[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"public-config":3,"i-flag:ph-4x3":14,"i-flag:us-4x3":19,"i-flag:de-4x3":21,"i-flag:hk-4x3":23,"i-tabler:lifebuoy":25,"i-tabler:timeline":28,"i-tabler:apps":30,"i-tabler:package":32,"i-tabler:circle-half-2":34,"i-tabler:sun":36,"i-tabler:moon":38,"i-tabler:menu-2":40,"i-tabler:user":42,"i-tabler:notebook":44,"i-simple-icons:forgejo":46,"i-tabler:shield-lock":48,"i-tabler:tools":50,"i-tabler:calendar":52,"i-tabler:x":54,"$f1yw4i5weusst8":56,"i-tabler:arrow-left":115,"i-tabler:tag":117},{"matomo":4,"booking":7,"site":9,"blog":11,"newsletter":12},{"enabled":5,"siteId":6},true,"7",{"enabled":5,"url":8},"https:\u002F\u002Fcal.com\u002Fjdbungart",{"url":10},"https:\u002F\u002Fjdneer.com",{"enabled":5},{"enabled":13},false,{"left":15,"top":15,"width":16,"height":17,"rotate":15,"vFlip":13,"hFlip":13,"body":18},0,640,480,"\u003Cpath fill=\"#0038a8\" d=\"M0 0h640v240H0z\"\u002F>\u003Cpath fill=\"#ce1126\" d=\"M0 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5l-4 4l-5-5m4 1l-1.5 1.5\"\u002F>\u003C\u002Fg>",{"left":15,"top":15,"width":26,"height":26,"rotate":15,"vFlip":13,"hFlip":13,"body":53},"\u003Cpath fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2\" d=\"M4 7a2 2 0 0 1 2-2h12a2 2 0 0 1 2 2v12a2 2 0 0 1-2 2H6a2 2 0 0 1-2-2zm12-4v4M8 3v4m-4 4h16m-9 4h1m0 0v3\"\u002F>",{"left":15,"top":15,"width":26,"height":26,"rotate":15,"vFlip":13,"hFlip":13,"body":55},"\u003Cpath fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2\" d=\"M18 6L6 18M6 6l12 12\"\u002F>",{"slug":57,"title":58,"excerpt":59,"image":60,"publishedAt":61,"topics":62,"readMinutes":66,"html":67,"metaTitle":58,"metaDescription":68,"shareImage":69,"updatedAt":73,"author":74,"related":77},"deepseek-ships-v4-1-flash-1017-with-open-weights-and-opens-its-search-and-fetch-apis","DeepSeek ships V4.1-Flash-1017 with open weights and opens its Search and Fetch APIs","DeepSeek has released V4.1-Flash-1017, a minor update to its Flash model with open MIT weights, unchanged API prices and higher scores on its own coding and agent benchmarks. It also opened its in-house Search and Fetch APIs to all developers.","\u002Fcontent\u002Fimages\u002F2026\u002F10\u002Fdeepseek_v41_flash_1017.png","2026-10-18T18:02:24.000+08:00",[63],{"key":64,"label":65},"news","News",3,"\u003Cp>DeepSeek released DeepSeek-V4.1-Flash-1017 on October 17, 2026. The company describes it as a minor update to \u003Ca href=\"https:\u002F\u002Fhuggingface.co\u002Fdeepseek-ai\u002FDeepSeek-V4.1-Flash?ref=ghost.jdneer.com\">DeepSeek-V4.1-Flash\u003C\u002Fa>, which shipped on September 10, with better scores on reasoning, coding, agent and vision tests, along with shorter outputs and faster task completion. The new version is already live on DeepSeek's website, app and API, according to the \u003Ca href=\"https:\u002F\u002Fapi-docs.deepseek.com\u002Fnews\u002Fnews261017?ref=ghost.jdneer.com\">release note\u003C\u002Fa>.\u003C\u002Fp>\u003Cp>The weights are public under the MIT License on \u003Ca href=\"https:\u002F\u002Fhuggingface.co\u002Fdeepseek-ai\u002FDeepSeek-V4.1-Flash-1017?ref=ghost.jdneer.com\">Hugging Face\u003C\u002Fa> and \u003Ca href=\"https:\u002F\u002Fmodelscope.cn\u002Fmodels\u002Fdeepseek-ai\u002FDeepSeek-V4.1-Flash-1017?ref=ghost.jdneer.com\">ModelScope\u003C\u002Fa>. The model card lists a 1M token context window and recommends a temperature and top_p of 1.0.