The VRAM leasing service for every GPU you run.
Lease. Hand off. Never collide.

Berth

Berth decides who gets your GPU. Chat models, image pipelines, voice engines, games and GPU apps lease the card instead of grabbing it, so two of them never load at once and crash each other with an out-of-memory error. One Go binary, no cloud account, nothing else to install.

What Berth does

Shares one card between everything

• Engines take turns. You start each one through berth run. When another needs the card, Berth unloads the holder (its own unload, then SIGTERM, then SIGKILL) and lets the next one in only after the driver shows the memory free.
• Priorities. foreground, interactive, batch, and hold above them all. A lower request waits and gets a reason naming the holder, never an OOM crash.
• No ping-pong. When two clients ask for different engines at once, a ranking picks one and the other waits, so the card stays put.
• ComfyUI at a job boundary. Berth waits for the running image job to finish before the handoff.
• Survives restarts. Upgrade or restart the daemon and your running engines stay up and re-attach.

Games and other apps

• Games take the card while you play. Launch a Steam, Lutris or gamescope game on Linux, or a Steam, Epic, GOG, EA, Ubisoft, Xbox or Battle.net game on Windows, and Berth drains your AI engines until you quit.
• Creative apps keep their memory. Berth names what Blender, DaVinci Resolve, OBS, Kdenlive, Premiere and After Effects hold and counts it against the card, without a stowaway report.
• Your own rules. [[claim]] in berth.toml covers anything else: a training run, a render farm job, a cracking session, by name, command line or launcher.
• berth hold frees the card for a call or a game you start yourself. Ctrl-C gives it back.
• berth run --pinned for an app that must never be stopped mid-work.

One API for your engines (preview)

• berth gateway: one OpenAI-compatible port. Name a model and Berth starts its engine, unloads whatever holds the card, waits for the load and streams the answer.
• It proxies ComfyUI's workflow API too, so an image request queues behind the same lease.
• Bearer key on every route, loopback only, browser origins refused.

Models

• berth pull hf:org/repo:Q4_K_M downloads from Hugging Face, resumes where it stopped, and checks every file against the size and sha256 the Hub publishes before using it.
• berth verify re-checks pulled models offline and names any file that changed.
• berth models lists every model on the machine (GGUF, safetensors, the Hugging Face cache, LM Studio and Ollama's stores) with quant, size, parameters, context and when each was last used, so you can see what earns its disk space.
• berth models export ollama turns a GGUF you already have into an Ollama model.

Sees everything on the card

• Finds your engines. Berth reads llama.cpp, llama-swap, Ollama, vLLM, SGLang, ComfyUI, Kokoro, LM Studio, KoboldCpp, TabbyAPI, LocalAI and more on their default ports, plus any OpenAI-compatible or custom server you name.
• Stowaways. Berth reports any process holding VRAM without a lease, with its PID, name and memory, and leaves it running.
• Built-in telemetry. Per-card memory, load, temperature, power and clocks; tokens per second, queue, latency percentiles, KV cache use, a token ledger and a per-model leaderboard; 30 days of history on disk.
• The harbor web UI (berth harbor): a departures board of leases, a collisions-avoided counter, charts and the event log. Read-only, loopback by default.
• Alerts to the desktop or a webhook, /metrics for Prometheus, and berth export for CSV or JSON.

Built for agents and scripts

• berth skill install teaches Claude Code, Codex, OpenCode and other agents to ask Berth for the card instead of killing GPU processes.
• Every command takes --format json|yaml, keeps results on stdout and diagnostics on stderr, and exits 0, 1 or 2 by one rule.

Runs on Linux with an NVIDIA GPU (supported) and Windows 10/11 with an NVIDIA GPU (experimental). Apache-2.0.

Status: alpha (v0.1). Runs daily on an RTX 4090 workstation beside llama-swap, NInfer, Strata, ComfyUI and games. Capabilities lists what works and has tests; the Roadmap lists what does not exist yet.

