Qwen 3.8 in Rope Notes: Frontier Preview for Plan and Execute

Alibaba's Qwen team previewed Qwen3.8-Max-Preview, a 2.4-trillion-parameter multimodal model with a 1-million-token context window, at WAIC in Shanghai, claiming it ranks second only to Anthropic's Claude Fable 5. Independent leaderboards and a full model card are not yet public, and open weights are promised "soon" with no date or license. The model is available via cloud API for use in Rope Notes' agent for Plan and Execute workflows, while local use still relies on the existing open-weight Qwen3 line.

Three days after Moonshot’s Kimi K3, Alibaba’s Qwen team previewed Qwen3.8-Max-Preview at WAIC in Shanghai — a 2.4-trillion-parameter multimodal flagship with a 1-million-token context window . Alibaba positions it near the top of the frontier stack their claim: second only to Anthropic’s Claude Fable 5 . Independent leaderboards and a full model card are not public yet, so treat the ranking as the vendor’s until third-party numbers land. If you already use Rope Notes’ agent for Dart, Flutter, or multi-file refactors, you can point a cloud provider at the preview today. Open weights are promised “soon,” with no date or license yet — so local 3.8 Max is not a thing yet. | Fact | Status | |---|---| | Model ID | qwen3.8-max-preview | | Parameters | 2.4T Alibaba ; activated-parameter count not published | | Context | 1M tokens per | There is no new “Qwen 3.8B” dense twin in this launch. The name is Qwen 3.8 family version , not an 8-billion-parameter sibling. For on-device work you still use the existing open-weight Qwen3 line qwen3:8b and friends via Ollama / llama.cpp until 3.8 Max weights appear. Rope Notes is a local-first, IDE-style editor: rope-backed editing, Dart analysis, and an agent that can Chat , Plan , and Execute — with tools, then multi-file edit proposals you accept or reject. A long-context frontier model is useful for the Plan → Execute loop; a local Qwen3 keeps day-to-day work on-device. | Qwen 3.8 Max strength | How Rope Notes uses it | |---|---| | Long-horizon coding + tools | Agent tool loop read file , search, definitions, … over many turns | | 1M context | Open tabs, @ mentions, plans, and memory stay coherent longer | | Multimodal input | Screenshot / layout feedback when your session includes image context | | OpenAI-compatible API | Same Preferences → Agent flow as other cloud backends | | Open weights later | Same UX once you host weights or a LAN OpenAI-compatible endpoint | Alibaba markets strong coding and full-stack work relative to Qwen3.7-Max. Until independent scores exist, the practical test is your own Plan/Execute sessions — not launch-day leaderboard claims. qwen3.8-max-preview not general pay-as-you-go at announce time .Open weights, when they land, change the local story. Until then, treat 3.8 Max as a cloud provider in Preferences. You need a desktop or mobile build with cloud agent backends web builds do not run the agent . https://dashscope-intl.aliyuncs.com/compatible-mode/v1 qwen3.8-max-preview If your Token Plan console shows a dedicated base URL some Alibaba plans use a plan-specific host , use that URL instead — the model ID stays qwen3.8-max-preview . Provider configs live under .rope notes/preferences.toml . Share the setup , not the secret keys. Rope Notes remains Ollama-first on desktop llama.cpp is also first-class . For offline or source-sovereign sessions: ollama pull qwen3:8b or a larger open Qwen3 tag your machine can hold Then select the Ollama local or llama.cpp local provider and the pulled tag. That is the current Qwen3 open line — not Qwen3.8-Max-Preview. @lib/... or by dragging from Explorer. plan- .md / checklist under .rope notes/ .The 1M window helps across long checklists; still prefer targeted @ mentions so turns stay cheaper and sharper. When Execute proposes changes, Rope Notes surfaces an inline diff review Accept / Reject per file, or Accept all . The model does not write straight through your buffer — you still own the rope. A common split: qwen3:8b or similar qwen3.8-max-preview Switch providers from the agent panel; no project rewrite required. On Android, cloud backends work even though local Ollama is a desktop feature. Use session transfer to move buffers and agent artifacts between machines, then keep the same Qwen Cloud provider selected. Accurate expectations beat marketing: @ mentions with LSP diagnostics on those snippets /remember , optional cognitive memory hits, active skills list directory , grep , read file , … for on-demand deeper readsUse @ and Plan artifacts deliberately; a 1M window is not a reason to paste the whole repo by default. Before long Execute sessions: .rope notes/permissions.toml .git and secret paths as neededFrontier models are most useful when they cannot touch everything. qwen3.8-max-preview qwen3.8-max-preview Qwen3.8-Max-Preview is available now as a hosted preview. In Rope Notes it is a Preferences change — and a natural cloud counterpart to the local Qwen3 models you may already run on Ollama. Rope Notes — a high-performance, local-first editor with a real AI agent, Dart analysis, and optional P2P sync. ropenotes.dev