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Use GLM-5.3 in Cursor today via tokengo API

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Use GLM-5.3 in Cursor today via tokengo API

Hi HN, Hearing a lot of buzz around GLM-5.3, which I expect to be the best open-source coding model with the weights dropping soon, I wanted to test it where I actually do my work. I just mapped GLM-5.3 to TokenGo so I could swap out the base URL and use it directly in my IDE. The backend handles the edge routing via Cloudflare to keep latency low, critical when you're waiting for inline code completions. If you want to try GLM-5.3 (or glm-5.3-flash) in your own workflow, here is the setup. For Cursor: Go to Settings > Models. Add your API key in the OpenAI API Key field. Toggle "Override OpenAI Base URL" and set it to: https://api.tokengo.com/v1 Under "Model Names", add z-ai/glm-5.3. Select it in your chat panel dropdown. We're one of the first inference providers to get the GLM 5.3 family online and fully accessible for IDEs. If you'd like to try it in a high volume production workload I'd be happy to provide test keys for yall

Visit productView on Hacker NewsAug 26, 2026
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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, model, models · Missing: mac, agents, macos
91%91% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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