# Release status without roadmap blur

A current v0.6.2 and historical v0.5.3 release hub that separates shipped capabilities, limitations, and planned work.

## Direct answer

The current audited release is v0.6.2 from 2026-07-11; v0.5.3 remains available as a historical record. GitHub Releases, immutable tagged changelogs, and the tagged model-support guide are authoritative. This hub renders both records and preserves visible capability labels so later features and future roadmap work are never attributed to the historical release.

- Canonical: https://macmlx.app/releases/
- Last verified: 2026-07-15

## Page facts

- **Apple Silicon macOS installation** — Released; since 0.1.0; last verified 2026-07-15. macMLX supports Apple Silicon Macs running macOS 14 or later. Use the current project installation and Gatekeeper guidance; do not disable system-wide security protections solely to open the app.
- **Swift in-process inference** — Released; since 0.1.0; last verified 2026-07-15. The default engine loads and runs MLX models inside the Swift process. Model loading, generation, caching, and serving use Apple MLX through MacMLXCore; the default inference path does not require a Python runtime.
- **Apple Silicon unified memory** — Released; since 0.1.0; last verified 2026-07-15. MLX arrays use the Mac's shared CPU/GPU memory system. Unified memory reduces explicit transfers between CPU orchestration and integrated-GPU compute, but model weights, activations, and KV cache still consume finite physical memory.
- **Shared code, process-local engines** — Released; since 0.1.0; last verified 2026-07-15. The app and CLI both import MacMLXCore, which owns inference and the server. The products share implementation and behavior. When the app and CLI run as separate processes, they do not share one in-memory engine instance.
- **No Python on the default path** — Released; since 0.1.0; last verified 2026-07-15. The released default engine is Swift-native and needs no Python runtime. Optional compatibility engines may use subprocesses and other runtimes. This is not a claim that Python is absent everywhere in the project.
- **OpenAI endpoint compatibility** — Released; since 0.5.3; last verified 2026-07-15. Chat, legacy completions, model listing, and embeddings use compatible request and response shapes. Compatibility is endpoint-specific. macMLX model load and unload routes under /x/models are project extensions, not OpenAI-compatible model management.
- **Anthropic Messages compatibility** — Released; since 0.5.3; last verified 2026-07-15. POST /v1/messages, including streaming, is available in v0.5.3. This is Messages API compatibility only, not compatibility with the full Anthropic API.
- **Selected Ollama endpoints** — Released; since 0.3.7; last verified 2026-07-15. macMLX supports /api/version, /api/tags, /api/show, /api/chat, and /api/generate. The compatibility layer has shipped since v0.3.7. It is a selected endpoint set, not a drop-in replacement for every Ollama API.
- **MCP server** — Released; since 0.5.0; last verified 2026-07-15. The CLI can expose local inference to MCP clients. The MCP server shipped in v0.5.0 and is separate from chat-side routing to external tools.
- **MCP client pool** — Released; since 0.5.3; last verified 2026-07-15. v0.5.3 includes managed MCP client connections. The pool manages external MCP processes and connections; integrated chat-side tool routing is a separate capability released in v0.6.0.
- **Integrated chat tool routing** — Released; since 0.6.0; last verified 2026-07-15. v0.6.0 ships multi-turn tool routing for OpenAI, Anthropic, and the GUI MCP loop. Protocol-specific validation keeps tool-call histories explicit; this routing is distinct from the MCP server and client-pool infrastructure.
- **Local embeddings** — Released; since 0.5.3; last verified 2026-07-15. POST /v1/embeddings shipped in v0.5.3. Encoder-family model detection exists, while using an unsuitable chat model can still produce vectors without semantic guarantees.
- **Bi-encoder rerank MVP** — Released; since 0.5.3; last verified 2026-07-15. POST /v1/rerank scores independently embedded texts with cosine similarity. This released MVP is not a cross-encoder reranker.
- **Exact-prefix RAM and SSD cache** — Released; since 0.5.0; last verified 2026-07-15. A hot RAM tier and content-addressed SSD cold tier support promotion and demotion. The released v0.5.0 cache reuses exact full prefixes. It does not provide released block sharing or paged KV allocation.
- **Trie longest-prefix reuse** — Released; since 0.6.0; last verified 2026-07-15. v0.6.0 reuses the longest compatible cached token prefix. Multi-turn prompts can trim to the longest common prefix and incrementally prefill only the new suffix while usage retains full-prompt accounting.
- **Bounded model pool** — Released; since 0.5.0; last verified 2026-07-15. Budgets, LRU eviction, pinning, cold swap, idle TTL, and probes bound multi-model use. The pool shipped in v0.5.0 and was hardened in v0.5.3. It is not a unified adaptive controller.
