Every week, I organize 400 to 700 links into roughly 60 categories as part of my ongoing effort to learn about AI. This is my personal notebook, which I enjoy sharing with friends… a hobby and a labor of love, rather than a commercial publication or product.
If you arrived here through a search or shared link, this page collects the links I found for Moonshot for the week ending July 31, 2026.
As part of my learning process, I like to automate the category covers. It gives me a chance to learn Python and APIs.
This week’s cover prompt was written using Claude Opus 4.7, and the image was generated using Gemini 3.1 Flash Image Preview.
Category Cover Image Prompt: A 1973 Chevrolet Chevelle Malibu in matte primer gray idling at the end of a long empty desert highway at night, aimed straight toward a huge low sodium-amber full moon on the horizon, a tiny golden-yellow scorpion hood ornament silhouetted against the moon's disc, warm red taillight trails and distant city sodium glow behind, 'Moonshot' scrawled across the upper sky in hot magenta-pink handwritten brush script with a faint glow, 1980s neo-noir movie poster, 35mm anamorphic grain with soft halation, long-lens compression, crushed blacks, generous cinematic negative space.
This Week in Moonshot News
Summary by Claude Sonnet 5.5 based on this week’s links:
- Release and licence: Moonshot released Kimi K3 as a 2.8T-parameter open-weight model with a technical report. Its MIT-inspired licence requires a separate agreement for companies earning over $20M a year, and Artificial Analysis labelled it 'Commercial Use Restricted'.
- Open-weight lead: Artificial Analysis rated K3 the top open-weights model at 57 on its index, with the gap to the best proprietary model down to 4 points. Arena ranked it #1 among open models in Frontend Code and Agent Arena, and Cognition called it the first open source model it tested to approach frontier-level performance.
- Day-0 availability: Many providers had K3 running at launch, including Cursor, Together, Baseten and Ollama's cloud. vLLM supported it on NVIDIA and AMD hardware from day zero. Running it locally is harder: Unsloth shrank it to a 594GB 1-bit version that keeps about 78.9% accuracy.
This summary was generated by Claude Sonnet 5.5 to help you explore the links below. Rest assured, I select, organize, and check the links by hand in Google Sheets, and write the introduction and personal commentary in The Main Newsletters myself each week as a labor of love.
This week's links related to Moonshot
Big update: Among open-weight models, Kimi K3 (Max) is #1 in the Agent Arena with +9.75% net-improvement, surpassing GLM-5.2 (Max) at +7.12%, and landed the #1 spot across 5 signals (see below). Kimi K3 (Max) is also now #1 in open-weight in the Frontend Code (1682 pts) and Text”
https://x.com/arena/status/2081804108433072623
We had Kimi K3 recursively self-improve the Cline harness to improve its own performance. 17 hours later, it went from 77.5% to 88.8% on Terminal Bench, and cut run cost from $79 to $49.8.”
https://x.com/cline/status/2082544250148057240
Open weights intelligence advanced today with the release of Kimi K3. The gap between the leading proprietary and open weights models is now just 4 points on the Artificial Analysis Intelligence Index, the smallest it has been since the GLM-5 release in February @Kimi_Moonshot’s”
https://x.com/ArtificialAnlys/status/2081926991788626011
China’s free Kimi K3 AI model shakes up global tech market – Rest of World
https://restofworld.org/2026/china-moonshot-kimi-k3-free-sovereign-ai/
Kimi K3 License: MIT + these 2 points: 1) Large AI hosting companies earning over $20M/year need a separate agreement. 2) Products over 100M users or $20M/month revenue must display “Kimi K3.””
https://x.com/petergostev/status/2081762420947562928
Kimi K3 license. It’s inspired by MIT but distinctly non-commercial, where any company making over $20M/yr must get a specific commercial deal (and display Kimi K3 if over 100M users or $20M/mo revenue)”
https://x.com/natolambert/status/2081760901020201086
Moonshot AI Surpasses Funding Goal to Hit $35 Billion Value – Bloomberg
https://www.bloomberg.com/news/articles/2026-07-29/china-s-moonshot-ai-passes-funding-goal-to-hit-35-billion-value
Moonshot Openly Defies The Trump Administration By Seeking Access To Additional NVIDIA GPUs For Training The Next-Gen Kimi K4 Model
https://wccftech.com/moonshot-openly-defies-the-trump-administration-by-seeking-access-to-additional-nvidia-gpus-for-training-the-next-gen-kimi-k4-model/
As we mentioned, success rates stayed close, but speed and token efficiency split between harnesses: – Success rate: 22/28 for Kimi Code, 21/28 for Hermes, 20/28 for Claude Code – Median time per task: 179s in Hermes, 297s in Kimi Code, 348s in Claude Code So the fastest”
https://x.com/composio/status/2082452274140311565
On FrontierCode 1.1 Extended, our benchmark for real-world engineering tasks that grades mergeability and quality, Kimi K3 scores 58.2% with a 63.6% pass rate. Within Devin, it excels on reproducing bugs and managing its environment effectively.”
