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Collect ideas for tomorrow. Explore tools for the week. Start fresh, all in one place.

102 finds. 9 distinct perspectives.

THE WEEKLY EDIT

Fresh morning edits when there’s news · weekly digest otherwise

Inspiration

19 PICKED

Tools Developer tools & creative kits

30 TOOLS

01Frameworks & libraries

02Developer tools

03Design tools

04UI components

05CSS tooling

Articles Ideas worth studying

8 PICKED

Product Hunt This week’s launches

5 LAUNCHES

LLM Stats A daily model leaderboard

TOP 10

RankModelScorePrice / 1M
1Claude Opus 5.559.9$ 4.76
2Gemini 4 Carbon58.8—
3Claude Sonnet 5.557.9$ 2.38
4GPT-6 Astra57.3$ 11.90
5Kimi K3.1 Pro55.6$ 2.38
6Gemini 4 Argon54.4$ 2.38
7Claude Mythos Preview54.3—
8Claude Opus 553.4$ 5.95
9GPT-6.1 Sol53.4$ 2.38
10Muse Wonder Full53.1—

Open LLM Stats An open-source model leaderboard

TOP 10

RankOpen LLM ModelScore
1Kimi K3.1 Pro55.57
2Kimi K351.35
3DeepSeek-V4.1-Flash-101750.88
4GLM-5.350.51
5Qwen3.8 Max50.43
6LongCat-2.549.96
7DeepSeek-V4-Pro-081349.49
8DeepSeek-V4.1-Flash49.45
9Hy4 preview49.07
10MiMo-V2.6-Pro48.49

News The signal behind the scroll

4 PICKED

01Developer tools

GPT-6.1 Terra

GPT-6.1 Terra It's always interesting to note which aspects of a new model are emphasized in the release announcement. In the case of GPT-6.1 Terra, OpenAI went with visual reasoning and computer use: We’re introducing GPT-6.1 Terra , a fast, efficient model that combines detailed visual reasoning and precise computer use alongside clearer, more natural writing. A significant step up from GPT‑5.6 Terra, it excels at the communication and computer-based tasks that fill the workday, from drafting proposals and interpreting technical drawings to filling out forms and editing videos. Terra sits in the same position as Sonnet in the Anthropic model collection - not the cheapest or the most expensive, making it harder to decide when to use it. Computer use is a good example of a task that benefits from a less expensive model, since you might put it to work on automated, repetitive tasks. OpenAI's Ted Sanders provided some useful advice in a comment on Hacker News: In the case of GPT-6.1 Terra, I'd say Terra is probably better than Astra and Sol at technical communication, similar on vision and computer use (but much faster!), and a bit worse on most other things. For API developers, it's a nice midrange option if you want something cheaper than Sol but a lot smarter than Luna (especially for vision / computer use / communication). For subscribers, it's not a bombshell release - if you're hitting usage limits, maybe it helps you go a bit further, and if you want clearer communication or faster computer use, it can be a nice option to select. Here are the pelicans for the different reasoning levels. This pelican for "max" cost 11.3161 cents and took 4 minutes and 11 seconds: Here's a new comparison grid showing pelicans for every reasoning level of OpenAI's current frontier lineup: GPT-6 Astra, GPT-6.1 Sol, GPT-6.1 Terra, and GPT-6 Luna. GPT-6.1 Terra is priced at $1/million input tokens and $5/million output - almost half the price of GPT-5.6 Terra and GPT-6.1 Sol, and around 10x the price of GPT-6 Luna. Via Hacker News Tags: ai , openai , generative-ai , llms , llm-pricing , pelican-riding-a-bicycle , llm-release , gpt , ted-sanders

SimonNov 2
02Developer tools

Introducing Kimi K3.1 Pro

Introducing Kimi K3.1 Pro Kimi K3.1 Pro landed on the Kimi API today - it's not yet open weights, but Moonshot promise "Full model weights will be released by Nov 4, 2026". They're also offering a "Highspeed" version that's 2-3x faster, at twice the price (except for input token cache hits, which are priced the same). The US dollar pricing is $2.00/million tokens for input and $10/million for output - the same as GPT-6.1 Sol and half the price of Claude Opus 5.5. Moonshot's own benchmarks show Kimi as approximately level with Opus 5.5 and GPT-6 Astra - beating them on a few benchmarks, coming close on others. Artificial Analysis scored Kimi at 55 - ahead of Claude Fable 5.1, GPT-6 Astra, and Gemini 4 Argon (all at 53) and behind only Claude Opus 5.5 (58). This is the first time a (soon-to-be) open weight model has scored this highly against the frontier. I tried it out via the Moonshot API using the llm openai endpoint command I added to LLM 0.32 back in August: llm openai endpoint \ https://api.moonshot.ai/v1 \ --key kimi \ -m kimi-k3.1-pro \ "Generate an SVG of a pelican riding a bicycle" \ --responses \ -o reasoning_effort low \ > kimi-k3.1-pro-pelican-low.stdout.txt \ 2> kimi-k3.1-pro-pelican-low.stderr.txt llm openai endpoint can run prompts against any OpenAI-compatible endpoint but doesn't log the results, hence the extra options to save stdout and stderr (the reasoning trace). Here are the pelicans I got for Kimi K3.1 Pro on the three reasoning levels it supports - low, medium, and max. This is max: For comparison, I ran fresh pelicans against Kimi K3 on those three reasoning levels. Via Hacker News Tags: ai , generative-ai , llms , llm , llm-pricing , pelican-riding-a-bicycle , llm-release , ai-in-china , moonshot , kimi

SimonNov 2

AI tools AI tools worth knowing

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Design/Dev Resources Design resources worth saving

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End note

Every find. A little more perspective.

All 102 items, across 9 categories. Now go make something good.

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