Quick start

go install github.com/T-Crypt/berth/cmd/berth@latest      # or a release binary, see Install
berth daemon &                                            # the broker for this card
berth status                                              # the card, leases, engines found
berth run --as llama --priority foreground -- llama-server -m model.gguf --port 8080
berth harbor                                              # the web UI on http://127.0.0.1:9798/

Preview

The harbor on an RTX 4090 running NInfer through llama-swap (real data, basic mode). The tide shows the card's memory by holder over six hours; the hatched stretch is a stowaway Berth reported while the model ran without a lease after a daemon restart.

The Engines & Requests tab: decode throughput, the token ledger and the per-model leaderboard.

Install

Two ways: hand it to your coding agent, or do it yourself. Both end in the same place: the daemon running as a user service, your engines wrapped in berth run, and the harbor UI on http://127.0.0.1:9798/.

Option 1: have your agent install it

Paste this into Claude Code, Codex, Cursor, OpenCode or any coding agent that can run shell commands on the machine with the GPU:

Install Berth (https://github.com/T-Crypt/berth), a VRAM lease broker for NVIDIA GPUs, on this
Linux machine, following its README and contrib/INTEGRATION.md. Steps:

1. Check prerequisites: Linux, an NVIDIA driver with `nvidia-smi` working, systemd user
   services. Stop and tell me if any is missing.
2. Download the latest release binary for this CPU (berth-linux-amd64 or berth-linux-arm64)
   and its SHA256SUMS from https://github.com/T-Crypt/berth/releases/latest, verify the
   checksum, and install it as ~/.local/bin/berth. (If Go 1.27+ is installed you may instead
   run: go install github.com/T-Crypt/berth/cmd/berth@latest.) Run `berth version`.
3. Install contrib/berthd.service and contrib/berth-harbor.service as systemd user units and
   start them. Confirm with `berth status`.
4. Find the inference engines on this machine (llama.cpp, llama-swap, Ollama, vLLM, SGLang,
   ComfyUI, LM Studio, KoboldCpp, TabbyAPI, LocalAI and so on): what runs them (systemd unit,
   llama-swap config, script) and on which port. Show me the list before changing anything.
5. For each engine I approve, wrap its start command in `berth run` as contrib/INTEGRATION.md
   shows (ComfyUI: contrib/comfyui.service with --drain-comfyui; Ollama: a systemd override of
   `ollama serve`). For llama-swap, wire the whole roster in one pass instead of one model at a
   time: `berth wire llama-swap --config <llama-swap config> --write` keeps a backup beside the
   file, keeps each model's original command, and `--check` exits 1 when a model is unwired.
   Ask me which engine wins the card (--priority foreground) and which waits (interactive or
   batch). Back up every file before you edit it and tell me how to undo each change.
6. Engines on non-default ports or other machines: add [[engine]] entries or
   [engines] discover_ports / discover_hosts to ~/.config/berth/berth.toml, then run
   `berth config check` and `berth engine check`.
7. Restart what you changed, then show me `berth status` with each engine leased and read,
   and the harbor at http://127.0.0.1:9798/. Do not expose the harbor beyond loopback unless
   I ask; it has no authentication.

The agent asks before it wraps anything, and every change it makes has an undo.

Option 2: manual

1. The binary. Download berth-linux-amd64 (or -arm64) and SHA256SUMS from the latest release:

cd /tmp
curl -fLO https://github.com/T-Crypt/berth/releases/latest/download/berth-linux-amd64
curl -fLO https://github.com/T-Crypt/berth/releases/latest/download/SHA256SUMS
sha256sum --check --ignore-missing SHA256SUMS
install -Dm755 berth-linux-amd64 ~/.local/bin/berth
berth version

Or build it: go install github.com/T-Crypt/berth/cmd/berth@latest (Go 1.27+, no C toolchain).

2. The daemon and the UI (one per machine, systemd user units from contrib/):

mkdir -p ~/.config/systemd/user
cp contrib/berthd.service contrib/berth-harbor.service ~/.config/systemd/user/
systemctl --user daemon-reload
systemctl --user enable --now berthd berth-harbor
berth status            # the card, leases, stowaways, engines found

Open http://127.0.0.1:9798/. Engines on their default ports appear on their own.

