XX / Twitter50
listening to
Opus 5.5 official announcement
50
mentions
tracked
tracked
net sentiment
+26%
16 positive
31 neutral
3 negative
volume & sentiment over time
Jul 3 – Sep 27, 2026 · 2-day buckets
sources
most discussed
pricing / model
active days
21
what people keep raising
- pricing / model 16
- performance / rollout 3
- anthropic / openai 2
- claude 2
mentions
Showing 26–50 of 50 mentions
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X X / Twitter 1w ▲ 7 negative pricing / modelThe official announcement. Opus 5.5 is here and it delivers Fable 5.1 performance at a cost 40% cheaper than even Opus 5. > They've lowered the API pricing since this model takes far less compute to run. > It is also 30% faster to run than Opus 5. > It talks naturally, finally fixing Opus 5's language problem BA… The official announcement. Opus 5.5 is here and it delivers Fable 5.1 performance at a cost 40% cheaper than even Opus 5. > They've lowered the API pricing since this model takes far less compute to run. > It is also 30% faster to run than Opus 5. > It talks naturally, finally fixing Opus 5's language problem BAD NEWS THO: Since this model shows similar bio & cyber capabilities, it has the same guardrails that Fable does. Overall, what a banger release. I am pumped to test it out.view source ↗
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X X / Twitter 1w ▲ 14 positive pricing / model🚨 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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X X / Twitter 1w ▲ 1 neutral claudeClaude Opus 5.5 just popped up in Hookami — before an official Anthropic announcement. 8 videos. 8 channels. The signal is already moving. You can make the video while everyone else is waiting for the press release. That’s Hookami. https://t.co/dAWiDQDjIp Claude Opus 5.5 just popped up in Hookami — before an official Anthropic announcement. 8 videos. 8 channels. The signal is already moving. You can make the video while everyone else is waiting for the press release. That’s Hookami. https://t.co/dAWiDQDjIpview source ↗
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X X / Twitter 1w ▲ 1 positive pricing / modelStill 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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X X / Twitter 1w ▲ 0 positive pricing / model@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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X X / Twitter 1w ▲ 6 positive pricing / modelAlibaba'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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X X / Twitter 2w ▲ 5 neutralhttps://t.co/Z64TY3xtha https://t.co/Z64TY3xthaview source ↗
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X X / Twitter 2w ▲ 8 neutralhttps://t.co/yo1DHXo2nx https://t.co/yo1DHXo2nxview source ↗
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X X / Twitter 1mo ▲ 3 positive pricing / model⚔ GLM-5.3-Flash Aims Straight at the Post-Hike DeepSeek Zhipu's GLM-5.3-Flash — revealed this week as the anonymous "Ox Alpha" — has been open-weighted and priced at roughly one-tenth of GLM-5.3. Much of the early discussion compares it to DeepSeek's V4 Flash, which recently raised prices. Zhihu contributor 起步十档, who … ⚔ GLM-5.3-Flash Aims Straight at the Post-Hike DeepSeek Zhipu's GLM-5.3-Flash — revealed this week as the anonymous "Ox Alpha" — has been open-weighted and priced at roughly one-tenth of GLM-5.3. Much of the early discussion compares it to DeepSeek's V4 Flash, which recently raised prices. Zhihu contributor 起步十档, who ran Ox Alpha inside real workflows before the reveal, gives a practitioner's verdict in one line: it is built to kill the post-hike DeepSeek. His case rests on three legs — performance, token efficiency, and an architecture change that makes the price possible. 1️⃣ It clears the bar for long-horizon work Official scores put Flash between Grok 4.6 and GLM-5.3, and clearly ahead of DeepSeek V4 Flash. In the author's own testing, its frontend ability roughly matches an early gray-test build of DeepSeek V4 Pro, while its backend is noticeably weaker than GLM-5.3 — but still usable on long-horizon tasks as long as the connection holds. His rule of thumb: any model past the Claude Opus 4.6 line is workflow-ready for long tasks. Beyond that, differences come down to reasoning style and accuracy, not viability. One caveat he flags: during the anonymous test the deployment was unstable, and some believe it served a mid-training checkpoint rather than the final model. 2️⃣ The real weapon: token efficiency Comparing peak API prices against the post-hike DeepSeek V4 Flash, the author notes cached input is actually 2x more expensive, while regular input and output sit at roughly 26% of DeepSeek's price. Since cached input is often the bulk of the bill, he wants real-world tests before calling a winner on price alone. But his own usage points the same direction. In one to two hours of real work — reading and writing files, running tests — Ox Alpha burned barely over 100K tokens. He estimates DeepSeek would need 250-300K for the same workload. His prediction: same tasks, run on both APIs, will come out cheaper on Flash — with clearly better performance. 3️⃣ His unview source ↗