\u003C\u002Fp>\u003Ch2 id=\"same-api-name-same-prices\">Same API name, same prices\u003C\u002Fh2>\u003Cp>Developers do not need to change anything to get the new model. DeepSeek's \u003Ca href=\"https:\u002F\u002Fapi-docs.deepseek.com\u002Fupdates?ref=ghost.jdneer.com\">change log\u003C\u002Fa> says the calling method and pricing stay the same, and the \u003Ccode>deepseek-flash\u003C\u002Fcode> model name now points to V4.1-Flash-1017. The older names \u003Ccode>deepseek-v4-flash\u003C\u002Fcode> and \u003Ccode>deepseek-v4-flash-vision-exp\u003C\u002Fcode> are still accepted and are served by the new model at the Flash price.\u003C\u002Fp>\u003Cp>On DeepSeek's \u003Ca href=\"https:\u002F\u002Fapi-docs.deepseek.com\u002Fquick_start\u002Fpricing?ref=ghost.jdneer.com\">pricing page\u003C\u002Fa>, off-peak rates for \u003Ccode>deepseek-flash\u003C\u002Fcode> are $0.15 per million input tokens on a cache miss, $0.003 on a cache hit, and $0.60 per million output tokens. Peak rates are double: $0.30 in and $1.20 out. Peak hours are 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays, which is 9 AM to 12 PM and 2 PM to 6 PM in Manila. Weekends and Chinese public holidays count as off-peak. The API supports up to 384K output tokens and accepts images.\u003C\u002Fp>\u003Ch2 id=\"deepseeks-benchmark-numbers\">DeepSeek's benchmark numbers\u003C\u002Fh2>\u003Cp>All figures below come from DeepSeek's \u003Ca href=\"https:\u002F\u002Fhuggingface.co\u002Fdeepseek-ai\u002FDeepSeek-V4.1-Flash-1017?ref=ghost.jdneer.com\">model card\u003C\u002Fa> and release note. They have not been independently verified. DeepSeek says it ran Terminal-Bench 4.0 with the Claude Code harness and DeepSWE v1.1 with the Mini-SWE-V2 harness.\u003C\u002Fp>\n\n\u003Ctable>\u003Cthead>\u003Ctr>\u003Cth>Benchmark\u003C\u002Fth>\u003Cth>V4.1-Flash-1017\u003C\u002Fth>\u003Cth>V4.1-Flash (Sept)\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd>HLE (no tools)\u003C\u002Ftd>\u003Ctd>42.6 (44.0 text-only)\u003C\u002Ftd>\u003Ctd>36.8 (39.1 text-only)\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Terminal-Bench 4.0\u003C\u002Ftd>\u003Ctd>42.3\u003C\u002Ftd>\u003Ctd>31.2\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>DeepSWE v1.1\u003C\u002Ftd>\u003Ctd>77.0\u003C\u002Ftd>\u003Ctd>74.2\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>ProgramBench\u003C\u002Ftd>\u003Ctd>29.1\u003C\u002Ftd>\u003Ctd>20.3\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>NL2Repo-Bench\u003C\u002Ftd>\u003Ctd>68.2\u003C\u002Ftd>\u003Ctd>65.4\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Automation-Bench v1.0.6\u003C\u002Ftd>\u003Ctd>60.5\u003C\u002Ftd>\u003Ctd>54.8\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Agents' Last Exam\u003C\u002Ftd>\u003Ctd>35.4\u003C\u002Ftd>\u003Ctd>31.8\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Apex Bench v1.1\u003C\u002Ftd>\u003Ctd>72.1\u003C\u002Ftd>\u003Ctd>64.6\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>Chartography (with tools)\u003C\u002Ftd>\u003Ctd>83.0\u003C\u002Ftd>\u003Ctd>78.9\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>BabyVision (with