3. Wrap your engines so they lease the card instead of grabbing it. The pattern:

berth run --as <name> --priority <batch|interactive|foreground> -- <the engine's command>

Per-engine recipes (llama-swap, llama.cpp, Ollama, ComfyUI, vLLM, SGLang, custom) are in contrib/INTEGRATION.md.

4. Optional configuration in ~/.config/berth/berth.toml; validate with berth config check:

[metrics]
listen = "127.0.0.1:9797"      # Prometheus text, loopback only

[engines]
# discover = true              # default: probe the well-known engine ports every minute
# discover_ports = [9123]      # extra ports to probe
# discover_hosts = ["192.168.1.40"]

[[engine]]                     # anything discovery does not find, on any port
name = "llama-swap"
type = "llama-swap"
url  = "http://127.0.0.1:9090"

[alerts]
[alerts.queue]
warn = 4
crit = 10

Uninstall: systemctl --user disable --now berthd berth-harbor, remove the two unit files and ~/.local/bin/berth, and take berth run ... -- off any engine command you wrapped. History lives in ~/.local/state/berth/.

---

Engines

Engine	Reader (type)	Found on its own	What Berth reads
llama.cpp llama-server	llamacpp	:8080	tokens, rates, queue, context window, KV slots
llama-swap	llama-swap	:8080	every running model's upstream, request log, per-model window
Ollama	ollama	:11434	loaded models and their VRAM
vLLM	vllm	:8000	models, window; tokens and queue from /metrics
SGLang	sglang	:30000	models, window; tokens and queue with --enable-metrics
ComfyUI	comfyui	:8188	jobs running and queued, version; job-boundary handoff
Kokoro-FastAPI (text to speech)	kokoro	:8880	health, models, voice count, default voice
LM Studio	lmstudio	:1234	loaded models, context length
KoboldCpp	koboldcpp	:5001	model, context length
TabbyAPI (ExLlamaV3)	tabbyapi	:5000	models, context length
LocalAI	localai	:8080	models, tokens
Unsloth Studio	unsloth	:8888	health; models with an API key
FreeToken	freetoken	:1919	tokens, queue
NInfer	ninfer	as llama.cpp	as llama.cpp, plus draft acceptance
Strata	strata	:8080	model, window, tokens, queue
Any OpenAI-compatible server	openai	:8080, :8000	models
Anything else	custom	never	your health, models, metrics and slots paths; kind = "tts", "stt", "image" or "other" tracks a voice or image server as one

Every reader takes any URL, so any port and any host works. Engines that need a key name the environment variable that holds it (api_key_env); the key never goes in the file. An engine's figures are its own claims and are shown apart from what the driver measures.

---

Capabilities

Leasing (the core)

• Explicit leases. Engines start through berth run, which waits for a berth, starts the engine in its own process group, and gives the berth back when the engine exits.

• Priorities. foreground > interactive > batch. An equal or higher request asks the holder to drain; a lower one waits and is refused with a reason naming the holder (exit 75), never an out-of-memory crash.

• Handoff in steps. A drain tries the engine's own unload first (for llama-swap, its unload URL), then SIGTERM to the process group, then SIGKILL, each after a grace period.

• Measured release. Berth grants the next engine only after the driver shows the old holder's processes gone, since an exited process can still hold memory.

• Stuck releases are caught. A released lease whose memory never frees turns aground and keeps blocking, with a reason naming the process and how much it holds.

• Process identity is PID plus start time, so a reused PID never inherits a lease.

• Whole-card or sized leases. --needs-mib N lets engines that fit share a card.

• Fail-open, never silent. If the daemon is down, berth run still starts the engine but records it as an unprotected run that status shows (--fail-closed refuses).

• Survives a daemon restart. A running engine stays up when berthd restarts or is upgraded; berth run dials the new daemon and re-attaches by PID plus start time. For 15 s after a start the daemon grants nothing new while such engines are still due back, so nothing is loaded onto a card an engine already holds.

• ComfyUI at a job boundary. --drain-comfyui waits until ComfyUI's queue is empty before stopping it; a job in progress is never cut off.

