{"id":159,"date":"2026-06-28T07:01:19","date_gmt":"2026-06-27T23:01:19","guid":{"rendered":"http:\/\/www.tantan.ink\/index.php\/2026\/06\/28\/mac%e6%9c%ac%e5%9c%b0ai%e6%8e%a8%e7%90%86%ef%bc%9agguf-vs-mlx%ef%bc%8c%e6%80%8e%e4%b9%88%e9%80%89%ef%bc%9f\/"},"modified":"2026-06-28T07:01:19","modified_gmt":"2026-06-27T23:01:19","slug":"mac%e6%9c%ac%e5%9c%b0ai%e6%8e%a8%e7%90%86%ef%bc%9agguf-vs-mlx%ef%bc%8c%e6%80%8e%e4%b9%88%e9%80%89%ef%bc%9f","status":"publish","type":"post","link":"https:\/\/www.tantan.ink\/index.php\/2026\/06\/28\/mac%e6%9c%ac%e5%9c%b0ai%e6%8e%a8%e7%90%86%ef%bc%9agguf-vs-mlx%ef%bc%8c%e6%80%8e%e4%b9%88%e9%80%89%ef%bc%9f\/","title":{"rendered":"Mac\u672c\u5730AI\u63a8\u7406\uff1aGGUF vs MLX\uff0c\u600e\u4e48\u9009\uff1f"},"content":{"rendered":"<p><em>2026\u5e746\u670828\u65e5 \u00b7 \u6280\u672f\u6298\u817e \u00b7 \u7ea6\u4e3a 15 \u5206\u949f<\/em><\/p>\n<hr>\n<p>\u5982\u679c\u4f60\u7528\u7684\u662f Apple Silicon Mac\uff08M1\/M2\/M3\/M4\uff09\uff0c\u60f3\u672c\u5730\u8dd1\u5927\u6a21\u578b\uff0c\u73b0\u5728\u57fa\u672c\u4e0a\u6709\u4e24\u6761\u8def\uff1a<\/p>\n<ol>\n<li><strong>GGUF \u8def\u7ebf<\/strong>\uff1aOllama\u3001LM Studio\u3001llama.cpp \u90fd\u7528\u8fd9\u4e2a\u683c\u5f0f\uff0c\u8de8\u5e73\u53f0\uff0c\u751f\u6001\u6700\u6210\u719f<\/li>\n<li><strong>MLX \u8def\u7ebf<\/strong>\uff1aApple \u5b98\u65b9\u51fa\u7684\u6846\u67b6\uff0c\u4e13\u95e8\u4e3a Apple Silicon \u4f18\u5316\uff0c\u53ea\u80fd\u8dd1\u5728 Mac \u4e0a<\/li>\n<\/ol>\n<p>\u8fd9\u4e24\u6761\u8def\u5230\u5e95\u5dee\u5728\u54ea\uff1f\u503c\u4e0d\u503c\u5f97\u4ece Ollama \u5207\u6362\u5230 MLX\uff1f\u6211\u7ffb\u4e86\u4e00\u5708\u5b9e\u6d4b\u6570\u636e\u548c\u793e\u533a\u53cd\u9988\uff0c\u7ed9\u4f60\u4e00\u4e2a\u9760\u8c31\u7684\u7ed3\u8bba\u3002<\/p>\n<h2>\u5148\u641e\u61c2\uff1aGGUF \u548c MLX \u5230\u5e95\u662f\u4ec0\u4e48\uff1f<\/h2>\n<h3>GGUF\uff1a\u8de8\u5e73\u53f0\u7684\u901a\u884c\u8bc1<\/h3>\n<p>GGUF \u662f llama.cpp \u9879\u76ee\u641e\u51fa\u6765\u7684\u6a21\u578b\u683c\u5f0f\uff0c\u8bbe\u8ba1\u76ee\u6807\u5c31\u4e00\u4e2a\uff1a<strong>\u8ba9\u5927\u6a21\u578b\u80fd\u5728\u5404\u79cd\u8bbe\u5907\u4e0a\u8dd1\u8d77\u6765<\/strong>\u3002<\/p>\n<ul>\n<li>CPU\uff1f\u53ef\u4ee5\u3002<\/li>\n<li>NVIDIA GPU\uff1f\u53ef\u4ee5\u3002<\/li>\n<li>AMD GPU\uff1f\u53ef\u4ee5\u3002<\/li>\n<li>Apple