- **Supported LoRA adapters** — Released; since 0.5.0; last verified 2026-07-15. The native engine can apply supported LoRA adapters. Adapter compatibility depends on the base architecture and weights; universal LoRA compatibility is not claimed.
- **Fourteen detected VLM families** — Released; since 0.5.3; last verified 2026-07-15. The model library detects 14 vision-language model_type families. This is an evidence-backed family count, not a guarantee that every checkpoint or processor variant will load.
- **DeepSeek V3.2 Swift overlay** — Released; since 0.5.3; last verified 2026-07-15. v0.5.3 includes pure-Swift component parity for the DeepSeek V3.2 architecture. A real-checkpoint smoke test remains pending and FP8 dequantization is absent, so this is not an end-to-end or universal MoE claim.
- **Eligibility-gated continuous batching** — Released; since 0.6.0; last verified 2026-07-15. v0.6.0 batches only eligible dense-text requests under real concurrency, with automatic serial fallback. The tagged 4-client benchmark measured 2.5–3.2× aggregate throughput. VLM, speculative decoding, Ollama, Anthropic, and embeddings remain serial.
- **Fixed prefill admission throttle** — Released; since 0.6.0; last verified 2026-07-15. A fixed prefillBatchSize bounds rows admitted per scheduler step. The released throttle is fixed configuration, not the planned adaptive memory controller.
- **Structured output** — Released; since 0.6.0; last verified 2026-07-15. v0.6.0 supports response_format with json_object and an explicit JSON Schema subset. Unsupported schema keywords return 400. VLM with structured output and tools with structured output are unsupported combinations and are explicitly rejected rather than silently degraded.
- **Speculative decoding** — Released; since 0.6.0; last verified 2026-07-15. v0.6.0 ships the classic draft-model path through both the API and GUI. Acceptance telemetry reports draft efficiency. Targets with non-trimmable hybrid or linear-attention caches are detected and fall back to standard decoding.
- **API compatibility pack** — Released; since 0.6.0; last verified 2026-07-15. v0.6.0 adds logit_bias, logprobs and top_logprobs, XTC, per-request LoRA adapters, and tools. An explicit compatibility matrix governs parameter combinations, and unsupported pairs return 400 instead of silently degrading.
- **KV-cache quantization** — Released; since 0.6.0; last verified 2026-07-15. v0.6.0 exposes kv_bits, kv_group_size, and quantized_kv_start for compatible requests. These controls change KV-cache precision, not model-weight precision. Nonpositive kv_bits disables the feature, and the compatibility matrix rejects unsupported model or request combinations.
- **Hugging Face cache discovery** — Released; since 0.6.0; last verified 2026-07-15. v0.6.0 can discover models in configured Hugging Face cache roots without downloading duplicate weights. Discovery confirms a local candidate, not a universal load guarantee; architecture, tokenizer, processor, and checkpoint compatibility still apply.
- **Per-model chat-template overrides** — Released; since 0.6.2; last verified 2026-07-15. v0.6.2 resolves templates in user file, built-in model_type, then checkpoint order. Built-in overrides carry standard-path parity evidence, but template support is not universal; checkpoint-specific branches and unsupported swift-jinja syntax can still define the boundary.
- **Track G tested models** — Released; since 0.6.2; last verified 2026-07-15. v0.6.2 adds four checkpoint-tested native model families. Measured real-checkpoint generation: Seed-OSS-36B 4-bit at 18.2 tok/s; Hunyuan V1 Dense 1.8B 4-bit at 80.3 tok/s; Cohere Command R7B 7B 4-bit at 21.7 tok/s; and MiniCPM3-4B 4-bit at 18.7 tok/s. Results are checkpoint-specific, not family-wide performance guarantees.
- **InternLM3 theoretical support** — Theoretical; since 0.6.2; last verified 2026-07-15. v0.6.2 ships parity-verified InternLM3 code at the theoretical support tier. Real generation has not been demonstrated. Public checkpoints ship tokenizer.model but no tokenizer.json, while the Swift tokenizer stack requires tokenizer.json; support remains theoretical until that load-path boundary changes.
- **Temperature and top-p** — Released; since 0.1.0; last verified 2026-07-15. Temperature and nucleus top-p sampling are released controls. These are the current exposed core sampling controls.
- **Paged KV, block sharing, and CoW** — Planned; since future; last verified 2026-07-15. Paged allocation, shared blocks, and copy-on-write branching are planned. None of these cache-virtualization features is released in v0.6.2.
- **Unified adaptive memory guard** — Planned; since future; last verified 2026-07-15. A feedback controller across cache, model pool, and concurrency is planned. Released memory probes and pool caps are separate mechanisms and must not be described as this guard.
- **Expanded sampling controls** — Planned; since future; last verified 2026-07-15. top-k, min-p, presence, frequency, and repetition penalties, plus per-request seed are planned. DeepSeek expert-routing top-k is an internal architecture operation and is unrelated to user sampling top-k.