• No juggling. Two engines at the same priority drain each other: the last one asked for wins, which is what you want when you switch models. When two clients want different engines at once, that flips the card back and forth and every request fails. Berth calls it a juggle when an engine is drained within juggle_window (15 s) of getting the card while it is still busy (a request in flight, a ComfyUI job queued, a model loading). The engine ranking decides a juggle: the winner keeps or takes the card, and the loser waits for it instead of draining it back. An idle holder hands over at once, so chat, then an image, then chat again is three clean handoffs.

  [priority]
  order = ["llama-swap", "strata", "comfyui"]  # first is best; omit to rank by use
  juggle_window = "15s"                        # a negative value turns it off

  Without an order, the engine with the most hours on the card through Berth over the last 7 days ranks first (kept in ~/.local/state/berth/usage.json); a tie leaves the holder in place. berth run --group NAME files a lease under an engine family: llama-swap runs each model under its own name, so give each --group llama-swap. berth status shows the ranking and a count of juggles stopped; the harbor log shows each one with the reason.

Games, apps and holds

• Claims cover work Berth does not start. berthd scans the process table every 2 s. A hold claim keeps the card while its process runs: engines are drained and wait, with a 15 s linger so a launcher restarting the game does not bounce the card back. A track claim names an app's card memory so it counts against the card without being reported as a stowaway; nothing waits on it.

• Built-in pack, on by default. Holds: Steam games (anything under Steam's reaper), Lutris and gamescope on Linux; Steam libraries (steamapps\common), Epic, GOG, EA, Ubisoft, Xbox and Battle.net games on Windows, with launchers, Wallpaper Engine and Lossless Scaling left out. Tracks: Blender, DaVinci Resolve, OBS, Kdenlive, Premiere, After Effects. berth claims shows every rule and what it matches now.

• Your own rules:

  [[claim]]
  name = "training"
  cmdline = 'train\.py'      # regex; on Windows it sees the exe's full path
  action = "hold"            # or "track"
  linger = "30s"
  
  [claims]
  builtin = false            # turn the built-in pack off

  A rule can also match exe names (globs, .exe optional), a launcher parent, and exclude with not_cmdline.

• berth hold [--for 2h] [--reason game] takes the card for you. It is a pinned lease at the top priority, so nothing drains it, and it ends on Ctrl-C, after --for, or when the process dies.

• berth run --pinned gives an app a lease that is never drained (it keeps the card until it exits).

• A hold cannot free memory held by something outside Berth: that memory is still reported, as contested.

Models

• berth pull hf:ORG/REPO[:QUANT|FILE|GLOB][@REV] resolves the revision to one commit, picks the GGUF for the quant (every part of a split model, and the vision projector when there is one), and downloads to ~/models/<org>/<repo>/.
• Integrity first. Each file lands as .part and is moved into place only after its size and sha256 match the Hub's published hash. A mismatch deletes it and fails.
• Resumes. Run the same command again after an interruption and it continues with a range request. A file already present and correct is skipped.
• berth verify re-hashes pulled models against the manifest the pull wrote (.berth-manifest.json: repo, commit, every hash), offline, and exits 1 on any change.
• Gated and private repos read $HF_TOKEN.
• berth models reads every GGUF header (never the weights) in the tools' usual places and any --dir or [models] dirs. Split models list as one; vision projectors and MTP or draft heads list with the model they belong to (--all shows them on their own). --usage 30d adds requests and tokens per file from the harbor's request log, matched through llama-swap's config when that is how the model is served.
• berth models show NAME prints one model's header: architecture, context, tensor types, chat template.
• berth models export ollama NAME [--dry-run] writes a Modelfile and runs ollama create; a split model needs llama-gguf-split --merge first.

Gateway (preview)

• One port for every engine. berth gateway proxies OpenAI-style requests to the engine that serves the requested model, streaming.
• Cold starts under a lease. An engine with start and serves in berth.toml starts on the first request that names one of its models, through the berth run path: lease, drain of the holder, measured release, then the start. One start per engine, however many requests arrive while it loads.
• Last switch wins. Give gateway-started engines the priority of the engine they replace (priority = "foreground" next to a foreground llama-swap) and each side drains the other on demand. A lower priority waits behind the holder instead.
• Clear failures. Unknown model: 404. A start the broker refuses or an engine that exits before it answers: 503 with the reason, the engine's last log line, a Retry-After and an error code a client can branch on: outranked (lost a juggle), drained_while_starting, no_berth, not_ready, start_failed or no_start. A model listed under serves by two engines fails berth config check.
• API key. Bearer token on every route; berth key prints it (created on first use, mode 600). Loopback only; browser origins and non-loopback Host names are refused.