tools)\u003C\u002Ftd>\u003Ctd>92.5\u003C\u002Ftd>\u003Ctd>89.6\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd>ZeroBench-main (with tools)\u003C\u002Ftd>\u003Ctd>51.0\u003C\u002Ftd>\u003Ctd>49.0\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\n\n\u003Cp>The largest jump is on Terminal-Bench 4.0, from 31.2 to 42.3. On DeepSWE v1.1, the coding benchmark DeepSeek leads with, the score rises from 74.2 to 77.0. DeepSeek's own chart of DeepSWE score against cost puts the new model's best setting at about $0.20 per task, while the September version's best setting sits just under $0.50. Those cost figures are read from the company's chart, not from a published table.\u003C\u002Fp>\u003Cp>The model card also compares the update with other models. In DeepSeek's table, Claude Opus 5 still scores higher on Terminal-Bench 4.0 (51.8) and HLE (56.3), while V4.1-Flash-1017 comes out ahead on DeepSWE v1.1 and several agent tests. DeepSeek says it tuned the model for its own DeepSeek Harness and for Tencent's CodeBuddy and WorkBuddy, and recommends DeepSeek Harness 0.2.1-rc.1 or later.\u003C\u002Fp>\u003Ch2 id=\"search-and-fetch-apis-open-to-everyone\">Search and Fetch APIs open to everyone\u003C\u002Fh2>\u003Cp>DeepSeek also opened up the in-house search engine behind its chat product. The new Search and Fetch endpoints are standalone APIs, each priced at $0.75 per 1,000 successful requests. When the DeepSeek API is used through DeepSeek Harness, Claude Code or Codex, server-side tool calls already go through these APIs, and those calls are free for now. Per-request billing for them starts at midnight Beijing time on November 1, 2026, which is also midnight in Manila (16:00 UTC on October 31).\u003C\u002Fp>\u003Ch2 id=\"running-it-locally\">Running it locally\u003C\u002Fh2>\u003Cp>This release does not ship a Jinja chat template. Instead, the repository includes a Python reference encoder in its \u003Ccode>encoding\u003C\u002Fcode> folder, and DeepSeek published \u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fdeepseek-ai\u002Fdeepseek-recipe?ref=ghost.jdneer.com\">deepseek-recipe\u003C\u002Fa>, a set of Rust libraries with Python bindings that handle the prompt format. Weight conversion and local inference steps are in the repository's \u003Ccode>inference\u003C\u002Fcode> folder.\u003C\u002Fp>\u003Cp>\u003Cem>Sources: \u003C\u002Fem>\u003Ca href=\"https:\u002F\u002Fapi-docs.deepseek.com\u002Fnews\u002Fnews261017?ref=ghost.jdneer.com\">\u003Cem>DeepSeek release note\u003C\u002Fem>\u003C\u002Fa>\u003Cem>, \u003C\u002Fem>\u003Ca href=\"https:\u002F\u002Fapi-docs.deepseek.com\u002Fupdates?ref=ghost.jdneer.com\">\u003Cem>DeepSeek API change log\u003C\u002Fem>\u003C\u002Fa>\u003Cem>, \u003C\u002Fem>\u003Ca href=\"https:\u002F\u002Fapi-docs.deepseek.com\u002Fquick_start\u002Fpricing?ref=ghost.jdneer.com\">\u003Cem>DeepSeek models and pricing\u003C\u002Fem>\u003C\u002Fa>\u003Cem>, \u003C\u002Fem>\u003Ca href=\"https:\u002F\u002Fhuggingface.co\u002Fdeepseek-ai\u002FDeepSeek-V4.1-Flash-1017?ref=ghost.jdneer.com\">\u003Cem>Hugging Face model card\u003C\u002Fem>\u003C\u002Fa>\u003Cem>, \u003C\u002Fem>\u003Ca href=\"https:\u002F\u002Fmodelscope.cn\u002Fmodels\u002Fdeepseek-ai\u002FDeepSeek-V4.1-Flash-1017?ref=ghost.jdneer.com\">\u003Cem>ModelScope\u003C\u002Fem>\u003C\u002Fa>\u003Cem>.