https://x.com/cognition/status/2081766143090737223
Kimi K3 is now available in Devin Desktop and CLI. On FrontierCode 1.1, Kimi K3 is the first open source model we tested that approaches frontier-level performance.”
https://x.com/cognition/status/2081766141454925992
Kimi K3 is now in Cursor! It scores close to the frontier on CursorBench. It’s available on US-based inference thanks to our partners Fireworks, Together, and Baseten. Zero Data Retention is also supported.”
https://x.com/cursor_ai/status/2081848014444876166
Kimi K3 is now live on @togethercompute! Happy to have Together AI as our day0 launch partner, giving developers immediate access to K3 through high-throughput inference optimized for coding agents and production workloads. A huge thank-you to the Together AI team for”
https://x.com/Kimi_Moonshot/status/2081804933188501886
We’ve open-sourced AgentENV in collaboration with kvcache-ai. AgentENV is a distributed system for running agent environments at scale. Its components power agentic RL training for Kimi K3, with fast snapshot, resume, and fork support for large-scale parallel agent workflows.”
https://x.com/Kimi_Moonshot/status/2081762978391843020
🧩 Kimi K3 Trained Nine RL Experts, Then Distilled Them into One Model Kimi K3’s open weights and technical report reveal more than a 2.8T-parameter MoE architecture. They also describe an unusually ambitious post-training system for long-horizon Agents. Zhihu contributor”
https://x.com/ZhihuFrontier/status/2082424226280288570
Kimi K3 has everyone’s attention. On July 30, hear @Kimi_Moonshot’s Feihu Tang explain the architecture and decisions behind it. He joins Jue Wang and Zain Hasan from Together AI for a deep dive into long-running agents and production inference.”
https://x.com/togethercompute/status/2082144534394273811
My conversation with Sam Altman (@sama), CEO of OpenAI. We discuss: – Kimi, distillation, and open source – OpenAI’s compute bets – The Hugging Face incident – What happens after AGI – Raising kids in an age of abundant intelligence – And much more Enjoy! TIMESTAMPS 0:00 Intro”
https://x.com/patrick_oshag/status/2082073587142234374
New blogpost from our @MATSprogram stream, with @koreankiwi1227 ! Both Kimi K3 and GLM 5.2 have been reported introducing themselves as Claude in public chats. We wanted to see how much this (potential distillation) changes their base personas?”
https://x.com/benji_berczi/status/2080646591061373067
We compared 1-bit Kimi K3 to Claude Opus 5 and GPT 5.6. We gave 4 models the same prompt: Create a glass aquarium whose side panel develops a visible crack and then bursts. 1-bit Kimi K3 GGUF ran locally on 4x B200s at 36 tok/s. GitHub repo:
https://x.com/UnslothAI/status/2082528683747873194
beautiful momentum for open source, kimi k3 open weight on monday, more and more frontier labs from around the world releasing very competitive models (thinking machine, poolside, motif, upstage…) also amazing releases from closed source labs, opus 5 matching mythos, gpt 5.6″
https://x.com/eliebakouch/status/2080898494710100042
Exciting news: Claude Opus 5 with Max reasoning is #1 in the Frontend Code Arena and Text Arena with factuality on! Claude Opus 5 with default reasoning high is also very strong landing #3 in Frontend Code Arena, right behind Kimi K3 – and #2 in Text Arena (factuality on). This”
https://x.com/arena/status/2081831019377004727
Kimi K3 is now available on Ollama’s cloud. To use it with Claude Code, run: ollama launch claude –model kimi-k3:cloud Currently Kimi K3 requires a Pro or Max subscription, and consumes extra usage credits. We’re quickly working on adding capacity to expand access.”
https://x.com/ollama/status/2081771120173408767
vLLM hit new peak bs=1 decode on Kimi-K3: 464 tok/s 🚀 Under a low-entropy reasoning workload, Kimi-K3 + DSpark on vLLM reaches 464 tok/s on batch size 1 with 4×4 GB300. This benchmark is fully reproducible with public image: vllm/vllm-openai:kimi-k3 and @inferact’s DSpark”
https://x.com/vllm_project/status/2082267336279814173
In Frontend Code Arena, Kimi K3 (Max) by @Kimi_Moonshot is ranked #1 among open and #1 overall! It’s the #1 open-weight model in all Domains: Brand & Marketing, Reference-Based Design, Data & Analytics, Consumer Product, Gaming, Simulations, and Content Creation Tools. And for”
https://x.com/arena/status/2081809520184209518
Kimi K3 weights have been released! Kimi K3 is now the leading open weights model at 57 in the Artificial Analysis Intelligence Index Moonshot has released the weights of their 2.6T parameter model under their ‘Kimi K3 License’ which we have labelled ‘Commercial Use Restricted’.”
