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OpenRouter

Service

OpenRouter is a service designed to provide a unified API for accessing multiple large language models. It is intended for developers and businesses looking to integrate various AI models into their applications seamlessly. A key use case is simplifying the process of switching between different AI models without changing the underlying code.

article 6 storys calendar_today First seen: 2026-02-03 update Last seen: 2026-02-24 open_in_new Website menu_book Wikipedia

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Links to check for updates: homepage, feed, or git repo.

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From vibe coding to agentic engineering: test-first orchestration

Engineering teams are shifting from vibe coding to disciplined agentic engineering that treats AI as test-driven collaborators and demands spec-first oversight. In a concise critique of “prompt DJ” development, [Roger Wong](https://rogerwong.me/2026/02/agentic-engineering) summarizes Addy Osmani’s call for agentic engineering—engineers orchestrate coding agents, act as architects and reviewers, and enforce spec-first discipline instead of accepting whatever the model returns. [Simon Willison’s](https://simonwillison.net/guides/agentic-engineering-patterns/first-run-the-tests/#atom-everything) “First run the tests” pattern operationalizes this by making a test suite the entry point for any agent, turning TDD into a four‑word prompt and letting agents learn a codebase through its tests. Hands-on workflows show how to scale this in practice, from a [complete greenfield agentic setup](https://www.youtube.com/watch?v=goOZSXmrYQ4&pp=ygUYQUkgY29kaW5nIGFnZW50IHdvcmtmbG93) to [advanced agent teams comparing Claude Code and Codex](https://www.youtube.com/watch?v=7BXZ-qR5cPE&pp=ygUYQUkgY29kaW5nIGFnZW50IHdvcmtmbG93), while case studies like [DumbQuestion.ai](https://dev.to/jagostoni/dumbquestionai--2ee) underline the need for structured backlogs and cost-aware multi‑model choices.

calendar_today 2026-02-24
openai codex claude-code openrouter agentic-engineering

Windsurf ships new models, Linux ARM64, and enterprise hooks

Windsurf rolled out new frontier coding models, full Linux ARM64 support, and enterprise-grade Cascade Hooks while community feedback spotlights its transparent crediting versus rivals' opaque limits. Windsurf’s latest updates add Gemini 3.1 Pro, Claude Sonnet 4.6, GLM-5, Minimax M2.5, and GPT-5.3-Codex-Spark with time-limited credit multipliers, plus quality-of-life fixes and features like automatic Plan→Code switching, skills loading from .agents/skills, tracked rules in post_cascade_response, and diff zones auto-closing on commit; importantly, it now provides full Linux ARM64 deb/rpm packages and enterprise cloud config for Cascade Hooks with Devin service key auth, as detailed in the [Windsurf changelog](https://windsurf.com/changelog). A power user’s comparison underscores cost control and predictability: they favored Windsurf’s clear credit model over Cursor/Claude Code’s rate-limit surprises, keeping GitHub Copilot Pro+ for predictable premium requests while continuing to code primarily in Windsurf, per this [Reddit write-up](https://www.reddit.com/r/windsurf/comments/1r9b58e/i_almost_left_windsurf/).

calendar_today 2026-02-20
windsurf gemini-31-pro claude-sonnet-46 glm-5 minimax-m25

Open-weight "AI engineer" models arrive: Qwen 3.5, GLM-5, MiniMax M2.5

A new wave of open-weight frontier models now rivals closed systems on coding and long-horizon agent tasks, making self-hosted AI engineer workflows practical for backend and data teams. Alibaba’s Qwen 3.5 ships as an open‑weights Mixture‑of‑Experts model (397B total, 17B active) with multimodal input and a 256K context, alongside a hosted Qwen3.5‑Plus variant offering 1M context and built‑in tools; details and early impressions are summarized by Simon Willison’s write‑up of the [Qwen 3.5 release](https://simonwillison.net/2026/Feb/17/qwen35/#atom-everything) and the official [Qwen blog](https://qwen.ai/blog?id=qwen3.5). Z.ai’s GLM‑5 launched open source with top open-model scores on SWE‑bench‑Verified (77.8) and Terminal Bench 2.0 (56.2), plus long‑context and RL‑driven agent training advances, with the announcement and code at [BusinessWire](https://www.businesswire.com/news/home/20260215030665/en/GLM-5-Launch-Signals-a-New-Era-in-AI-When-Models-Become-Engineers) and the [GitHub repo](https://github.com/zai-org/GLM-5). MiniMax M2.5 claims state‑of‑the‑art coding/agent performance (e.g., 80.2% SWE‑Bench Verified) and aggressive cost/speed on its [Hugging Face card](https://huggingface.co/unsloth/MiniMax-M2.5), while hands‑on videos compare real coding runs for GLM‑5 and M2.5; you can also quickly trial free models via [OpenRouter’s free router](https://openrouter.ai/openrouter/free).