\u003C\u002Fem>\u003C\u002Fp>","DeepSeek has released V4.1-Flash-1017, a minor update to its Flash model with open MIT weights, unchanged API prices and higher scores on its own coding...",{"src":60,"width":70,"height":71,"type":72},1600,900,"image\u002Fpng","2026-10-18T18:03:58.000+08:00",{"name":75,"url":76,"owner":13},"Aiko Tanaka",null,[78,87,98,106],{"slug":79,"title":80,"excerpt":81,"image":82,"publishedAt":83,"topics":84,"readMinutes":86},"rakazo-v0-3-3-self-hosted-grok-bot-alternative","Rakazo v0.3.3: What's New in the Self-Hosted Grok Bot Alternative","Rakazo, the open source, self-hostable AI agent platform, shipped v0.3.3 on October 22. A small release: delete chats on mobile, Telegram replies with images and files, and a handful of fixes.","\u002Fcontent\u002Fimages\u002F2026\u002F10\u002Frakazo-readme-hero-1280x720.png","2026-10-24T18:00:00.000+08:00",[85],{"key":64,"label":65},1,{"slug":88,"title":89,"excerpt":90,"image":91,"publishedAt":92,"topics":93,"readMinutes":86},"dito-cme-board-changes-2026","DITO CME elects four new directors at annual stockholders' meeting","DITO CME Holdings elected Oozi Cats, Xinxin Wang, Enrique Pampolina and Cenon Audencial Jr. to its board, as Eric Recto and Salvador Medialdea ended their terms.","\u002Fcontent\u002Fimages\u002F2026\u002F10\u002Fdito-board-boardroom-pavel-gromov-unsplash.jpg","2026-10-24T08:00:00.000+08:00",[94,97],{"key":95,"label":96},"philippines","Philippines",{"key":64,"label":65},{"slug":99,"title":100,"excerpt":101,"image":102,"publishedAt":103,"topics":104,"readMinutes":86},"downfall-of-bgp-exchange","The downfall of bgp.exchange: how a volunteer peering exchange lost its domain, mail and management plane in a day","In September 2026 a volunteer peering exchange lost its domain, mail and management plane in about a day. A timeline from public records.","\u002Fcontent\u002Fimages\u002F2026\u002F10\u002Fbgpx-fiber-switch.jpg","2026-10-23T12:00:00.000+08:00",[105],{"key":64,"label":65},{"slug":107,"title":108,"excerpt":109,"image":110,"publishedAt":111,"topics":112,"readMinutes":86},"a-third-of-philippine-businesses-now-use-ai-but-only-17-have-a-plan-to-scale-it","A Third of Philippine Businesses Now Use AI, but Only 17% Have a Plan to Scale It","An AWS-commissioned study says 32% of Philippine businesses now use AI, up from 21% a year ago. But only 17% have a roadmap to scale it, and just 19% feel ready for agentic AI. Skills remain the biggest gap. Here are the numbers that matter.","\u002Fcontent\u002Fimages\u002F2026\u002F10\u002Fteam-laptops-cherrydeck-unsplash.jpg","2026-10-22T18:00:00.000+08:00",[113,114],{"key":95,"label":96},{"key":64,"label":65},{"left":15,"top":15,"width":26,"height":26,"rotate":15,"vFlip":13,"hFlip":13,"body":116},"\u003Cpath fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2\" d=\"M5 12h14M5 12l6 6m-6-6l6-6\"\u002F>",{"left":15,"top":15,"width":26,"height":26,"rotate":15,"vFlip":13,"hFlip":13,"body":118},"\u003Cg fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2\">\u003Cpath d=\"M6.5 7.5a1 1 0 1 0 2 0a1 1 0 1 0-2 0\"\u002F>\u003Cpath d=\"M3 6v5.172a2 2 0 0 0 .586 1.414l7.71 7.71a2.41 2.41 0 0 0 3.408 0l5.592-5.592a2.41 2.41 0 0 0 0-3.408l-7.71-7.71A2 2 0 0 0 11.172 3H6a3 3 0 0 0-3 3\"\u002F>\u003C\u002Fg>"]