https://x.com/ArtificialAnlys/status/2081821449745236270
Kimi K3 is available day-0 for on-premise deployment on @Dell Host the 2.8T frontier open intelligence in your own servers, with PowerEdge XE9780 Link to Dell Enterprise Hub below. GG @juanjucm @balaatdell @MichaelDell on the release”
https://x.com/jeffboudier/status/2081864251816231350
Kimi K3 has first class support for vLLM on NVIDIA! vLLM serves K3 across Grace Blackwell, Blackwell, Hopper, and NVL72 systems, also integrating with Dynamo to keep a model this large, fast and efficient at production scale. Available Day 0, the moment the weights went public.”
https://x.com/vllm_project/status/2082559386535550983
Kimi K3 runs on vLLM + AMD from Day 0! vLLM brings K3 to ROCm at launch, so teams can serve the full 2.8T parameter model on AMD Instinct hardware from the start. Broader Instinct performance tuning is also in progress! @vllm_project × @AMD × @Kimi_Moonshot”
https://x.com/vllm_project/status/2082534192517394479
𝗞𝗶𝗺𝗶 𝗞𝟯’s 𝗽𝗼𝘀𝘁-𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗿𝗲𝗰𝗶𝗽𝗲 Kimi K3’s technical report just dropped. K3 is a 2.8T-parameter open-weight MoE model. I went through the report, and here I share its post-training recipe. As we have seen through the DeepSeek V4 post-training recipe,”
https://x.com/BhavinJawade/status/2082134026475946235
The Kimi K3 architecture figure for yesterday’s big open-weight model release, along with some observations and thoughts. 1. Yes, it looks relatively complicated, but it’s essentially a scaled-up production version of their Kimi Linear model they released last year (scaled up”
https://x.com/rasbt/status/2082098201247600765
moonshotai/Kimi-K3 · Hugging Face
https://huggingface.co/moonshotai/Kimi-K3
Kimi K3 can now be run locally! ✨ The 1-bit model retains ~78.9% accuracy after we shrunk it from 1.56TB to 594GB (-62% size). Run on a Mac Studio + 128GB RAM device. Kimi K3 is the strongest open model to date. Guide:
https://t.co/1mVwOMLpDW GGUF:
https://x.com/UnslothAI/status/2082463988953367031
Running Kimi K3 on Hopper? We released an FP8-Block quantized checkpoint tuned for it. FP8 is native to Hopper’s tensor cores, so you get the throughput the H100/H200 are built to deliver. Day Zero support ready with @vllm_project. Weights – try it now:”
https://x.com/RedHat_AI/status/2082150579464188139
Releasing the model weights and technical report of Kimi K3. Kimi K3 is our most capable model: a 2.8T MoE model with native visual understanding and a 1M-token context window. New model architecture: 2.5x the intelligence per unit of compute, not just more params. Alongside”
https://x.com/Kimi_Moonshot/status/2081760186235289764
@cursor_ai Thrilled to be your inference provider for day 0 support of Kimi K3!”
https://x.com/baseten/status/2082051819010662420
Happy to have @FireworksAI_HQ as our day0 launch partner and bring Kimi K3 to more developers. With Fireworks, you can now deploy and fine-tune the 2.8T Kimi K3 model with just a few clicks!”
https://x.com/Kimi_Moonshot/status/2081767950588223507
Kimi K3 is available on @baseten in collaboration with vLLM! Baseten provides a fast, reliable production API for Kimi K3 with vLLM as a part of the inference stack. You can call the 2.8-trillion-parameter model now, without managing any of the infrastructure yourself.”
https://x.com/vllm_project/status/2082588600345178269
Kimi K3 is available on @digitalocean, served by vLLM! vLLM handles serving K3 efficiently; DigitalOcean makes it straightforward to deploy and scale on familiar infrastructure. Full 2.8T model with 1M-token context, available at launch. @vllm_project × @digitalocean ×”
https://x.com/vllm_project/status/2082557005739573661
Kimi K3 is now available on @digitalocean ‘s Serverless Inference! Developers can start building with our most capable model in minutes.”
https://x.com/Kimi_Moonshot/status/2081778998494007793
Kimi K3 is now available on @nebiustf! Excited to have Nebius as our Day 0 launch partner and bring fast, reliable access to Kimi K3 to more users.”
