AI Coding Live News

Microsoft Open-Sources Mage-VL-Cowork, a 4B Computer-Use Agent That Chooses Between Clicking the GUI and Running Bash, Scoring 66.0% on OSWorld-Verified

On October 30, Microsoft's Mage team released Mage-VL-Cowork on Hugging Face under Apache-2.0: a 4B multimodal computer-use agent in which a single model decides at every step whether to act through screenshots and GUI clicks (computer_use) or through bash and Python in a terminal, with no external orchestrator. Microsoft reports a two-run average of 66.0% on OSWorld-Verified (361 tasks, 50-step budget), above Qwen3.6-27B at 63.9% but below the 9B SCALECUA-Qwen3.5-9B at 68.7%.

Microsoft Open-Sources Mage-VL-Cowork, a 4B Computer-Use Agent That Chooses Between Clicking the GUI and Running Bash, Scoring 66.0% on OSWorld-Verified

Key Takeaways

  • 4B parameters, built on Mage-VL (Mage-ViT vision encoder plus Qwen3-4B-Instruct-2507); about 9.48 GB of bf16 weights under Apache-2.0.
  • On OSWorld-Verified, two independent runs scored 65.33% and 66.75% for a 66.0% average; 87.5% on operating-system tasks and 62.7% on multi-app workflows.
  • In Microsoft's side-by-side, a LibreOffice Calc chart task took 39 seconds (6 steps) via Python in the terminal, versus 9:56 (39 steps) for GUI-only Qwen3.6-27B.
  • Online RL adds 10.16 points over hybrid SFT while cutting mean model calls by 13.0% and output tokens by 25.4%.
  • Training data came from Mage-CUA-Forge, which synthesized about 294K desktop and web tasks across 6,915 skills and cut per-task generation cost from $0.906 to $0.158.
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⚡ Mage-VL-Cowork⚡ Mage-VL⚡ Qwen3-4B⚡ Qwen3.6-27B🌐 Microsoft

Claude Code waits 3x less for the first token: gzip on every turn and cloud sessions that warm up as you type (p90 4.07s to 1.33s)

On Oct 16 Anthropic shared August-to-October latency gains. p90 wait before the first token, excluding model time, fell from 4.07s to 1.33s for local Claude Code sessions (about 3x) and from 16.99s to 6.00s for cloud sessions (2.8x); Claude chat and Cowork improved about 1.5x, and API p50 time to first token dropped from 1.53s to 1.01s. The main changes are default gzip for large requests since CLI 2.1.300 and cloud sessions that start when you begin typing.

Claude Code waits 3x less for the first token: gzip on every turn and cloud sessions that warm up as you type (p90 4.07s to 1.33s)

Key Takeaways

  • Local Claude Code p90 wait before first token (excluding model time): 4.07s to 1.33s, about 3x; cloud sessions 16.99s to 6.00s, 2.8x (Anthropic figures, Aug to Oct 2026)
  • Claude chat and Cowork p90 3.36s to 2.17s; Claude API p50 time to first token (including model time) 1.53s to 1.01s, both about 1.5x
  • Since CLI 2.1.300 (released Oct 14), large requests to api.anthropic.com are gzipped even with telemetry off; set CLAUDE_CODE_GZIP_REQUEST_BODIES=0 to disable
  • A community measurement in issue #90457 found real request bodies compress about 2.1x and one machine saved 185 MB of upload in about 3 hours
  • Gzip shrinks bytes on the wire, not billed tokens
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Alibaba Synthesizes 64.9K Interactive Environments in Cowork-Gym (27B Beats 100B+ on ClawEval) & Harvard/MIT Open-Source Market-Based Agent Swarms (MPT)

Alibaba researchers introduce Cowork-Gym (arXiv:2610.17670), synthesizing 64,900 interactive human-agent coworking environments paired with a stateful user simulator that dynamically edits the shared workspace; post-training a 27B Qwen model yields #1 scores on PawBench and ClawEval, outperforming 100B+ parameter models. Concurrently, Harvard and MIT researchers open-source Market-Based Post-Training (MPT, arXiv:2610.22322), enabling decentralized agent swarms to jointly learn action policies and bidding-based self-orchestration without a central coordinator.

