Probe0 vs Bifrost
Bifrost is server infrastructure you deploy so a whole organisation can share providers, budgets and failover. Probe0 is a proxy that runs on your laptop and only cares about the coding agents you personally run.
An open-source LLM gateway written in Go by Maxim AI, self-hosted as a server in front of 20+ model providers, with an enterprise tier for clustering, RBAC and compliance.
| Feature | Probe0 | Bifrost | Edge |
|---|---|---|---|
| Where it runs | On your Mac. No Probe0 server exists | A Go server you deploy (Docker, npx, VPC) | Even |
| Setup for one developer | One proxy plus a certificate, once. Claude Code, Codex and Cursor all route through it | Deploy the gateway, then point each tool at its endpoint | Probe0 |
| Failover across providers | Weak local answers retry on the cloud. No health-based routing | Fallback chains re-weighted by live latency and error rate, across 20+ providers | Competitor |
| Model already loaded locally | First attempt goes to Ollama or LM Studio, cloud only on retry | Ollama is one provider among 20+ | Probe0 |
| Where a cache hit is served from | Local disk. A hit never touches the network | External vector store (Weaviate, Redis) over the wire | Probe0 |
| Semantic cache safety | Strict similarity floor, and refuses to match anything carrying tool calls | Semantic cache via an external vector store | Probe0 |
| Which process spent the money | Per-call ledger with model, tokens, real cost, latency and the calling process | Cost tracking, Prometheus metrics and tracing per key | Probe0 |
| What a cap does when you hit it | Warns, then pauses the run. Per run and per day | Hierarchical budgets per virtual key, team and customer | Probe0 |
| Plan-tier advice | Reads your real usage and tells you when your subscription tier is above what you use | Not a feature of the gateway | Probe0 |
Bifrost is the right answer for shared production traffic: Go instead of Python, single-digit microseconds of added overhead in Maxim's benchmarks, load balancing across 20-plus providers with fallback chains re-weighted on live latency, plus virtual keys, RBAC, SSO and clustering. None of that is what costs a solo developer money. What costs me money is three coding agents on one laptop and no idea which of them is burning the budget, and answering that by deploying and maintaining a server is out of proportion to the question. Probe0 installs one local proxy and one certificate, and after that every coding agent CLI on the machine routes through it with no per-tool configuration. Nothing leaves the Mac that did not already have to: there is no Probe0 server to send it to.
The modules each switch on and off independently and each report what they saved, so you can turn one off and watch the number move. Local Routing sends work to a model already running in Ollama or LM Studio and retries on the cloud when the local answer is weak. Model Tiering tries the cheap model first. Exact Cache lives on local disk, and a hit never opens a socket at all, which is a latency difference as much as a cost one. Request Coalescing collapses simultaneous identical calls into one upstream. Spend Guard sets a hard cap per run and per day, warns at a threshold, then actually pauses instead of sending a notification about money already spent.
The one place I think Probe0 is stricter than a general-purpose gateway is the semantic cache, and it is because of what coding agents are. A support bot serving a paraphrased FAQ can tolerate a slightly loose vector match. An agent mid-run cannot: a near-miss on a message carrying tool calls hands the model a result from a different file or a different command, and the run silently goes wrong. So Probe0 keeps a strict similarity floor and refuses outright to match any conversation carrying tool calls. The Recording ledger is built on the same instinct, showing model, tokens, real cost, latency and which process made each call, so a claimed saving can be checked rather than believed. That data also drives plan-tier advice, which will tell you when you are paying for a subscription tier above what you actually use. The honest limits: macOS only, private beta, sign-in with Google or GitHub, and no multi-user deployment at all.
The verdict
Bifrost is the better pick in one situation, and it is a real one: more than one person depends on the thing, so you need shared provider keys, per-team budgets, cross-provider failover and compliance controls. Everywhere else in my day, Probe0 is what I would install. It is one certificate for every coding agent on the Mac, a ledger that names the process that spent the money, a cap that pauses the run, and a cache whose hits never leave the disk, with no server to deploy and nothing to keep alive.
Questions
- Is Probe0 a Bifrost alternative?
- For a single developer on macOS, yes. Probe0 is a local LLM proxy that covers the same cost levers Bifrost covers for a team (caching, routing, spend caps) without running a server. For shared production traffic across many providers, Bifrost is the right tool and Probe0 does not compete with it.
- Do I have to reconfigure Claude Code, Codex and Cursor to use it?
- No. You install the local proxy and a certificate once, and every AI coding agent CLI on the machine routes through it. With Bifrost you deploy the gateway and then point each client at its endpoint.
- Can Bifrost use local models too?
- Yes, Bifrost supports Ollama as a first-class provider with chat, embeddings, streaming and tool calling. The difference is framing: for Bifrost local inference is one provider among 20-plus, while Probe0 treats local LLM routing as the default first attempt and only escalates to the cloud when the local answer is weak.
- How does Probe0 handle LLM cost control?
- Spend Guard sets a hard cap per run and per day, warning first and then pausing. Every call lands in a local ledger with model, tokens, real cost, latency and the process that made it, so you can see which agent spent the money rather than guessing.