Switch engines by naming a model

Two engines that each want the whole card can't run together, and most harnesses can't start an engine before they call it. berth gateway starts it for them. Give an engine a start command and the model names it serves in berth.toml:

[[engine]]
name     = "strata"
type     = "llamacpp"
url      = "http://127.0.0.1:8080"
start    = ["/path/to/strata/.venv/bin/python", "serve/server.py", "--engine", "strata",
            "--config", "strata-262k.json", "--port", "8080"]
serves   = ["router-strata", "qwen3.8-flash-next-iq2_xs"]
priority = "foreground"   # equal to the engine it replaces, so the last model you ask for wins

Run berth gateway (loopback 127.0.0.1:9799; a user unit is in contrib/berth-gateway.service) and send your requests there with the node's API key as the bearer token. The gateway creates the key on first start (~/.config/berth/api.key, mode 600) and berth key prints it, so a client that runs commands for its key never has the secret written into its config:

{ "baseUrl": "http://127.0.0.1:9799/v1", "apiKey": "!berth key" }

For each request the gateway:

1. reads the model name from the body;
2. hands the request straight to an engine that is up and lists that model (llama-swap and Ollama load their own models under their own leases);
3. otherwise starts the engine that serves it through the same path as berth run: it takes a lease, Berth drains the holder (llama-swap through its unload URL once its slots are idle, then SIGTERM, then SIGKILL), and the gateway waits until the new engine answers /v1/models;
4. proxies the request and streams tokens as the engine sends them.

Requests that arrive during a start wait on that one start. A model no engine serves gets a 404, and a start the broker refuses comes back as a 503 with the broker's reason. A start waits for the card no longer than --ready (10 minutes); if the holder has not left by then, the request fails and the start is dropped, so it cannot take the card hours later. Asking llama-swap for one of its models later drains the gateway's engine the same way, so either side can take the card back.

Measured on the reference RTX 4090 with an agent harness switching models between NInfer (through llama-swap) and Strata (262K context):

Switch	Drain of the holder	Request answered after
Strata on an empty card	none	106 s (Strata's own cold load)
Strata to NInfer	Strata released in 2 s	41 s
NInfer to Strata	NInfer released in 0.6 s	110 s

At no point did the two engines hold the card at the same time.

Long waits and idle clients. Cold starts take 41-110 s (table above), and forward writes zero bytes while ensure drains the holder and starts the engine: both proxies stream once the engine sends bytes (FlushInterval = -1) but send no keep-alive during the wait, and flushing a 200 early is unsafe for non-streamed bodies. If a client with an idle-connection timeout (OpenWebUI's is ~40 s) drops the wait first, raise its read timeout and prefer streamed requests. A stream-aware early flush needs its own ticket. The gateway serves /v1/chat/completions, /v1/completions, /v1/embeddings and a merged /v1/models, plus the ComfyUI surface: POST /prompt queues a workflow (starting ComfyUI under a lease when it is down, holding the request until its /queue answers), while /ws, /queue, /history/, /view and /upload/ proxy to a running ComfyUI. Every route needs the key. The gateway listens on loopback only, refuses a Host that is not a loopback name (DNS rebinding) and refuses any request that carries a browser Origin, so a web page cannot start an engine. ComfyUI already hands off at a job boundary under a lease (--drain-comfyui); a drain first unloads its models via POST /free, and --keep-comfyui-up leaves the server on its port for OpenWebUI instead of stopping it.

