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GLM 5.3 Flash

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Headlines · 6

  1. Rivermark benchmark finds tuned open models competitive on design

    Rivermark developer JannVanDam reported preliminary results from 112 social and marketing design requests evaluated through more than 4,700 blind pairwise human judgments. He said DeepSeek v4.1 Flash 1017 and GLM 5.3 Flash, using Rivermark, matched or beat plain Claude Code with Sonnet 5.5 and /design, while Sonnet 5.5 achieved the strongest result with Rivermark. The design-specific harness has been tuned for some models used in production, though not for the benchmark test cases. The author is validating the findings with additional judges.

    r/LocalLLaMA · 🔥 0
  2. Xiaomi MiMo Desktop upgrades membership with more quota and third-party models

    Xiaomi MiMo announced an immediate upgrade to MiMo Desktop membership benefits, increasing members’ overall usage quota without raising prices. Members can now select selected third-party models in addition to MiMo models, and IT之家 observed DeepSeek V4 Pro, GLM 5.3, Kimi K3, and Qwen 3.8 variants in the expanded list.

    IT之家 AI · 🔥 0
  3. OpenRouter tests Armor against prompt-injection attacks

    OpenRouter evaluated 25 prompt-injection attacks against four models using a document-summarizing assistant, comparing configurations with defenses enabled and disabled. Its Armor tool-call filter reduced successful attack emails from 73 of 1,440 attempts to zero, while labeling documents as data alone left 13 of 720 attempts successful. Armor allowed nearly every explicitly requested email but blocked one legitimate request because the user had not named the recipient address.

    OpenRouter Blog · 🔥 0
  4. Reddit user shows eight-Radeon R9700 rig

    Reddit user /u/NunzeCs showed a rig upgraded from four to eight Radeon R9700 GPUs, saying the added capacity would provide more room for larger models. The listed system includes a Threadripper 9955WX, 128GB of DDR5 5600 memory, an ASRock WRX 90 WS EVO motherboard, and Seasonic power supplies rated at 2200W and 1600W. The user reported problems with a bifurcation card and six extension cables and said they planned to buy a retimer. They also said they were running QFN and preferred “QFN with Radiance” after trying GLM 5.3 Flash. The post does not provide benchmarks or detail the nature of the cable problems.

    r/LocalLLaMA · 🔥 0
  5. DeepSeek V4.1-Flash-1017 Tops OpenRouter Weekly Usage Ranking

    DeepSeek V4.1-Flash-1017 ranked first on OpenRouter’s Oct. 19–25 weekly model-usage chart with 33.6 trillion tokens, up 801% from the previous week. The previous V4.1 Flash ranked second with 18 trillion tokens and a 45% decline, while MiniMax M3.1 Flash, GLM 5.3 Flash, and Tencent Hy4 preview completed the top five. The ranking covers aggregated API traffic routed through OpenRouter and excludes vendor websites, independent apps, and private deployments.

    36氪 人工智能 · 🔥 0
  6. Hands-on: an iPhone Duo app that dispatches agent tasks to a home Mac Studio

    APPSO published a first-hand account of pairing a 21,499-yuan iPhone Duo with an 86,749-yuan Mac Studio to build what it calls a personal AI hub, with the desktop left at home to run models and execute agent tasks while the phone connects remotely. The team wrote a custom app tailored to the Duo's three states: closed, half-folded hover and fully unfolded, giving each a different agent interface — an approval dashboard, a live execution view with voice dispatch, and a two-column console for previewing outputs. On the network side, an HTTPS proxy on the Mac listens on its LAN address and forwards phone requests to a local Bridge service, with Tailscale suggested for cellular access; tasks are tracked by session ID, and a dropped phone connection does not cancel them while the Mac keeps running. Models including DeepSeek V4 Flash, Qwen3.8 27B and GLM 5.3 Flash were served locally through LM Studio, with DeepSeek Harness handling planning and tool use; APPSO said one pelican-on-a-bicycle generation took 2 minutes 18 seconds, averaging 34 tokens per second after two rounds of edits.

    爱范儿 · 🔥 0

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