Silicon\uff1f\u53ef\u4ee5\u3002<\/li>\n<\/ul>\n<p>\u4e3a\u4e86\u5b9e\u73b0\u8fd9\u4e2a\u517c\u5bb9\u6027\uff0cGGUF \u9700\u8981\u901a\u8fc7 Metal API \u8c03\u7528 Apple Silicon \u7684 GPU\uff0c\u8fd9\u5c42\u62bd\u8c61\u4f1a\u6709\u4e00\u70b9\u6027\u80fd\u635f\u8017\uff0c\u4f46\u6362\u6765\u7684\u662f<strong>\u751f\u6001<\/strong>\u2014\u2014\u51e0\u4e4e\u6240\u6709\u672c\u5730 AI \u5de5\u5177\u90fd\u652f\u6301 GGUF\u3002<\/p>\n<p>Ollama \u5e95\u5c42\u5c31\u662f llama.cpp\uff0c\u4f60\u7528 <code>ollama run qwen3.5<\/code> \u7684\u65f6\u5019\uff0c\u5b9e\u9645\u8dd1\u7684\u662f GGUF \u683c\u5f0f\u7684\u6a21\u578b\u3002<\/p>\n<h3>MLX\uff1aApple \u7684\u4eb2\u513f\u5b50<\/h3>\n<p>MLX \u662f Apple \u673a\u5668\u5b66\u4e60\u7814\u7a76\u56e2\u961f\u5f00\u6e90\u7684\u6846\u67b6\uff0c<strong>\u4e13\u95e8\u4e3a Apple Silicon \u8bbe\u8ba1<\/strong>\u3002\u5b83\u7684\u6838\u5fc3\u4f18\u52bf\u662f\uff1a<\/p>\n<ol>\n<li><strong>\u7edf\u4e00\u5185\u5b58<\/strong>\uff1aCPU \u548c GPU \u5171\u4eab\u540c\u4e00\u5757\u7269\u7406\u5185\u5b58\uff0c\u4e0d\u7528\u62f7\u8d1d\u6570\u636e<\/li>\n<li><strong>\u76f4\u63a5\u8c03\u7528\u786c\u4ef6<\/strong>\uff1a\u4e0d\u9700\u8981\u901a\u8fc7 Metal API \u8fd9\u5c42\u62bd\u8c61<\/li>\n<li><strong>\u652f\u6301 Neural Engine<\/strong>\uff1a\u53ef\u4ee5\u8c03\u7528 Apple \u7684\u795e\u7ecf\u7f51\u7edc\u5f15\u64ce<\/li>\n<\/ol>\n<p>\u7b80\u5355\u7c7b\u6bd4\uff1a<\/p>\n<ul>\n<li>GGUF \u50cf\u662f\u56fd\u9645\u901a\u7528\u63d2\u5934\u8f6c\u6362\u5668\uff0c\u54ea\u91cc\u90fd\u80fd\u63d2\uff0c\u4f46\u591a\u4e86\u4e00\u5c42<\/li>\n<li>MLX \u662f\u76f4\u63a5\u63d2\u672c\u5730\u63d2\u5ea7\uff0c\u6ca1\u6709\u8f6c\u6362\u635f\u8017<\/li>\n<\/ul>\n<h2>\u5b9e\u6d4b\uff1aMLX \u5230\u5e95\u5feb\u591a\u5c11\uff1f<\/h2>\n<p>\u6211\u627e\u5230\u4e86\u4e00\u4e2a\u6bd4\u8f83\u9760\u8c31\u7684\u5b9e\u6d4b\uff1a<a href=\"https:\/\/meirong.dev\/posts\/mlx-vs-ollama-benchmark-on-m2-mbp\/\">meirong.dev \u7684\u57fa\u51c6\u6d4b\u8bd5<\/a>\uff0c\u5728 M2 MacBook Pro 32GB \u4e0a\u5bf9\u6bd4\u4e86 Ollama\uff08GGUF\uff09\u548c MLX\u3002<\/p>\n<h3>\u6d4b\u8bd5\u73af\u5883<\/h3>\n<ul>\n<li><strong>\u786c\u4ef6<\/strong>\uff1aM2 MacBook Pro\uff0c32GB \u7edf\u4e00\u5185\u5b58<\/li>\n<li><strong>\u6a21\u578b<\/strong>\uff1aQwen3.5 9B\uff0c4-bit \u91cf\u5316<\/li>\n<li><strong>\u6d4b\u8bd5 Prompt<\/strong>\uff1a\u56fa\u5b9a\u540c\u4e00\u6bb5\u4e2d\u6587\u63d0\u95ee\uff0c\u9650\u5236\u8f93\u51fa 128 tokens<\/li>\n<\/ul>\n<h3>\u7ed3\u679c<\/h3>\n<table>\n<tr>\n<th>\u5f15\u64ce<\/th>\n<th>\u751f\u6210\u901f\u5ea6 (tokens\/s)<\/th>\n<th>\u76f8\u5bf9\u901f\u5ea6<\/th>\n<\/tr>\n<tr>\n<td>Ollama (GGUF)<\/td>\n<td>18.58<\/td>\n<td>1.00x<\/td>\n<\/tr>\n<tr>\n<td><strong>MLX<\/strong><\/td>\n<td><strong>28.35<\/strong><\/td>\n<td><strong>1.53x<\/strong><\/td>\n<\/tr>\n<\/table>\n<p><strong>MLX \u6bd4 Ollama \u5feb\u7ea6 50%<\/strong>\u3002<\/p>\n<p>\u8fd9\u4e2a\u5dee\u8ddd\u5728\u66f4\u957f\u7684\u751f\u6210\u4efb\u52a1\uff08\u5199\u4f5c\u3001\u4ee3\u7801\u751f\u6210\uff09\u91cc\u4f1a\u66f4\u660e\u663e\uff0c\u56e0\u4e3a MLX \u5bf9\u5185\u5b58\u5e26\u5bbd\u7684\u5229\u7528\u66f4\u5145\u5206\u3002<\/p>\n<h3>35B \u6a21\u578b\u7684\u60c5\u51b5<\/h3>\n<p>\u7528 LM Studio \u6d4b\u8bd5 Qwen3.5 35B A3B\uff08MoE \u6a21\u578b\uff09\u65f6\uff0cMLX \u7684\u4f18\u52bf\u66f4\u660e\u663e\uff1a<\/p>\n<ul>\n<li>35B \u6a21\u578b\u5bf9\u5185\u5b58\u5e26\u5bbd\u66f4\u654f\u611f<\/li>\n<li>MLX \u7684\u76f8\u5bf9\u63d0\u5347\u5e45\u5ea6\u6bd4 9B \u65f6\u66f4\u5927<\/li>\n<li>32GB \u5185\u5b58\u8dd1 35B 4-bit \u91cf\u5316\u8fd8\u7b97\u53ef\u884c<\/li>\n<\/ul>\n<h2>MLX \u7684\u5751\uff1a\u4e0d\u662f\u4e07\u80fd\u836f<\/h2>\n<p>MLX \u5feb\u662f\u5feb\uff0c\u4f46\u4e5f\u6709\u51e0\u4e2a\u5df2\u77e5\u7684\u5751\uff1a<\/p>\n<h3>1. \u7279\u5b9a\u573a\u666f\u4e0b\u901f\u5ea6\u672a\u5fc5\u66f4\u5feb<\/h3>\n<p>Reddit \u4e0a\u6709\u7528\u6237\u5728 M1 Max \u4e0a\u6d4b\u8bd5\u4e86\u591a\u4e2a\u771f\u5b9e\u4efb\u52a1\u573a\u666f\uff0c\u53d1\u73b0 MLX \u7684&#8221;\u6709\u6548 tokens\/s&#8221;\u5728\u67d0\u4e9b\u573a\u666f\u4e0b\u5e76\u4e0d\u9886\u5148\uff08<a href=\"https:\/\/www.reddit.com\/r\/LocalLLaMA\/comments\/1rs059a\/mlx_is_not_faster_i_benchmarked_mlx_vs_llamacpp\/\">\u539f\u5e16<\/a>\uff09\u3002<\/p>\n<p>\u6d4b\u8bd5\u65b9\u6cd5\u4e0d\u540c\uff0c\u7ed3\u8bba\u53ef\u80fd\u5dee\u5f02\u5f88\u5927\u3002<strong>\u5355\u4e00 benchmark \u4e0d\u80fd\u4ee3\u8868\u5168\u90e8\u573a\u666f<\/strong>\u3002<\/p>\n<h3>2. \u591a\u8f6e\u5bf9\u8bdd\u540e\u7684&#8221;\u964d\u667a&#8221;\u73b0\u8c61<\/h3>\n<p>\u6709\u7528\u6237\u53cd\u6620\u5728 MLX \u4e0b\u8fdb\u884c\u591a\u8f6e\u5bf9\u8bdd\u65f6\uff0c\u6a21\u578b\u8f93\u51fa\u8d28\u91cf\u4f1a\u51fa\u73b0\u4e0b\u964d\uff08<a href=\"https:\/\/x.com\/LotusDecoder\/status\/2031526735213453633\">\u76f8\u5173\u8ba8\u8bba<\/a>\uff09\u3002<\/p>\n<p>\u8fd9\u53ef\u80fd\u4e0e MLX \u7684 KV cache \u5b9e\u73b0\u6709\u5173\uff0c\u76ee\u524d\u8fd8\u4e0d\u7a33\u5b9a\u3002\u5982\u679c\u4f60\u8981\u505a\u957f\u4e0a\u4e0b\u6587\u591a\u8f6e\u5bf9\u8bdd\uff0cMLX \u53ef\u80fd\u8fd8\u4e0d\u662f\u6700\u4f73\u9009\u62e9\u3002<\/p>\n<h3>3. \u751f\u6001\u4e0d\u5982 GGUF<\/h3>\n<ul>\n<li>GGUF \u6a21\u578b\u5e93\u66f4\u4e30\u5bcc\uff08Hugging Face \u4e0a\u968f\u4fbf\u4e0b\uff09<\/li>\n<li>MLX \u683c\u5f0f\u6a21\u578b\u9700\u8981\u4e13\u95e8\u8f6c\u6362\uff0c\u793e\u533a\u7248\u672c\u5c11\u4e00\u4e9b<\/li>\n<li>\u5de5\u5177\u94fe\u4e0d\u5982 GGUF \u6210\u719f\uff08Ollama\u3001LM Studio \u90fd\u4f18\u5148\u652f\u6301 GGUF\uff09<\/li>\n<\/ul>\n<h2>\u600e\u4e48\u9009\uff1f\u6211\u7684\u5efa\u8bae<\/h2>\n<p>\u6839\u636e\u4ee5\u4e0a\u4fe1\u606f\u548c\u793e\u533a\u53cd\u9988\uff0c\u6211\u76ee\u524d\u7684\u4f7f\u7528\u7b56\u7565\u662f\uff1a<\/p>\n<h3>\u7528 MLX \u7684\u573a\u666f<\/h3>\n<ul>\n<li><strong>\u8f7b\u91cf\u4efb\u52a1<\/strong>\uff1a\u7ffb\u8bd1\u3001\u6458\u8981\u3001\u7b80\u5355\u95ee\u7b54<\/li>\n<li><strong>\u8ffd\u6c42\u901f\u5ea6<\/strong>\uff1a\u60f3\u69a8\u5e72 Apple Silicon \u7684\u6027\u80fd<\/li>\n<li><strong>\u6280\u672f\u7814\u7a76<\/strong>\uff1a\u60f3\u5c1d\u8bd5 Apple \u5b98\u65b9\u6846\u67b6<\/li>\n<\/ul>\n<p>MLX \u7684\u5b89\u88c5\u5f88\u7b80\u5355\uff1a<\/p>\n<pre><code>pip install mlx-lm\nmlx_lm.generate --model mlx-community\/Qwen3.5-9B-MLX-4bit --prompt \"\u4f60\u597d\"\n<\/code><\/pre>\n<h3>\u7528 GGUF\uff08Ollama\uff09\u7684\u573a\u666f<\/h3>\n<ul>\n<li><strong>\u590d\u6742\u63a8\u7406\u3001\u957f\u4e0a\u4e0b\u6587\u591a\u8f6e\u5bf9\u8bdd<\/strong>\uff1a\u7a33\u5b9a\u6027\u66f4\u597d<\/li>\n<li><strong>\u9700\u8981 OpenAI \u517c\u5bb9\u63a5\u53e3<\/strong>\uff1aOllama \u5f00\u4e2a\u670d\u52a1\u5c31\u80fd\u63a5\u5165\u5176\u4ed6\u5de5\u5177<\/li>\n<li><strong>\u751f\u6001\u9700\u6c42<\/strong>\uff1a\u8981\u7528 LM Studio\u3001Continue.dev \u7b49\u5de5\u5177<\/li>\n<li><strong>\u65b0\u624b\u5165\u95e8<\/strong>\uff1aOllama \u7684\u5b89\u88c5\u548c\u7ba1\u7406\u4f53\u9a8c\u66f4\u7701\u5fc3<\/li>\n<\/ul>\n<p>Ollama \u7684\u4f7f\u7528\u66f4\u7b80\u5355\uff1a<\/p>\n<pre><code>ollama pull qwen3.5\nollama run qwen3.5 \"\u4f60\u597d\"\n<\/code><\/pre>\n<h3>\u6211\u7684\u5b9e\u9645\u7528\u6cd5<\/h3>\n<p>\u8c08\u8c08\u8fd9\u8fb9\u662f <strong>Mac mini M4 16GB<\/strong>\uff0c\u672c\u5730\u8dd1\u7684\u662f <strong>QWen36 (Qwen3.6-35B-A3B)<\/strong>\uff0c\u7528\u7684\u662f GGUF \u683c\u5f0f\uff08\u901a\u8fc7 llama-server \u63d0\u4f9b\u670d\u52a1\uff09\u3002<\/p>\n<p>\u539f\u56e0\uff1a<\/p>\n<ol>\n<li>35B \u6a21\u578b\u5bf9\u5185\u5b58\u538b\u529b\u6bd4\u8f83\u5927\uff0cGGUF \u7684\u751f\u6001\u66f4\u6210\u719f<\/li>\n<li>\u9700\u8981\u901a\u8fc7 OpenAI \u517c\u5bb9\u63a5\u53e3\u63a5\u5165\u5176\u4ed6\u5de5\u5177<\/li>\n<li>\u7a33\u5b9a\u6027\u4f18\u5148\uff0c\u4e0d\u60f3\u8e29 MLX \u7684\u5751<\/li>\n<\/ol>\n<p>\u5982\u679c\u4f60\u7684\u662f <strong>M4 Pro\/Max\uff0832GB+\uff09<\/strong>\uff0c\u53ef\u4ee5\u8003\u8651\u628a\u5e38\u7528\u6a21\u578b\uff087B\/9B\/14B\uff09\u5207\u6362\u5230 MLX \u683c\u5f0f\u8bd5\u8bd5\uff0c\u901f\u5ea6\u63d0\u5347\u660e\u663e\u3002<\/p>\n<h2>\u603b\u7ed3<\/h2>\n<table>\n<tr>\n<th>\u7ef4\u5ea6<\/th>\n<th>GGUF (Ollama)<\/th>\n<th>MLX<\/th>\n<\/tr>\n<tr>\n<td><strong>\u901f\u5ea6<\/strong><\/td>\n<td>\u57fa\u51c6<\/td>\n<td>\u5feb 30-50%<\/td>\n<\/tr>\n<tr>\n<td><strong>\u751f\u6001<\/strong><\/td>\n<td>\u4e30\u5bcc<\/td>\n<td>\u4e00\u822c<\/td>\n<\/tr>\n<tr>\n<td><strong>\u7a33\u5b9a\u6027<\/strong><\/td>\n<td>\u6210\u719f<\/td>\n<td>\u6709\u5751<\/td>\n<\/tr>\n<tr>\n<td><strong>\u517c\u5bb9\u6027<\/strong><\/td>\n<td>\u8de8\u5e73\u53f0<\/td>\n<td>\u4ec5 Apple Silicon<\/td>\n<\/tr>\n<tr>\n<td><strong>\u4e0a\u624b\u96be\u5ea6<\/strong><\/td>\n<td>\u7b80\u5355<\/td>\n<td>\u4e2d\u7b49<\/td>\n<\/tr>\n<\/table>\n<ul>\n<li><strong>\u666e\u901a\u7528\u6237<\/strong>\uff1a\u7528 Ollama\uff0c\u7701\u5fc3\uff0c\u793e\u533a\u6a21\u578b\u5e93\u4e30\u5bcc\u3002<\/li>\n<li><strong>\u6298\u817e\u515a<\/strong>\uff1a\u4e24\u4e2a\u90fd\u88c5\uff0c\u8f7b\u91cf\u4efb\u52a1\u7528 MLX\uff0c\u590d\u6742\u4efb\u52a1\u7528 Ollama\u3002<\/li>\n<li><strong>Mac mini M4 16GB \u7528\u6237<\/strong>\uff1a\u4f18\u5148 GGUF\uff0c\u5185\u5b58\u591f\u7528\uff0c\u7a33\u5b9a\u6027\u66f4\u597d\u3002<\/li>\n<\/ul>\n<hr>\n<p><strong>\u53c2\u8003\u8d44\u6599<\/strong><\/p>\n<ol>\n<li><a