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智谱的GLM 5.3的确是强,这两天刚发布的Terminal Bench 4.0,在原来的基础上去除了很多已经饱和的任务,主要修复了旧的任务问题。但是这个新的评测结果GLM 5.3排名第三,仅次于Fable 5(可能是安全限制?),好于GPT-5.6,的确是可以的
实际测试的Codex的Plus订阅的额度,基本上GPT-6.1 Sol可以在5个小时完成15个任务左右,根据复杂度不一样。而GPT-6 Astra可以完成5次。这两个5小时额度分别站周额度的1%和3.1%左右,也就是ChatGPT的Plus会员用GPT-6.1 Sol一周可以做100个任务。如果和ChatGPT共享额度,那就基本没打完了。
Replying to @LLMLearnerAI
Codex usage on Plus:
• GPT-6 Astra: 20.9% of the 5-hour quota per task
• GPT-6.1 Sol: 6.1% per task
That's just ~5 Astra or ~16 Sol tasks to exhaust the entire 5-hour allowance, ignoring resets.
Unless the shared quota increases, Plus could become very limiting.
OpenAI将Pro级别订阅的使用量翻倍了,但是plus保持不变,这么一看,20美元订阅ChatGPT几乎是毫无意义了,不软转为Claude
Day 25/
We are doubling all usage limits for all Pro 100/200/500 tiers and Business Premium, effective today.
We heard your kind feedback and won’t be reducing usage limits for Pro 200, so your Work and Codex usage will stay the same. We’re also going to continue offering extended limits for dots for now, and usage of your dot will still continue to be separate from your default usage.
And we'll of course also keep shipping better models and other efficiency improvements that increase your effective usage over time.
DataLearner retweeted
software engineers are going to have to tackle a new set of problems to unlock powerful multiagent systems to solve the world's hardest problems - right now is one of the most interesting moments in history to be an engineer.
来了 Anthropic提交S-1表格了 正式开启上市进程了 还没看到具体以估值多少上市,打算融资多少
Anthropic has filed an S-1 registration statement with the SEC related to its proposed IPO.
Read more: anthropic.com/news/s1-sec
Legal disclaimer: A registration statement relating to these securities has been filed with the SEC but has not yet become effective. These securities may not be sold, nor may offers to buy be accepted, prior to the time the registration statement becomes effective. This post does not constitute an offer to sell or the solicitation of an offer to buy these securities, nor shall there be any sale of these securities in any state or jurisdiction in which such offer, solicitation or sale would be unlawful prior to registration or qualification under the securities laws of any such state or jurisdiction.
感觉OpenAI有点不太给力,战略方向总是变化,产品运营有点像国内鸡贼。目前codex额度消耗过快,没有5小时限额解除之后可以继续工作,Dots这个agent普通20美元订阅者不可使用。GPT-6.1 Sol虽然还可以,但是相比Opus 5.5没有啥优势。OpenAI的人不够纯粹啊,运营有点不太行感觉。
大模型的坟墓🤔
Replying to @LLMLearnerAI
Built it in ~2 days. Started with Claude Code + Fable 5.1 and somehow burned ~$80, then moved most of the work to Codex + GPT-6 Astra Low (~10M input tokens). ChatGPT did the artwork, Gemini did the music.
visit: llmlearner.com/graveyard
这个数据有意思 GPT-6 Astra的tokens使用效率比较高 使用low模式基本上不会比GPT-5.6 Sol high高不了多少
DataLearner retweeted
In Codex / Claude Code we can talk to the agent while it’s still working in 4 ways: 1) Steer: change what it does next 2) Queue: add work for later 3) BTW: ask something without interrupting 4) Interrupt: stop it
Looks like a small UX feature, but changes the architecture.
OpenAI说GPT-6的需求太大了 服务器快搞不定了 如果这样继续下去 就要限制新增pro用户了 我去 这是催着大家有机会赶紧订阅pro啊
Demand for Astra is really unprecedented. We're pulling all the levers possible to sustain the demand, but I've not seen anything like it until now and we went through very steep growth before. Priority will always be to keep excellent service for existing users, but we might have to pause new Pro subscriptions for a bit if this continues.
这个数据挺有意思:一次 GPT-6 Astra 的 Codex 任务,11 分钟消耗了约 90% 的 5 小时额度,但 97.8% 的输入已命中缓存,最终输出也只有 1.1 万 tokens。看样子Codex额度消耗最大的像是长上下文下反复进行「推理 → 调工具 → 获取结果 → 再推理」的 Agent iteration 本身非常昂贵,而不是单纯输出长度
这么看 OpenAI GPT-6模型训练完成到大规模提供服务也就2个月时间 很快啊
Replying to @LLMLearnerAI
Another implication: frontier models can be useful internally well before launch.
GPT-6 Astra-class RL was active by July 20; GPT-6 Astra launched Sep 3.
That’s ~6 weeks from documented internal RL/safety work to rollout—not “training finished,” but a short deployment window.
这里还有个可能,其实GPT-6 Astra区分为Pro版本和普通版本。当前codex里面似乎没有开放Pro版本的使用
目前为止我还没觉得 GPT 6 Astra 在开发方面比 Fable 5.1 更强,差不多是 Fable 5 的水平,但是速度很快,比 Fable 耐用。
这其实带来的优势很明显,首先绝大部分场景不需要 Fable 那么强的智能,但是 Opus 5 又不聪明又慢。而现在 Astra 就是绝大部分任务表现的足够聪明胜任,速度又快,而且 Token 消耗没有 Fable 那么夸张,加上 Tibo 时不时送重置卡,这套组合下来优势会相当明显。
另外还有 UI 方面 Astra 有明显提升,但是目前我测试下来还是不如 Fable,细节上很多问题,但是你纠正一下它还是能改好。
写作方面还没有深入体验,比 GPT 5.6 强。
综合来说我接下来应该会更多的使用 Astra 在大部分任务上,但是更复杂的任务或者是 UI 设计产品设计的任务,还是会优先考虑 Fable 5.1(如果还有额度的话,太不耐用)。
当然这只是我目前为止的结论,我也没去测试做游戏和3D,那些不是我目前关心的,估计后面还会有些修正。





