Visibility

• Stowaways: every process holding VRAM without a lease, with memory, identity and first-seen time; optional desktop notification and webhook. Report-only by design.
• Contested grants: a grant made while stowaways hold memory is flagged, not hidden.
• Event log: every request, wait, drain, release, free, stuck lease, stowaway and probe change, with gap-free sequence numbers; berth events -f follows it live.
• The collisions board: collisions avoided, VRAM handed off, drains, stuck releases caught, stowaways caught, contested grants, refusals. Each count links back to a recorded event. berthd keeps the board in ~/.local/state/berth/counters.json (--counters), so a restart or a reboot carries the counts on. The harbor stores a reading a minute and its ticket counter shows the last 5 min, 15 min, hour, 24 h or 7 days next to the all-time board (GET /v1/counters?range=5m|15m|1h|24h|7d).
• Alerts: one threshold table in berth.toml ([alerts]): warn and crit per key (queue, ttft, tpot, p95, cache, reingest, vram, temp, power, kv). The node evaluates it on its 5 s sample cycle, fires a desktop notification and webhook on entering a level, and logs alert.raised / alert.cleared events (berth events -f, the harbor log); a level stays until the value stays clear for clear_polls samples (default 3). GPU probe failure and aground leases are built-in danger alerts, always on. Default posture: no [alerts] table means no KPI alerts, and the notification channels are separately opt-in (--notify, --webhook). The harbor colors the same state the node notifies on: KPI tiles and GPU cells, a strip of the currently-breaching keys, and an overall LIVE / DEGRADED / OFFLINE state beside the connection pill.

Telemetry (built in, no other tool needed)

• GPU: memory, utilisation, temperature, power against its limit, fan, SM and memory clocks, PCIe link, for every card in the machine with its real limits.
• Host: CPU, RAM, swap, load.
• Engines: every engine in the table above, found on its default port or configured on any other. Loaded models, decode and prefill tok/s, token totals, queue, draft acceptance, the context window per model (llama.cpp/NInfer /props, Strata /health, llama-swap per model proxy), and the live KV slot pool (/slots: per-slot context tokens against the window). An engine without those endpoints degrades to "no window / no slot data", never an error. An engine that was up and stops answering is shown as unresponsive (latched), distinct from one that never ran.
• Requests: a 24-hour request log from llama-swap; requests per minute, p50 and p95 latency, prefill time, time per output token, cache and re-ingest share, a token ledger (1 h, 24 h, since start), a per-model leaderboard, and the most recent requests.
• History: the node keeps the last hour at 5-second resolution in memory. The harbor stores it on disk (SQLite, no C toolchain needed): 1-minute rows for 30 days, per engine the KV pressure (peak slot fill against the window) and the resident models' windows, hourly rows for 400 days, and the request log for 30 days, de-duplicated by request id. Databases written before the KV column is added are migrated in place on the first open; nothing is ever rewritten.
• Model timeline: when each model was loaded and unloaded on each engine, kept across restarts. A gap in the readings over 3 minutes is never drawn as loaded.
• The UI labels engine-reported figures as the engine's own, apart from what the driver measures.

Interfaces

• CLI: one command tree with one output contract. berth status, berth events -f, berth run, berth hold, berth claims, berth pull, berth verify, berth models, berth gateway, berth wire llama-swap, berth engine check, berth config check, berth config show, berth export, berth key, berth skill install, berth version. Berth runs fully headless.

  berth wire llama-swap --config cfg.yaml          # plan: which models lack a wrapper
  berth wire llama-swap --config cfg.yaml --write  # apply; a backup stays beside the file
  berth wire llama-swap --config cfg.yaml --check  # exit 1 when a model is unwired
  berth config check --strict          # a warning fails the check, exit 1
  berth config show --format toml      # the evaluated config, ready to save
  berth engine check -v                # what each engine reports, right now
  berth -q status; echo $?             # exit codes only, for CI
  berth status --format json | jq .leases

  Results go to stdout, diagnostics go to stderr. --format is human (the default), json or yaml, and berth config show also takes toml, the config's own file format. -v adds detail to the human view, and -q suppresses stdout and leaves the exit code as the answer. Exit codes are 0 (done), 1 (validation or logic: an invalid config, a warning under --strict, an engine that did not answer, a lease the broker refused) and 2 (berth could not do its job: unknown flag, missing file, berthd unreachable). berth run passes the engine's own status through and exits 75 when no berth was granted. Every read-only command changes nothing.