href=\"https:\/\/meirong.dev\/posts\/mlx-vs-ollama-benchmark-on-m2-mbp\/\">MLX vs Ollama \u57fa\u51c6\u6d4b\u8bd5<\/a><\/li>\n<li><a href=\"https:\/\/ml-explore.github.io\/mlx\/build\/html\/index.html\">MLX \u5b98\u65b9\u6587\u6863<\/a><\/li>\n<li><a href=\"https:\/\/nsclass.github.io\/2026\/06\/20\/gguf-vs-mlx-llm-model-formats\/\">GGUF vs MLX \u683c\u5f0f\u5bf9\u6bd4<\/a><\/li>\n<li><a href=\"https:\/\/macgpu.com\/zh\/blog\/2026-mac-ollama-lmstudio-mlx-sanzhan-juece-fenliu.html\">2026 \u5e74 Mac \u672c\u5730\u63a8\u7406\u4e09\u6808\u600e\u4e48\u9009\uff1f<\/a><\/li>\n<\/ol>\n<p><strong>\u6807\u7b7e<\/strong>\uff1a<code>\u672c\u5730AI<\/code> <code>Apple Silicon<\/code> <code>GGUF<\/code> <code>MLX<\/code> <code>Mac<\/code> <code>Ollama<\/code> <code>\u6a21\u578b\u63a8\u7406<\/code><\/p>\n","protected":false},"excerpt":{"rendered":"<p>2026\u5e746\u670828\u65e5 \u00b7 \u6280\u672f\u6298\u817e \u00b7 \u7ea6\u4e3a 15 \u5206\u949f \u5982\u679c\u4f60\u7528\u7684\u662f Apple Silicon Mac\uff08M &#8230; <a title=\"Mac\u672c\u5730AI\u63a8\u7406\uff1aGGUF vs MLX\uff0c\u600e\u4e48\u9009\uff1f\" class=\"read-more\" href=\"https:\/\/www.tantan.ink\/index.php\/2026\/06\/28\/mac%e6%9c%ac%e5%9c%b0ai%e6%8e%a8%e7%90%86%ef%bc%9agguf-vs-mlx%ef%bc%8c%e6%80%8e%e4%b9%88%e9%80%89%ef%bc%9f\/\" aria-label=\"\u9605\u8bfb Mac\u672c\u5730AI\u63a8\u7406\uff1aGGUF vs MLX\uff0c\u600e\u4e48\u9009\uff1f\">\u9605\u8bfb\u66f4\u591a<\/a><\/p>\n","protected":false},"author":2,"featured_media":160,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-159","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai"],"_links":{"self":[{"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/posts\/159","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/comments?post=159"}],"version-history":[{"count":0,"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/posts\/159\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/media\/160"}],"wp:attachment":[{"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/media?parent=159"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/categories?post=159"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tantan.ink\/index.php\/wp-json\/wp\/v2\/tags?post=159"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}