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X X / Twitter 1mo ▲ 3 positive pricing / model### Decision question Should an enterprise AI buyer routing developer-workflow and coding workloads (e.g., Cursor integrations) migrate primary traffic from GPT-5.5 or Claude Opus 4.8 to xAI's Grok 4.5 to optimize cost-per-token and execution speed? ### Dated conclusion Evidence from July 2026 shows that xAI’s Grok 4.… ### Decision question Should an enterprise AI buyer routing developer-workflow and coding workloads (e.g., Cursor integrations) migrate primary traffic from GPT-5.5 or Claude Opus 4.8 to xAI's Grok 4.5 to optimize cost-per-token and execution speed? ### Dated conclusion Evidence from July 2026 shows that xAI’s Grok 4.5—trained on trillions of tokens of Cursor data—outperforms GPT-5.5 (29% vs 22%) and Claude Opus 4.8 (29% vs 21%) on professional work tasks while delivering fast-model speeds of 80 tokens per second (TPS) at double the token efficiency. For specialized software engineering and developer tooling workloads, enterprises have empirical justification to substitute incumbent models, provided they account for its lower general intelligence ranking. ### Confidence High — Supported by official primary-source release telemetry (https://t.co/weowGvrpDL), targeted enterprise vertical analysis (AI Business), and comparative professional benchmark evaluations (ValueAdd VC) published in July 2026. ### Provenance block (required) - Telemetry authorization: Public web only - Fields covered: list prices, token pricing tiers, professional work benchmark scores, inference speed (TPS), context window rate rules, and model training datasets - Time window: January 2025 – August 18, 2026 - Coverage: Publicly announced xAI model specifications, third-party intermediary pricing via PromptLayer/OpenRouter, and published comparative benchmarks - Blind spots: Private provider routing volumes, true infrastructure margins, unannounced enterprise enterprise-agreement discounts, and full internal OpenRouter traffic distributions - Number labels: - $0.20 per million input tokens, $0.50 per million output tokens (Observed) - 128,000 context threshold doubling rule (Observed) - 29% vs 22% / 21% professional work task outperformance (Observed) - 80 TPS inference speed (Observed) - 100 trillion tokens aggregate study scale (Observed) ### Strongest evidence (top 3) 1. **Introview source ↗
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X X / Twitter 1mo ▲ 2 neutralhttps://t.co/HMClL2bCeb https://t.co/HMClL2bCebview source ↗
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X X / Twitter 2mo ▲ 1027 neutralhttps://t.co/cjXFWC9Eyf https://t.co/cjXFWC9Eyfview source ↗
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X X / Twitter 2mo ▲ 90 neutralhttps://t.co/jtugf7eh1U https://t.co/jtugf7eh1Uview source ↗
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X X / Twitter 2mo ▲ 5 neutralhttps://t.co/pq2g8eqHeo https://t.co/pq2g8eqHeoview source ↗
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X X / Twitter 2mo ▲ 6 neutralhttps://t.co/5BWvsHEOTJ https://t.co/5BWvsHEOTJview source ↗
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X X / Twitter 2mo ▲ 62 neutralhttps://t.co/fNsN5B6zph https://t.co/fNsN5B6zphview source ↗
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X X / Twitter 2mo ▲ 12 neutralhttps://t.co/r1L8qCQgL0 https://t.co/r1L8qCQgL0view source ↗
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X X / Twitter 2mo ▲ 3 neutralhttps://t.co/RYu5vvWNNz https://t.co/RYu5vvWNNzview source ↗
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X X / Twitter 2mo ▲ 4 positive pricing / modelHere's the translation of the WeChat Announcement https://t.co/ZHF1ky9xdw Kimi K3: The New Frontier of Intelligence Those who take on the hardest challenges and pursue the farthest horizons begin with courage, persevere with focus, and prevail through strength. Today, we are officially launching Kimi K3, our most ca… Here's the translation of the WeChat Announcement https://t.co/ZHF1ky9xdw Kimi K3: The New Frontier of Intelligence Those who take on the hardest challenges and pursue the farthest horizons begin with courage, persevere with focus, and prevail through strength. Today, we are officially launching Kimi K3, our most capable model to date. Kimi K3 is a 2.8-trillion-parameter model built on the Kimi Delta Attention (KDA) hybrid linear-attention mechanism and Attention Residuals. It natively supports visual understanding and features a one-million-token context window. It is the world’s first open-source model in the three-trillion-parameter class, designed for frontier intelligence applications such as long-horizon coding, knowledge work, and reasoning. Although Kimi K3’s overall performance still trails the strongest closed-source models, Claude Fable 5 and GPT-5.6 Sol, it demonstrates frontier-level capabilities across our full evaluation suite and consistently outperforms every other model. The release of Kimi K3 is only the beginning. We will continue exploring the model’s potential and improving its performance on real-world tasks. Starting today, Kimi K3 is available through https://t.co/pf2bINlnkD, the latest version of the Kimi mobile app, the latest Kimi Work desktop client, Kimi Code, and the Kimi API. The default reasoning intensity is currently set to max, with low and high modes to be added in a future update. We are working closely with inference partners and open-source maintainers to align technical details and ensure that the model can be deployed reliably across the ecosystem. The complete model weights will be released by July 27, 2026. Further details about the architecture, training process, and evaluations will be published alongside the Kimi K3 technical report. An Open-Source Model in the Three-Trillion-Parameter Class Kimi K3 is the first open-source model to reach a scale of 2.8 trillion parameters. This represents the latest step in Kview source ↗