## Sources

- https://github.com/magicnight/mac-mlx/releases/tag/v0.6.2
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/README.md
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Engine/MLXSwiftEngine.swift
- https://ml-explore.github.io/mlx/build/html/usage/unified_memory.html
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Server/HummingbirdServer.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/CHANGELOG.md
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/MCP/MCPClientPool.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/MCP/ToolCallingSession.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Engine/EmbeddingEngine.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Engine/RerankScoring.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/PromptCache/PromptCacheStore.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/PromptCache/PromptTrie.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/ModelPool/ModelPool.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Managers/ModelLibraryManager.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Models/DeepseekV32.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Batching/BatchScheduler.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Engine/MLXSwiftEngine+BatchGenerationServing.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Constraint/ResponseFormatDecoder.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Engine/SpeculativeDecodingUsage.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Engine/GenerateRequest.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Engine/ChatTemplateOverride.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/docs/model-support.md
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Models/InternLM3.swift
- https://github.com/magicnight/mac-mlx/blob/v0.6.2/MacMLXCore/Sources/MacMLXCore/Managers/ModelParametersStore.swift
- https://github.com/magicnight/mac-mlx/blob/main/docs/superpowers/specs/2026-07-10-engine-scroll-story-design.md
- https://github.com/magicnight/mac-mlx/blob/main/MacMLXCore/Sources/MacMLXCore/Managers/ModelParametersStore.swift
- https://github.com/magicnight/mac-mlx/releases/tag/v0.5.3
- https://github.com/magicnight/mac-mlx/blob/v0.5.3/CHANGELOG.md

## Related pages

- [macMLX v0.6.2](https://macmlx.app/releases/v0-6-2/)
- [macMLX v0.5.3 (historical)](https://macmlx.app/releases/v0-5-3/)
- [How macMLX runs models on Apple Silicon](https://macmlx.app/architecture/)
- [Local API compatibility, endpoint by endpoint](https://macmlx.app/api-compatibility/)