https://x.com/Kimi_Moonshot/status/2081771462676123810
Kimi K3 is now live on our Model APIs, day 0.”
https://x.com/baseten/status/2081760458747318359
Kimi K3 on Dynamo: deploy yourself aggregated/disaggregated!”
https://x.com/KranenKyle/status/2082202727543894459
Kimi K3 runs on @modal since Day 0 – powered by vLLM! vLLM provides the serving engine; Modal exposes it as a production endpoint that scales on demand. One deploy gets you the full model, and it grows with your traffic. @vllm_project × @modal × @Kimi_Moonshot”
https://x.com/vllm_project/status/2082583344597041559
This is all a bit theoretical. When Kimi weights go public, we’ll have an interesting conversation about unit economics vs V4. I suspect that V4 wins *crushingly* on anything below GB300 NVL72 (and there too, if less so), and the only argument for Kimi is that it’s a better model”
https://x.com/teortaxesTex/status/2080856545848393775
With Kimi K3 Day-0 on vLLM: Open Frontier Intelligence for Everyone 🚀 At 2.8 trillion parameters, Moonshot AI’s Kimi K3 is one of the most powerful open-weight models ever released. Starting today, you can serve it on vLLM the moment the weights are public. What K3 brings: 🧠”
https://x.com/vllm_project/status/2081767404598919213
We’ve added Kimi K3 to Perplexity and Perplexity Computer for Pro and Max subscribers. Kimi K3 in Perplexity is hosted exclusively on U.S.-based servers.”
https://x.com/perplexity_ai/status/2082188732585972120
💰 Kimi K3 Is Open, but Running It Is Anything but Cheap Kimi K3 is now officially open-weight. Moonshot AI has released the 2.8T-parameter model, its technical report, and three key infrastructure projects: MoonEP, FlashKDA and AgentEnv. But open weights do not automatically”
https://x.com/ZhihuFrontier/status/2082013716770664595
and blog post with the fully Kimi K3 implementation details:
https://t.co/JYL9CpMsuE 3/3″
https://x.com/vllm_project/status/2082267340406964601
if you ever want to feel dumb just read the Kimi K3 technical report”
https://x.com/maharshii/status/2082088643255263450
Kimi K3 Architecture Notes | Sebastian Raschka, PhD
https://sebastianraschka.com/blog/2026/kimi-k3-architecture-notes.html
Kimi K3 is live on Modal. Moonshot has shipped the world’s first open 3T-class model, and we’re a day zero launch partner. We trained a custom DFlash speculator for K3’s novel architecture so you can run it faster, losslessly. The most capable open model we’ve worked with by”
https://x.com/modal/status/2081763806774989112
Kimi K3 Scales Across Length, Depth, and Width @Kimi_Moonshot AI has released Kimi K3’s full model weights, technical report, and three pieces of training infrastructure: MoonEP, FlashKDA, and AgentEnv. The release reveals how K3 scales a 2.8T-parameter MoE model to a 1M-token”
https://x.com/ZhihuFrontier/status/2081990590741594139
Kimi K3 tech report does not disclose the number of training tokens A pity, because this is straight up the biggest model trained in China ever, and I suspect it’s well over 2e25 FLOPs, probably 3-4e25. The report is overall great.”
https://x.com/teortaxesTex/status/2081764014883848563
Kimi-K3/k3_tech_report.pdf at main · MoonshotAI/Kimi-K3 · GitHub
https://github.com/MoonshotAI/Kimi-K3/blob/main/k3_tech_report.pdf
The central change is not scale alone. Each architectural step changes what the model stores, how it updates that state, or how it retrieves information that a fixed-size state cannot preserve. Kimi K3 combines constant-state recurrent memory, periodic softmax retrieval, sparse”
https://x.com/baseten/status/2082056034521059749
this scaling law is a piece of art, kimi K3 recipe improves by ~2.5x over kimi K2 recipe the tech report is amazing”
https://x.com/eliebakouch/status/2081762200180453657
We’ve open-sourced FlashKDA, our high-performance CUTLASS-based implementation of Kimi Delta Attention kernels. It delivers 1.72×-2.22× prefill speedup over the flash-linear-attention baseline on H20, and works as a drop-in backend for flash-linear-attention. Explore on GitHub:”
https://x.com/Kimi_Moonshot/status/2081762799202746420
We’ve open-sourced MoonEP, our high-performance communication library for distributed MoE workloads. Built to make expert-parallel communication more efficient at scale, MoonEP helps reduce communication overhead in large MoE training and inference systems. Explore on GitHub:”
https://x.com/Kimi_Moonshot/status/2081763086281973847
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