CLI guide¶
Run rondine COMMAND --help for the option list installed with your version.
This guide explains the choices that affect model recommendations.
Rondine enables colors automatically for interactive terminals. If terminal detection is incorrect, force the mode before the command:
rondine --color doctor
rondine --color suggest
# Persist for the current shell:
export RONDINE_COLOR=1
Use --no-color or RONDINE_COLOR=0 for plain output.
Global options precede the subcommand: rondine --no-color suggest, not
rondine suggest --no-color.
Interactive session¶
Run Rondine without a command to start the full guided interface:
On first use, the session runs hardware doctor, asks for workload, required context and model sources, then opens the recommendation selector. On later runs, Rondine detects the active plan and saved presets first. It offers to continue the active configuration, load a preset, open the main menu directly, or start a new guided setup—so hardware detection and recommendation are not repeated unnecessarily.
The first-run wizard asks for workload (coding or chat), required context,
and model sources (catalog plus Hub, or offline catalog only) before showing the
arrow-key recommendation selector.
The main menu groups related actions into five focused areas:
- Run selected model: preview, download, start, verify or stop
- Choose or change model: recommendations, catalog, Hub search or direct plan
- Environment: inference-engine setup and hardware doctor
- Presets: load, save or list
- Current configuration: concise active model and runtime summary
Potentially expensive or state-changing actions such as installing engines, downloading weights and starting a server require confirmation. Browsing the catalog or searching the Hub does not replace the active plan; choose a recommendation or use direct planning to do that. Command failures are shown as warnings and return to the menu instead of ending the session.
rondine --help continues to show the command list. Explicit commands such as
rondine doctor, rondine suggest and rondine serve behave as before. When
standard input is not interactive, bare rondine prints help instead of
waiting for input.
Suggest¶
rondine suggest detects the current machine, ranks curated configurations, and
supplements them with current Hugging Face search results that fit its available
memory. Hub failures are non-fatal: the command falls back to the catalog.
Each result includes its rank, estimated memory use and headroom, context size,
engine arguments, sampling settings, and an equivalent serve command.
Interactive terminals display each configuration as a separated card.
Cards use three source markers:
TOP: model recommended for the matched hardware targetHUB: live Hugging Face discovery resultCAT: another curated catalog result
On discrete CUDA systems, resident fit and the summary use VRAM rather than system RAM. Missing engines are reported separately from model fit.
Profiles¶
--profile coding is the default. It favors models with a higher coding
priority, uses a 32,768-token context by default, enables model-appropriate
reasoning where supported, and tunes engines for one interactive coding client.
--profile chat uses a 16,384-token context, disables explicit reasoning for
supported model families, and tunes llama.cpp for more concurrent chat slots.
Profiles affect ranking, context, sampling, reasoning flags, and engine
configuration. They do not change model weights. Model-family settings can
override the general profile defaults; suggest prints the resolved values.
Use --context TOKENS when the application requires a specific context window.
Rondine recalculates KV-cache memory at that size and excludes catalog models
whose declared maximum context is lower.
Options¶
--profile coding|chat
Select the workload profile described above. Default: coding.
--limit INTEGER
Set the maximum number of ranked configurations to display. Default: 5.
In interactive selection, choose Show more recommendations to increase the
same search by five results at a time, up to 50 or until results are exhausted.
--opt-in / --no-opt-in
Include or exclude models marked opt-in. These are usually unusually large,
specialized, or impractical on common hardware. They must still pass the
planner's memory checks. Default: --no-opt-in.
--hub / --no-hub
Search Hugging Face and inspect the leading results before merging fitting
repositories into the recommendations. This is enabled by default. Use
--no-hub for an offline, deterministic catalog-only result.
Rondine reserves one displayed slot for a fitting Hub result when the total limit is below six, and two slots for larger result sets. API errors are non-fatal and leave the catalog ranking intact.
--hub-query TEXT
Override the Hub search text. The default is coder for the coding profile and
instruct for the chat profile. Rondine still filters toward the preferred
engine and rejects repositories that do not fit the detected hardware.
