Capability Matrix

Capability Matrix

“Yes” means the current architecture and source contain a usable path. “Limited” calls out an important constraint. Exact availability can depend on the build feature and the connected server.

Capability	Browser-only	Native CPU	Apple MLX	NVIDIA CUDA
Core language and arrays	Yes	Yes	Yes	Yes
Infix comparisons (<, >, <=, >=, ==, !=)	Yes	Yes	Yes	Yes
Direct vector indexing (at) + length-one array broadcasting	Yes	Yes	Yes	Yes
Namespace-qualified first-class references + partial application	Yes	Yes	Yes	Yes
Named axes and structured shape errors	Yes	Yes	Yes	Yes
Model DSL	Yes	Yes	Yes	Yes
CPU autograd and optimizers	Yes	Yes	Fallback	Fallback
General arbitrary-model GPU training	No	N/A	Yes	No
Supported LoRA GPU training fast path	No	N/A	Yes	Yes
Supported two-linear MLP GPU training path	No	N/A	Yes	Yes
Tiny/tutorial training	Yes, size-limited	Yes	Mixed by model path	Mixed by model path
Inline visualization	Yes	No, artifact path	Via client/artifact	Via client/artifact
Filesystem load	No	Yes, sandboxed	Yes, native host	Yes, native host
Static include (script mode)	No, precise error	Yes, sandboxed under --source-dir	Yes, native host	Yes, native host
@word annotations + @test registry + reflection (tests, test_info, annotations)	Yes	Yes	Yes	Yes
bracket(setup, use, teardown) guaranteed-finally	Yes	Yes	Yes	Yes
transpose_axes dyadic transpose + blocked rank-3/4 disp	Yes	Yes	Yes	Yes
Typed test events (test_event_sink/emit_test_event) + host transport	Yes, response array	Yes, --test-events JSONL	Yes	Yes
expunge / :erase name removal	Yes	Yes	Yes	Yes
Header staleness badge (current / update-reload / unknown-offline)	Yes	n/a	n/a	n/a
global_set explicit workspace writes	Yes	Yes	Yes	Yes
Sandboxed fs API (fs_walk/read_text/write_text/remove_path)	No, err value	Yes, --source-dir sandbox	Yes	Yes
run_script fresh-env execution + exit interception	No, err value	Yes	Yes	Yes
Higher-order quartet (each/table/atop/over)	Yes	Yes	Yes	Yes
parse_json + multi-line argument lists	Yes	Yes	Yes	Yes
clock_ms monotonic benchmark clock	No, not a browser builtin	Yes	Yes	Yes
Structural SVG dataflow renderer	Yes, inline	Yes, artifact	Yes, artifact/client	Yes, artifact/client
Fixed-width bit ops (band/bor/bxor/bnot/popcount/shl/shr/bmask/bits/from_bits)	Yes	Yes	Yes	Yes
KV-cache generation (gen_state/gen_logits/gen_append/gen_clone/gen_reset/gen_stats)	Yes	Yes	Yes	Yes
Exception-free record access (has_field / record_get)	Yes	Yes	Yes	Yes
JSON codec (parse_json / to_json, deterministic round trip)	Yes	Yes	Yes	Yes
Root value-kind detection (type_of)	Yes	Yes	Yes	Yes
Raw-byte file I/O (read_bytes / write_bytes, sandboxed)	Yes	No (no sandbox)	Yes	Yes
Crash-safe write (write_atomic, temp + rename)	Yes	No (no sandbox)	Yes	Yes
TOML codec (parse_toml / to_toml, config subset, round trip)	Yes	Yes	Yes	Yes
Decode limits (parse_json / parse_toml max_depth + max_bytes)	Yes	Yes	Yes	Yes
Result round trip (to_json/to_toml + parse {results:1})	Yes	Yes	Yes	Yes
Bounded file I/O (read_bytes offset/length, file_size)	Yes	No (no sandbox)	Yes	Yes
File metadata (file_metadata: kind/size/modified_unix_ms, exact UTC Unix-ms mtime, sandboxed)	Yes	No (no sandbox)	Yes	Yes
Incremental byte sink (append_bytes, bounded output)	Yes	No (no sandbox)	Yes	Yes
Bounded incremental stdin (read_stdin_chunk)	No	Yes	Yes	Yes
Non-seekable byte sink (write_stdout, pipes/stdout)	Yes	No (no stdout)	Yes (server stdout)	n/a
Native extension registry (static provider, namespaced invoke/help)	No	Yes	Yes	Yes
Native extension C-ABI adapter (scalars/arrays/records/handles)	No	Yes	Yes	Yes
Dynamic extension loading (load_extension, MLPL_EXTENSION_PATH, cdylib dlopen)	No	Yes	Yes	Yes
Ports, bounded event delivery, and host-driven applet loop	No	Yes	Yes	Yes
Typed-native binary codec (to_native / parse_native, lossless round trip; MLPB v2 CRC32 integrity, reads v1)	Yes	Yes	Yes	Yes
Decode element cap (parse_json / parse_toml max_elements)	Yes	Yes	Yes	Yes
Record key enumeration (record_keys) + JSON duplicate-key rejection	Yes	Yes	Yes	Yes
Tagged $mlpl envelope: lossless rank>=2 / Result JSON round trip	Yes	Yes	Yes	Yes
Provenance badge v2 (running vs served vs repo; deploy-pending state)	Yes	n/a	n/a	n/a
Partial application + applicative call (the combinator birds)	Yes	Yes	Yes	Yes
Fixed-point combinator via partials (Y / recursion without a name)	Yes	Yes	Yes	Yes
load_preloaded	Yes	Yes	Yes	Yes
Trace export to disk	No	Yes	Yes	Yes
BPE and byte tokenization	Yes	Yes	Yes	Yes
Experiment tracking	Memory	Disk	Disk	Disk
Device feasibility estimation	Yes	Yes	Yes	Yes
Trustworthy calibration	Limited	Yes	Yes	Yes
Direct llm_call or local Ollama	No	Yes	Yes	Yes
Server sessions and inspection	Client only	Server build	Server build	Server build
SSE training telemetry and cancel	Connected client	Yes	Yes	Yes
Session persistence and reattach	Connected client	Yes	Yes	Yes
Compilation to Rust/native	Build elsewhere	Yes, subset	CPU target subset	CPU target subset
Engram conditional memory	Yes, CPU	Yes, CPU	CPU execution	CPU execution

Reading GPU claims correctly

flowchart TD
    Scope[Enter device scope] --> Backend{Backend built and available?}
    Backend -->|No| CPUFallback[Run CPU fallback and warn]
    Backend -->|Yes| Operation{Operation or model shape supported?}
    Operation -->|General forward op| GPUOp[Dispatch GPU operation]
    Operation -->|Recognized training fast path| GPUTrain[Train on GPU]
    Operation -->|Unsupported training graph| Tape[Use CPU autograd tape]
    Tape --> Notice[Do not interpret scope alone as GPU training]

Loading

MLX uses persistent device tensors and a device-aware autograd tape for general training. CUDA accelerates recognized LoRA and two-linear MLP training shapes; other CUDA-scoped training uses the CPU tape. Confirm device telemetry rather than inferring residency from the device scope alone.

See Execution Surfaces for deployment choices and the individual backend pages for build and limitation details.