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X X / Twitter 2mo ▲ 50 neutralhttps://t.co/8IS9xotQua https://t.co/8IS9xotQuaview source ↗
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X X / Twitter 2mo ▲ 1 positive pricing / modelChatGPT Is No Longer Just a Chatbot The new OpenAI release is really about work, not just models OpenAI’s latest ChatGPT release looks, at first glance, like another model announcement. New names, new capabilities, new benchmarks. Sol, Terra and Luna. GPT-5.6. More power, more speed, more coding ability. But that is … ChatGPT Is No Longer Just a Chatbot The new OpenAI release is really about work, not just models OpenAI’s latest ChatGPT release looks, at first glance, like another model announcement. New names, new capabilities, new benchmarks. Sol, Terra and Luna. GPT-5.6. More power, more speed, more coding ability. But that is not really the main story. The real story is that ChatGPT is moving from being a conversational assistant into something much closer to a work platform. It is no longer only a place where we ask questions, brainstorm ideas, write drafts or get help understanding things. It is becoming a place where work is planned, executed, reviewed, corrected, published and repeated. That is a very big change, especially for people who already use ChatGPT seriously every day. In the release video, OpenAI presented three linked developments: the GPT-5.6 model family, ChatGPT Work, and a new desktop app that brings Chat, Work and Codex closer together. The transcript describes Sol as coming to paid users, Terra and Luna as coming to free users, and ChatGPT Work as a new way for ChatGPT to perform complex tasks across web, mobile and desktop. It also describes a desktop experience where ChatGPT can work with local files, browser tabs and apps, while hosted Sites allow users to create and share interactive websites or dashboards. That is the shift. ChatGPT is not just answering. It is starting to do. The three-model family: Sol, Terra and Luna OpenAI now describes GPT-5.6 as a family of models with three durable tiers: Sol, Terra and Luna. Sol is the flagship model. Terra is the balanced model for everyday work. Luna is the most cost-efficient model. That naming matters because it gives users a more practical way to think about model choice. Instead of only asking “what is the best model?”, the better question becomes: “what is the right model for this job?” Sol is for the hardest work. It is the model OpenAI positions for complex coding, agentic workflows, cyberview source ↗
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X X / Twitter 2mo ▲ 349 neutralhttps://t.co/Eu2wIdFJDJ https://t.co/Eu2wIdFJDJview source ↗
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X X / Twitter 2mo ▲ 32 neutralhttps://t.co/B5bRGzgw48 https://t.co/B5bRGzgw48view source ↗
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X X / Twitter 2mo ▲ 124 positive pricing / modelBOOM GROK 4.5 IS OUT! Grok 4.5 has now been officially released and is available via the SpaceXAI API, Grok Build, and integrated into Cursor. This follows Elon Musk’s earlier announcement of strong beta feedback and accelerates the public rollout. SpaceXAI positions it as its strongest model to date, specifically o… BOOM GROK 4.5 IS OUT! Grok 4.5 has now been officially released and is available via the SpaceXAI API, Grok Build, and integrated into Cursor. This follows Elon Musk’s earlier announcement of strong beta feedback and accelerates the public rollout. SpaceXAI positions it as its strongest model to date, specifically optimized for coding, agentic tasks, and knowledge work. The official announcement emphasizes training alongside Cursor and reinforcement learning on hundreds of thousands of multi-step engineering tasks. It highlights practical strengths in building functional applications, complex spreadsheets, presentations, and documents. Key Specifications and New Details • Architecture: 1.5-trillion-parameter V9 foundation model, trained on curated datasets spanning coding, science, engineering, and mathematics. • Specialization: First Grok model explicitly trained for coding and agents, with supplemental Cursor data and extensive RL on real engineering workflows. • Inference Speed: Served at fast-model speeds of approximately 80 tokens per second. • Pricing: $2 per million input tokens and $6 per million output tokens — competitive for frontier performance. • Availability: Live now on the SpaceXAI API (model name: grok-4.5), Grok Build, and Cursor. Not yet available in the EU (expected mid-July). Microsoft Office plugins for Word, PowerPoint, and Excel are also rolling out. Performance and Benchmarks Independent benchmarks are now public, providing concrete data beyond internal claims. Grok 4.5 shows particular strength in agentic and engineering-focused evaluations: • Harvey’s Legal Agent Benchmark: #1 score. • DeepSWE 1.0 (within each model’s harness): 62.0% — ahead of Opus 4.8 (max) at 55.75% and competitive with GPT 5.5 (xhigh) at 64.31%. • DeepSWE 1.1 (mini-swe-agent harness): 53%. • Terminal Bench 2.1: 83.3% — ahead of Opus 4.8 (max) at 78.9% and close to top performers. • SWE Bench Pro resolve rate: 64.7% (Opus 4.8 max: 69.2%; Fable max leadsview source ↗
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X X / Twitter 3mo ▲ 94 neutralhttps://t.co/sC6KVRr4EJ https://t.co/sC6KVRr4EJview source ↗