Opus 5.5 is now available on Hyperbrowser 🚀 It handles most tasks as well as Fable 5.1, while costing about 40% less than Opus 5 on typical workloads Give it a task and watch it use the browser Try it now in our AI Agents Playground 👇

Opus 5 is now available in Hyperbrowser. It comes close to Fable 5's intelligence at half the price, and that it verifies its own work and keeps iterating until it succeeds. We paired that with stealth browsers and residential proxies. Just got scary good↓

We had one Kimi K3 browse 30 pages at once, on Hyperbrowser. Browserswarm spins up a swarm of cloud browsers that read the web in parallel and stream every page into a single shared context. One brain, many eyes. 428k tokens into one window, zero failures, one cited answer in just a few minutes.

We gave Gemini 3.5 Flash-Lite a multi-hop research task in a Hyperbrowser cloud browser: dig through GitHub's docs, find the REST API rate limits, check whether GraphQL differs, and summarize both. 24 steps. Multiple pages, navigation decisions at every hop, no hand-holding. It finished:

Here's one run: we gave it a real task and it finished in 5 steps. 21,173 input tokens, 863 output. The whole thing streamed live in the browser, every click and scroll visible. This is what "computer use" looks like when the model has an actual environment to work in.

Gemini 3.5 Flash-Lite is cheap and genuinely capable at computer use. Google's most affordable model. A computer-use model is only as good as the browser you give it. It's now live on Hyperbrowser: Stealth, proxies, captcha solving, and a live view you watch it work through. The perception is cheap now, we gave it the environment.

Task list, harness, and raw results are open source: github.com/hyperbrowserai/ex… Want to run your own agents on the same infra? Start free: hyperbrowser.ai

Benchmark summary:

Fable cost 6x more per completed task than Grok ($0.06 vs $0.01). Sol sat in the middle. Setup: live websites, one system prompt, one action space, no per-model tuning. Fresh cloud browser per trial, interleaved so no model saw a different web. Environment and API failures were tagged separately and excluded from model scores.

We benchmarked GPT-5.6 Sol (high), Grok 4.5 (high), and Claude Fable 5 on 24 browser tasks, run on Hyperbrowser with an identical harness, 3 trials per task. Fable 5 led overall at 78%, Sol 75%, Grok 4.5 69% and each specialized: Fable was perfect on reading, Sol was best at navigation (94%), and Fable led on forms and logins (89%). Full task set and harness are open source. The breakdown below ↓

Learn more about Hyperbrowser: hyperbrowser.ai

Try gpt-5.6 sol and the rest of the family on Hyperbrowser: app.hyperbrowser.ai/playgrou…

GPT-5.6 sol, running on hyperbrowser. Threw it at kayak. popups, cookie walls, a flight search that reloads every time you touch a filter. one task: sfo to jfk, one-way, top 3 results back as json. Openai’s flagship model, up against the sites that fight back ↓

GPT-5.6 terra in the hyperbrowser playground. Pointed it at a github repo. stars, forks, latest release, back as json in one pass. The everyday model, doing an everyday check ↓

GPT-5.6 luna is the fastest and cheapest of the family. Pointed it at hacker news. top 5 posts, points and comment counts, back as json in one pass. Smallest & cheapest model in the family, still gets it done ↓

GPT-5.6 sol is insane when paired with cloud browsers. Sol, Terra and Luna are now available on Hyperbrowser. Openai's most capable models yet, running computer use tasks on cloud browsers and sandboxes. here's how it performs ↓

Hyperbrowser: hyperbrowser.ai

Learn more about Hyperbrowser Sandboxes here: hyperbrowser.ai/docs/sandbox…

This is the part agents keep getting stuck on, spinning up a real environment, driving a real browser, cleaning up after. The model plans it. The sandbox runs it.