Evidence brief
Perplexity users can choose the U.S.-hosted DeepSeek V4 Pro in its Computer product.
The repost says Perplexity announced that US-hosted DeepSeek V4 Pro is now available in Perplexity Computer, and evaluated it against other models.
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Source attributionX · @AravSrinivas
Open the original sourceRelationships are derived from shared topics, entities, categories, tags, and community context; every result remains independently source-linked.
Zhipu announced that the GLM-5.3 API is available today, saying it excels at complex coding, defensive cybersecurity, and long-horizon tasks, with an AA general intelligence index score of 60, and API pricing unchanged from GLM-5.2.
Why it mattersDevelopers can use this to compare the API usage costs of GLM 5.3, DeepSeek, and Kimi.
Original sourceThe author says they built Pilot Harness, a ready-to-use client for DeepSeek Harness, including a client shell and plugins for UI interactions, file trees, model providers, and model management.
Why it mattersIt lets users use the client directly or install the plugin into their own DeepSeek Harness.
Original sourceThe poster says the open-source DeepSeek Harness desktop client has been popular recently, and believes the DSH philosophy should be minimalism and everything as a plugin, questioning why some desktop wrappers hard-code features into the shell.
Why it mattersThis view points to the plugin boundaries and product form choices of desktop Agent tools.
Original sourceAgent memory is not a feature to switch on casually; its dose must be calibrated to model capability. Strong models are better suited to injecting a full set of guides, with DeepSeek-V3.2 (671B MoE) improving task completion by +9.5 percentage points. Weaker models perform best with curated retrieval, with gpt-oss-120b (117B MoE) improving by +16.1pp while adding only +5% tokens. This method requires no weight updates or manual annotation; it works by distilling guides from an agent’s past trajectories and injecting them at inference time.
Original sourceThe author discusses whether DeepSeek Harness, if centered on an SDK, could also feed real software engineering task trajectories back into Post-training like Coding products such as ZCode.
Why it mattersThis relates to whether Coding products can retain long-cycle task data and support later model upgrades.
Original source