--context TOKENS
Require at least this context window. The value must be at least 1,024 tokens and directly affects KV-cache estimates and ranking. Catalog models below the required capability are excluded. Hub results are also excluded when their inferred catalog family has a lower known limit; unknown Hub families are marked as not independently verified.
--json
Write the complete result as JSON instead of human-readable output. This is intended for scripts and includes detected hardware, selected hardware target, engine order, suggestions, estimates, arguments, and notes.
-i / --interactive
After a normal suggest, Rondine offers interactive selection when attached to
a terminal. Use -i to open the menu without the confirmation or
--no-interactive to suppress the offer. In the menu, use ↑/↓ (or j/k)
to move, Enter to select and configure a model, or q to cancel. When input is
not attached to a terminal, explicit -i falls back to a numbered prompt.
Interactive mode cannot be combined with --json or --configure.
--no-interactive
Suppress the post-results selection offer in an interactive terminal.
--configure INTEGER
Save the suggestion with that rank as the active plan. The rank is the #N
shown in the output and must be present in the current result list.
--save-as NAME
With --configure or interactive selection, also save the selected plan as a
reusable preset. The name is user-defined; coding is only an example.
--help
Print the command's current usage and option summary.
Typical workflows¶
Inspect recommendations without changing configuration:
Select the top recommendation and save it for later:
rondine suggest --profile coding --configure 1 --save-as coding
rondine setup
rondine pull
rondine serve --preset coding
Compare coding and chat recommendations:
rondine suggest --profile coding --json > coding.json
rondine suggest --profile chat --json > chat.json
The detected hardware and installed engines can change the ranking, so rank
#1 is not guaranteed to identify the same model on another machine.
suggest exits with status 1 when no fitting result is available.
Command reference¶
Use rondine COMMAND --help for every option.
doctor— inspect RAM/VRAM, disk, platform, engines, and matched target.models— list curated variants and whether each fits this machine.search QUERY— search Hugging Face; optionally filter with--engine.inspect ORG/REPO— inspect repository files, sizes, formats, and quants.plan MODEL— create the active plan fromauto, a catalog ID, or Hub repo.setup— install recommended engines; supports--engineand--dry-run.pull [MODEL]— download the active or supplied model.serve [MODEL]— launch the active, supplied, or--presetconfiguration.stop— stop a managed server by--name.verify— check a managed--nameor explicit--base-url.preset—list,show,save,delete, orservenamed configurations.cluster—init,doctor,plan, and dry-runserve; see cluster setup.
When serve loads an existing active plan or preset, its saved profile and
settings win; use plan or the dashboard to change them first. A managed run
name is separate from a preset name, although --save-as NAME uses the same
name for both in the common workflow.
Plan, pull, and serve memory modes¶
plan, pull, and serve share two related options:
--memory-mode auto|resident|hybrid|mmap
auto(default): prefer a resident fit; on discrete CUDA GGUFs, fall back to a supported hybrid RAM+VRAM plan when VRAM alone is insufficient.resident: require the estimate to fit the primary budget (VRAM or unified RAM).hybrid: require llama.cpp GGUF on a discrete CUDA host and estimate against combined RAM + VRAM. Emits--cpu-moefor MoE models plus auto-fit GPU layers.mmap: experimental SSD demand paging. Never chosen byauto.
--allow-oversize
Required acknowledgment for --memory-mode mmap. Experimental plans stay marked
fits=false and experimental=true; presets show an [EXPERIMENTAL] marker and
serve reprints the warning at launch.
# Supported hybrid MoE offload on a GPU workstation
rondine plan glm-5.2 --memory-mode hybrid --context 4096 --save-as glm-hybrid
# Explicit experimental SSD paging (not selected automatically)
rondine plan glm-5.2 --quant UD-IQ1_S --context 4096 \
--memory-mode mmap --allow-oversize --save-as glm-ssd
rondine pull glm-5.2 --memory-mode mmap --allow-oversize
rondine serve --preset glm-ssd
pull refuses a download when free disk is below the estimated shard total.
mmap is OS page-cache demand paging, not the unmerged llama.cpp --moe-stream*
expert streamer. See engine tuning for capacity notes and
Apple Silicon Metal/mmap hazards.