Alibaba Synthesizes 64.9K Interactive Environments in Cowork-Gym (27B Beats 100B+ on ClawEval) & Harvard/MIT Open-Source Market-Based Agent Swarms (MPT)

Key Takeaways

  • 64.9K synthesized environments in Cowork-Gym: pairs a build-execute-revise loop with a stateful user simulator that edits shared workspaces alongside the agent
  • 27B model beats 100B+ giants on PawBench & ClawEval: post-trained Qwen models gain up to +8.7 average points across 6 agentic benchmarks
  • Market-Based Post-Training (MPT) for agent swarms: Harvard and MIT open-source a bidding-based RL framework for decentralized self-orchestration
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WorkRover: Fudan Unveils Recursive Environment Evolution for Cowork Agents, Surging JobBench by 26.27%

Training long-horizon cowork agents via reinforcement learning requires scalable, iteratively refined interactive environments. Researchers from Fudan University NLP Lab introduced WorkRover, a framework enabling recursive environment evolution. Featuring Factorial Compatibility Replay (FCR) to maintain alignment across work contexts, tasks, and verifiers, and Verifier-to-Turn Credit Assignment (VTCA) to route progress signals to causal prerequisite turns, WorkRover-35B-A3B outperforms baseline checkpoints by 26.27% on JobBench, 29.32% on OfficeQA Pro, and 413.25 Elo on GDPval v2.

Key Takeaways

  • Recursive environment evolution: empowers construction agents to iteratively adapt work contexts, tasks, and verifiers from workspace execution feedback
  • FCR and VTCA algorithms: Factorial Compatibility Replay selects minimal valid repairs; Verifier-to-Turn Credit Assignment credits causal prerequisite turns
  • Massive empirical leaps: WorkRover-35B-A3B achieves +26.27% on JobBench, +29.32% on OfficeQA Pro, and +413.25 Elo on GDPval v2
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Google Cloud launches Gemini agent: universal work agent with Gemini+Claude routing, sub-agents and coworker identities, multi-day cloud persistence

At Gemini at Work 2026 (Oct 8) Google launched the Gemini agent: objectives from one prompt box spanning Q&A, knowledge work, media, and code; cloud-persistent memory with sub-agent/coworker orchestration and Gemini+Claude model choice. Private preview now.

Google Cloud launches Gemini agent: universal work agent with Gemini+Claude routing, sub-agents and coworker identities, multi-day cloud persistence

Key Takeaways

  • One universal work agent for Q&A, knowledge work, media, and coding from objectives not step lists
  • Sub-agents plus coworker agents with dedicated identity/@agents.company.com; multi-hour/day runs
  • Model choice decoupled: routes across Gemini family and Anthropic Claude today
  • Governance: Agent Identity, Gateway, sandbox, Smart Routing, per-project spend caps
  • Availability: private preview now; broader for select Workspace Business/Enterprise
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CopilotKit open-sources OpenDots: self-hosted always-on coworker template; any AG-UI agent + OpenAI-compatible models (MIT)

Around 2026-10-01 CopilotKit released OpenDots (MIT): a self-hosted open alternative to OpenAI Dots. Each Dot can own a computer (browser/files/terminal), Spaces/Pages, live calls, Slack via Channels SDK, draft approval, and schedules. Bring any AG-UI agent and OpenAI-compatible model; computer access is off by default. ~1448★ / 176 forks at ingest (GitHub API).

CopilotKit open-sources OpenDots: self-hosted always-on coworker template; any AG-UI agent + OpenAI-compatible models (MIT)

Key Takeaways

  • Official blog 2026-10-01; repo CopilotKit/OpenDots MIT
  • Self-hosted always-on coworkers; any OpenAI-compatible model + AG-UI agents (vs closed Dots)
  • Features: per-Dot computer (off by default), Spaces/Pages, calls, Slack, draft approval, schedules, Automatic Learning
  • At ingest: ~1448★ / 176 forks; created 2026-09-29T17:13Z; pushed 2026-10-02T21:16Z
  • Quickstart: clone → npm ci → .env → npm run dev
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Anthropic Unifies Claude Chat and Cowork into Seamless Multi-Modal Workspace

Anthropic rolled out a major unified workspace redesign merging Claude Chat and Cowork. Users can now fluidly transition between conversational chat, persistent Cowork pairing, interactive Artifacts, and Design preview modes within a single continuous context thread.

Key Takeaways

  • Eliminates boundaries between Chat and Cowork, preserving continuous context across workflows
  • Dynamically routes between code pairing, document authoring, and interactive UI synthesis
  • Retains persistent project memory across modalities for long-horizon enterprise tasks
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Anthropic Merges Claude Cowork and Chat Into One Claude for Pro/Max

Anthropic is merging Claude Cowork and chat into one Claude experience: ask a quick question or hand off a report, keep work running after you close the laptop, and Claude asks when unclear while you keep final say. Existing Cowork chats, projects, artifacts, connectors, and skills carry over; Claude Design, Slides, and Docs are in beta on paid plans, rolling out to Pro and Max over the next few weeks.