• Harbor web UI (berth harbor): a departures board of every lease, a boat ticket per lease, the collisions counter, berths with measured memory, stowaways, the event log, and engine metrics. The tide (card memory by holder) and the model timeline share a 1H / 6H / 24H / 7D / 30D picker; the Engines tab adds a queue KPI (the berth's own queue; each engine's own queue stays on its card), the KV pool (the live slots of each engine against their model windows, stored ranges the per-minute peak slot fill), context residency (the last requests' token figures against the model's window, plus the live KV sessions), a throughput chart, a 24H / 7D / 30D leaderboard and, in advanced mode, a storage panel. The top bar shows the overall state (LIVE / DEGRADED / OFFLINE) and a strip of the alerts currently breaching, colored from the node's own threshold state. Basic and advanced modes. Read-only, strict content security policy. It listens on loopback by default (127.0.0.1:9798); passing a non-loopback --listen address (e.g. 0.0.0.0:9798; a specific interface IP works too) is the explicit opt-in to expose it on your network: the startup logs a warning and the page shows a banner on every screen while exposed. There is no authentication in this release: expose it only on a network you trust; phones on that network get the full read-only dashboard. To reach it from elsewhere without exposing it, keep the loopback listener and put a same-machine reverse proxy in front (tailscale serve, caddy), passing the proxy's hostname with --allow-host. A systemd user unit is in contrib/berth-harbor.service.

• Prometheus /metrics (loopback only) for Grafana and friends.

• Footprint: the node uses about 0.2% of one CPU core and ~21 MB of memory on the reference box; the harbor about 0.4% and ~23 MB, writing to disk once a minute.

---

Support matrix

Platform	Status
Linux + NVIDIA	Supported
Windows 10/11 + NVIDIA	Experimental: leases, process attribution, job-object drains and game claims work; no installer yet, and the driver reports no per-process memory under WDDM, so use whole-card leases
AMD, Intel, Apple	Not supported yet (the telemetry layer is an interface for later backends)
Multiple GPUs	Inventoried with real limits; leases schedule one card per daemon today

---

Roadmap

Phase	What it delivers	Status
P0	Safety core: identity, measured release, stuck and contested detection, unprotected runs	Done
P1	Node API: event log, collisions board, config, engine readers, /metrics, light probe	Done
P2	Harbor web UI; native telemetry, request KPIs, ledger, leaderboard, stored history, measured against Speculum parity	Done
P3	berth hold and claims for games and apps (done); drain and hold from the harbor, behind authentication (planned)	Partly done
P3.5	Node gateway: one OpenAI-compatible port; engines start on demand under a lease and drain each other	Preview
P4	Restart reconciliation: engines re-attach after a daemon restart, nothing left unprotected	Done
P5	Fleet: berth install --harbor <addr> --join <token> on every machine; nodes push metrics into the harbor's store (already built for one box in P2)	Planned
P6	ComfyUI job-boundary handoff on Linux (done); ComfyUI started on demand through the gateway (done); Windows node (experimental)	Partly done
P7	Offers: a waiting request can offer for an idle card on another machine; the holder decides	Planned
P8	Multi-GPU scheduling: a lease table per card, "any card that fits"	Planned
P9	Organisations: single sign-on, roles, audit log, regional harbors	Planned
P10	Opt-in auto-yield: a card's owner can pre-approve offers for their own card	Later
P11	A staffed harbor: a local model routes leases and offers, seeing only VRAM metadata	Later

Next, in this order: a model library (berth models, with usage and Ollama export), Berth starting and swapping models itself the way llama-swap does, one gateway for every engine type on the machine, and engine install and update from upstream.

What Berth never does

• Kill a process it did not start, or any process by default.
• Grant a card because a process exited, before the driver shows the memory free.
• Claim memory is reserved when it is only estimated to be free.
• Take a card from another user's machine without their consent (on one machine, only the priorities you set decide).
• Require a cloud account, telemetry upload, or any other software to work.

Contributing

Issues and pull requests are welcome. AGENTS.md has the one command that proves a change (build, format, vet, tests, lint, as CI runs them) and the invariants a change must keep.

License

Apache License 2.0. The Berth name, the Pilot mascot and the artwork in assets/ are not covered by the license; see NOTICE. Third-party components: THIRD_PARTY_NOTICES.