calendar_today 2026-02-17
qwen35-397b-a17b qwen35-plus qwen-chat alibaba-cloud glm-5

GLM-5 and MiniMax M2.5 push low-cost, agentic coding into production range

Two Chinese releases—Zhipu AI’s GLM-5 and MiniMax M2.5—signal a shift toward affordable, agentic coding models that challenge frontier systems on practical benchmarks. Zhipu AI’s GLM-5 is positioned as an MIT-licensed open model with a native Agent Mode that rivals proprietary leaders on multiple benchmarks, with a deep-dive detailing its pre-launch appearance under a pseudonym and hints from vLLM pull requests ([official overview](https://z.ai/blog/glm-5?_bhlid=d84a093754c9e11cb0d2e9ff416fd99cb5f0e2da), [leak analysis](https://medium.com/reading-sh/glm-5-chinas-745b-parameter-open-source-model-that-leaked-before-it-launched-b2cfbafe99ef?source=rss-8af100df272------2), [weights claim](https://medium.com/ai-software-engineer/glm-5-arrive-with-a-bang-from-vibe-coding-to-agentic-engineering-disrupts-opus-b2b13f02b819)). MiniMax’s M2.5 posts strong results on coding and agentic tasks—80.2% SWE-Bench Verified, 51.3% Multi-SWE-Bench, 76.3% BrowseComp—while running 37% faster than M2.1 and costing roughly $1/hour at 100 tokens/sec (or $0.30/hour at 50 tps), with speed reportedly matching Claude Opus 4.6 ([release details](https://www.minimax.io/news/minimax-m25)). For developer workflows, quick-start videos show GLM-5 (and similarly Kimi K2.5) slotting into Claude Code with minimal setup, lowering trial friction inside existing IDEs ([GLM-5 with Claude Code](https://www.youtube.com/watch?v=Ey-HW-nJBiw&pp=ygURQ3Vyc29yIElERSB1cGRhdGU%3D), [Kimi K2.5 with Claude Code](https://www.youtube.com/watch?v=yZtLwOhmHps&pp=ygURQ3Vyc29yIElERSB1cGRhdGU%3D)).

calendar_today 2026-02-12
zhipu-ai glm-5 minimax minimax-m25 openrouter

Continue config-yaml 1.41–1.42 expands model routing, hardens CLI/networking

Continue shipped config-yaml updates that add OpenRouter dynamic model loading and Nous Research Hermes models, plus SSL verification for client transports and reasoning-content handling in chats ([config-yaml 1.42.0](https://github.com/continuedev/continue/releases/tag/%40continuedev/config-yaml%401.42.0)[^1]). The prior release fixes OpenAI Responses API parallel tool-call call_ids, improves WSL PATH detection, patches file-descriptor leaks in resource monitoring, upgrades openapi-generator, and adds .continuerc.json tool prompt overrides ([config-yaml 1.41.0](https://github.com/continuedev/continue/releases/tag/%40continuedev/config-yaml%401.41.0)[^2]). A separate CLI stable build was published directly from main ([CLI v1.5.43](https://github.com/continuedev/continue/releases/tag/v1.5.43)[^3]); note the Feb 3 config changes may land in a subsequent CLI cut. [^1]: Adds: OpenRouter provider, Hermes models, SSL verification toggle, and reasoning-content support. [^2]: Adds: Responses API call_ids fix, WSL PATH detection, resource monitoring stability, tool prompt overrides. [^3]: Adds: Stable CLI build note; timing suggests it may not include Feb 3 config-yaml changes.

calendar_today 2026-02-03
continue continue-cli openrouter openai nous-research