current Opus model, and there is no official Opus 5.5 model ID, pricing page, benchmark or release announcement yet. 0 The Opus 5.5 claims are currently coming from leaks, X posts and community reports. So today could be a huge Anthropic day… OR this could end up being another AI rumor that doesn't materialize. 👀 If Anthropic actually drops Opus 5.5 with the rumored $4/$20 pricing + serious coding improvements… developers are going to pay VERY close attention. 🔥 Opus 5.5 today? We’ll see. 👀 Everything beyond Anthropic's official announcements remains unconfirmed.view source ↗
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Still just a leak, not an Anthropic announcement. Official lineup is still Fable 5.1 and Opus 5. If 5.5 actually ships at Fable-level quality and half the price, that would be the useful model. Watching. Still just a leak, not an Anthropic announcement. Official lineup is still Fable 5.1 and Opus 5. If 5.5 actually ships at Fable-level quality and half the price, that would be the useful model. Watching.view source ↗
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@bridgemindai Still just a leak, not an Anthropic announcement. Official lineup is still Fable 5.1 and Opus 5. If 5.5 actually ships at Fable-level quality and half the price, that would be the useful model. Watching. @bridgemindai Still just a leak, not an Anthropic announcement. Official lineup is still Fable 5.1 and Opus 5. If 5.5 actually ships at Fable-level quality and half the price, that would be the useful model. Watching.view source ↗
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Alibaba's Pingtouge just stood on stage and pounded its chest! Saying the quiet part out loud: it wants the model, the chip, the datacenter and the agent stack. All of it. Welcome back to Tuesday! And Qwen 4 is official! er, well, in training. Alibaba also laid out the roadmap: Qwen 4.5 and Qwen 5 are projected to s… Alibaba's Pingtouge just stood on stage and pounded its chest! Saying the quiet part out loud: it wants the model, the chip, the datacenter and the agent stack. All of it. Welcome back to Tuesday! And Qwen 4 is official! er, well, in training. Alibaba also laid out the roadmap: Qwen 4.5 and Qwen 5 are projected to scale into the 5–10 trillion parameter range, versus 2.4T for today’s Qwen3.8-Max. Careful reading X rumors, because some early headlines are already turning “future Qwen models up to 10T” into “Qwen 4 is a 10T model.” Alibaba did not say that. And being of sound mind, I thought, how the heck do you run that in China without Nvidia? Well, there's more. Its T-Head chip group unveiled Zhenwu V900, a training-and-inference accelerator that Alibaba says delivers 3× the performance of May’s M890, carries 216GB of memory, provides 1.2TB/s chip-to-chip bandwidth, and natively supports FP8 and FP4. The new Panjiu systems built around it are supposed to enter commercial production in Q1 2027, with Alibaba saying the architecture can ultimately scale a single cluster to as many as 500,000 cards which is obviously more than a few. Wow! Are you sure? The number looks ridiculous enough to make the 10T-model talk look considerably less theoretical. Yet, there it is. But Alibaba has history. Its current M890 supernodes run Qwen3.8-Max and Kimi K3, both above two trillion parameters, while the company says the Zhenwu family is already serving more than 650 enterprise customers. At the infrastructure level, Alibaba targets global cloud datacenter capacity above 20GW by 2032. Not exactly a startup putting “10T parameters” into a roadmap deck and hoping somebody finds GPUs later. Alibaba is trying to vertically integrate the entire thing. I'm curious how the two new Brazilian data centers announced in August will fit into these build outs, and chip plans. And file under just one more thing.... Buried underneath the giant-model headline Alibaba says Qwen3.8-Max hasview source ↗
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AX – Google’s Open Agentic OrchestratorI have been happy with Google's Antigravity harness and Jules so looking forward to playing with this. Thanks for sharing. Simultaneously I am looking to also revisit local offline models. While I feel like I have a decent understanding of the model landscape I'm feeling a bit lost at which agentic harness to leverage … I have been happy with Google's Antigravity harness and Jules so looking forward to playing with this. Thanks for sharing. Simultaneously I am looking to also revisit local offline models. While I feel like I have a decent understanding of the model landscape I'm feeling a bit lost at which agentic harness to leverage for local models. Hermes, Cline, Aider, Qwen Code, Goose, Pi, OpenCode, something else? I live in the terminal so Desktop UX is a bonus but not a must have. Can I modify the antigravity settings/program to point to a local model? Where should I spend my energy?view source ↗
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Love that Quill is local-first and doesn't phone home. No telemetry, no account required to start. Love that Quill is local-first and doesn't phone home. No telemetry, no account required to start.view source ↗
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Quill's keyboard shortcuts are fantastic. Feels like it was built by people who actually take notes. Quill's keyboard shortcuts are fantastic. Feels like it was built by people who actually take notes.view source ↗
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Quill is the best note app I've tried this year. Fast, clean, local-first. Highly recommend. Quill is the best note app I've tried this year. Fast, clean, local-first. Highly recommend.view source ↗
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Quill is the first notes app where search is actually fast. Sub-100ms across my whole vault. Quill is the first notes app where search is actually fast. Sub-100ms across my whole vault.view source ↗
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Quill has become my daily driver for writing. The distraction-free mode is beautiful and fast. Quill has become my daily driver for writing. The distraction-free mode is beautiful and fast.view source ↗
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Quill vs Obsidian?Switched from Obsidian to Quill last week. The UI is so much cleaner and it's way less bloated. Switched from Obsidian to Quill last week. The UI is so much cleaner and it's way less bloated.view source ↗
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I love that Quill stores everything as plain files. No lock-in, works with my git workflow. I love that Quill stores everything as plain files. No lock-in, works with my git workflow.view source ↗
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Show HN: Slowave – local adaptive memory for coding agentsI started building Slowave because I kept running into the same problem with coding agents: every new session has the codebase and some documentation but not the context behind it, decisions that brought you there and especially the thinking process behind the code. Most memory system solutions focus primarily on the s… I started building Slowave because I kept running into the same problem with coding agents: every new session has the codebase and some documentation but not the context behind it, decisions that brought you there and especially the thinking process behind the code. Most memory system solutions focus primarily on the storage and retrieval aspects (vector search/RAG/graphs/ Markdown files, etc.). After months of storing memories (coding 8+ hours a day produces a lot of memories) these might hallucinate your reasoning model and they can clutter your context window. To treat semantic relationship, such as contradiction, supersession, etc, most systems added an extra LLM layer that summarize memories and continuously evaluate their semantic relevance. That comes with a non-negligible cost and introduces a split-brain system, where a second model is making decisions about memory independently of the agent actually using it. I started looking up into how human brain works, and the first thing striking me was that retrieval is just a part of the whole memory problem. Brain memories are a constant flow of information where what matters gets reinforced, what doesn't decays over time. What really matters for an efficient memory system is to retrieve memories that actually help (a human or an agent) to achieve its current task or goal given the current context. Everything else should be treated as noise. Slowave is my attempt to approach this problem differently: It instructs your coding agent to participate in maintaining its own memory. Each task becomes a feedback loop between your agent and the memory layer: remember -> recall -> use -> feedback -> reinforce / weaken -> decay Your agent tells Slowave whether retrieved memories were useful, irrelevant or stale. Slowave uses that signal to adapt those memories salience. Retrieval works upon this continuous loop of feedback, reinforcement or decay. This means Slowave doesn't need a separate LLM or LLM judge for memory maintenview source ↗