rbitar

Fantastic, this looks excellent and excited to try it

I regularly use @ key to add files to context for tasks I know require edits or patterns I want claude to follow, adds a few extra key strokes but in most cases the quality improvement is worth it

Congrats to the team, I'm surprised the industry hasn't been as impressed with their benchmarks on token throughput. We're using the Qwen 3 Coder 480b model and seeing ~2000 tokens/second, which is easily 10-20x faster then most LLM models on the market. Even some of the fastest models still only achieve 100-150 tokens / second (see OpenRouter stats by provider). I do feel after around 300-400 tokens/second the gains in speed feel more incremental, so if there was a model at 300+ tokens/second, I would consider that a very competitive alternative.

Really excited for this product, the industry needs alternatives to WebContainers which has become more restrictive around licensing. Also great to see that non-node runtimes (ruby / python) will be supported. Having said that, really wish this was open-source, even if that meant the OSS version had more limited features then the commercial alternative.

This token throughput is incredible and going to set a new bar in the industry. The main issue with the cerebras code plan is that number of requests/minute is throttled, and with agentic coding systems each tool call is treated as new "message" so you can easily hit the api limits (10 messages/minute).

One workaround we're doing now that seems to work is use claude for all tasks but delegate specific tools with cerebras/qwen-3-coder-480b model to generate files or other token heavy tasks to avoid spiking the total number of requests. This has cost and latency consequences (and adds complexity to the code), but until those throttle limits are lifted seems to be a good combo. I also find that claude has better quality with tool selection when the number of tools required is > 15 which our current setup has.

Self-hosting is definitely something we are keen to explore as most of the cloud solutions have resource constrains (ie, total active MicroVMs and/or specs per VM) and managing billing gets complicated even with hibernation features. Great project and we'll definitely take it for a spin

Looks great and excited to try this out. We’ve also had success using CodeSandbox SDK and E2B, can you share some thoughts on how you compare or future direction? Do you also use Firecracker under the hood?

Excited to try this out, it will solve two problems we’ve had: applying a code diff reliably and selecting which files from a large codebase to use for context.

We quickly discovered that RAG using a similarity search over embedded vectors can easily miss relevant files, unless we cast a very wide net during retrieval.

We’ve also had trouble getting any LLM to generate a diff format (such as universal diff) reliably so your approach to applying a patch is exciting.