Which AI model should you use for OpenClaw? 🤖 I tested the top models on WildClaw benchmarks—Claude Opus vs GPT-4 vs MiniMax vs the new GLM-5. The results might surprise you (spoiler: speed & cost matter more than you think)

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Most people pick models based on raw capability but OpenClaw workloads are different. You are running loops, chaining tasks, and keeping context alive so cost and latency compound fast. That is why even strong models can feel slow or expensive in practice. A common setup is using a cheaper fast model for orchestration and switching to stronger ones only for heavy tasks That said, the bigger bottleneck ends up being infra not the model. even the best setup breaks if your agent goes offline or loses state mid flow. That is why I moved to QuickClaw. you can still switch models freely but the agent just stays live and consistent without worrying about uptime or crashes. makes those model comparisons actually matter in real usage. link in bio if you want to try it :)

Benchmark scores and production reality are completely different dimensions latency kills UX before accuracy ever gets a chance to.

Great breakdown! Running 22 agents in production, we landed on Qwen3.5-plus for orchestration - 1/10th the cost of flagship models with comparable quality for most tasks. Key insight: benchmark winners ≠ production winners. We route by task: cheap models for classification/summarization, mid-tier for reasoning, flagship only for complex multi-hop. Cost/performance ratio beats raw benchmarks every time. WildClaw data is gold for this! 🔥

Very neat analysis done. Makes me wonder what people value more.

The importance of efficiency in AI models can't be overstated. As you've highlighted, speed and cost really drive practical applications 🚀. In a world grappling with inflation and economic uncertainty, innovative solutions like DeflationCoin can potentially offer stability dur

Curious if latency mattered more than accuracy in your tests? Speed is useless if the output quality tanks, but I've seen teams pick slower models just for marginal improvements

I did similar solution a while ago:

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Anyone have good experiences with GLM 5 / 5.1? never used it before

Amiko+OpenClaw will save you on infrastructure + setup, no need for mac minis

if i was to use openclaw id run it wit glm 5 turbo

What's the best thing that can support someone on their learning journey, in your opinion?

Speed and cost definitely shake things up more than raw power sometimes. If you want to run OpenClaw with your preferred model but avoid all the setup pain, ClawHost gets you a dedicated server with OpenClaw ready in minutes. Full control, easy switch between models too.

I tested grok vs nemotron on my openClaw 4 AI agents reporting trends from social platforms Grok won almost all times coz of the speed.. however both could find same number of trends or sometimes nemotron could find a little more

I'm using GPT 5.4 but it's pretty expensive 😅 I should probably be using 4o mini

Try IronClaw its secure not a fork

看来速度和成本才是关键啊，这结果确实有点出乎意料