Key Takeaways

  • Cowork and chat merge into one Claude that can keep working after you close the laptop
  • Existing Cowork chats, projects, artifacts, connectors, and skills carry forward
  • Claude Design, Slides, and Docs are in beta on paid plans; Pro and Max roll out over the next few weeks
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Microsoft open-sources Skill Recorder: record a desktop workflow once, Copilot CLI rebuilds a reusable Skill/Automation

Community coverage notes Microsoft open-sourced Skill Recorder (github.com/microsoft/skill-recorder, ~3.9k stars). After a local screen/activity capture, GitHub Copilot CLI reconstructs an intent plus ordered steps, then builds a SKILL.md Skill or schedulable Automation for Microsoft Scout, Copilot Cowork, and Copilot Studio—preferring native agent tools (gh, web_fetch) over click replay.

Key Takeaways

  • Microsoft open-sourced Skill Recorder (microsoft/skill-recorder), ~3.9k GitHub stars.
  • Local capture → Copilot CLI reconstructs intent + steps → Skill (SKILL.md) or Automation.
  • Targets Scout / Copilot Cowork / Copilot Studio; prefers native tools over click replay.
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Microsoft: GPT-6 Astra available today in Copilot Cowork and Copilot Studio

Microsoft EVP of Apps & Agents Jeff Teper says OpenAI GPT-6 Astra is rolling out today in Microsoft Copilot Cowork and Copilot Studio, with the official hub post at aka.ms/AstraInCopilot. Teams and custom agents can use the frontier model inside Microsoft’s Copilot stack.

Key Takeaways

  • Microsoft EVP Jeff Teper confirms GPT-6 Astra is live today in Copilot Cowork and Copilot Studio.
  • Official landing page: aka.ms/AstraInCopilot (Microsoft Community Hub).
  • Frontier model access for teams and Copilot Studio custom agents.
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Claude Can Now Use Your Computer in the Background

Anthropic enabled Claude to use a user's computer in the background inside Claude Cowork and Claude Code—clicking, typing, and opening apps while the user works on something else. The beta is available to Pro and Max plans in the macOS desktop app. It moves Claude from a chat assistant to a parallel desktop coding and productivity agent.

Key Takeaways

  • Clicks, types, and opens apps in the background while you work
  • Available in both Claude Cowork and Claude Code
  • Beta for Pro and Max plans on the macOS desktop app
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Command Code ships Qwen 3.8 Max 0902: 2.4T params, 1M context, coding/cowork post-train

Command Code says Qwen 3.8 Max 0902 is live: an upgraded Qwen 3.8 Max with ~2.4T parameters, 1M context, and post-training for coding and cowork. It is available on GOAT, Pro, Max, and API—useful when closed-model routes flap.

Key Takeaways

  • Qwen 3.8 Max 0902: ~2.4T params, 1M context, coding/cowork post-train.
  • Available on Command Code GOAT, Pro, Max, and API.
  • Positioned as an open-weights coding fallback when closed models are down or rate-limited.
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Claude Gains Background Computer Use in Cowork and Claude Code

Claude can now use a computer in the background inside Claude Cowork and Claude Code—clicking, typing, and opening apps while the user works on something else. The beta is available on Pro and Max plans in the macOS desktop app, enabled under Settings → General → Computer use.

Key Takeaways

  • Coding agents move from chat-in-the-loop to async desktop operators
  • Background computer use is shared across Claude Cowork and Claude Code
  • macOS desktop beta on Pro/Max, with an official safety guide for computer use
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Qwen3.8-Max-0902 Hits #1 on Code Arena With 2.4T Params and 1M Context

Alibaba’s Qwen released Qwen3.8-Max-0902, a 2.4T-parameter, 1M-context model further post-trained for coding and cowork. It debuted at #1 on Code Arena: WebDev with 1,691 points, edging Claude Opus 5, while sitting on the Pareto frontier at a blended per million tokens.

Key Takeaways

  • 2.4T parameters and 1M-token context, post-trained for coding, cowork, research, and long-horizon workflows
  • #1 on Code Arena: WebDev at 1,691 pts, above Claude Opus 5 (1,688) and Kimi K3 (1,674)
  • Priced at input / output per 1M tokens, now live on QwenCloud
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Qwen ships Qwen3.8-Max-0902: 2.4T params, 1M context, stronger coding post-training

Alibaba Qwen upgraded Qwen3.8-Max to Qwen3.8-Max-0902: about 2.4T parameters, 1M context, and further post-training on Coding and Cowork for complex enterprise, research, and long-horizon workflows. QwenCloud API pricing is $2 input / $6 output per 1M tokens, with explicit/implicit cache hits at $0.17 / $0.25.

Key Takeaways

  • Qwen3.8-Max-0902 is live on the QwenCloud API for coding and cowork-style long-horizon work.
  • About 2.4T parameters with 1M context, with extra Coding/Cowork post-training versus prior Max.
  • List price is $2/$6 per 1M tokens; cache hits drop to $0.17–$0.25.
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