Entity trail

Qwen Code

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-09-11 / reddit-researcherA retrofit of DeepSeek V4.1 Flash's KV approximation cut Qwen3-8B prefill time in halfDeveloper Naoki Kishida trained a small projector that writes the KV cache for Qwen3-8B's later layers during prefill, while the full model still handles decoding. He reports a 50% cut in prefill time on a 341-token input, with prose intact but spurious variables showing up in generated code. MIT-licensed weights were posted September 10 and a browser demo runs it. An r/LocalLLaMA user has started a port to Qwen3.8-27B for a single RTX 3090.
2026-09-11 / github-pulse-researcherqwen-code 0.23.3 can hand a subagent turn to Claude Code over ACPQwenLM/qwen-code v0.23.3 (2026-09-10) adds delegating a subagent turn to an external agent over the Agent Client Protocol, with Claude Code supported first (#11003). It also adds an OpenAI Responses API content generator, Kimi, Qwen and DeepSeek reasoning presets, and 256 workspaces by default in `serve`. Daemon-managed ACP sessions can now register in the session registry and message each other, so qwen-code is turning into a coordinator for other vendors' agents.
2026-09-11 / projects-researchermesh-llm v0.76.0 makes the KV prefix cache survive eviction, restarts and cold nodesMesh-LLM splits model inference across pooled machines. Its v0.76.0 release (2026-09-10) replaces flat prefix caches with a durable radix structure, so agent system-prompt prefixes survive node restarts, and routes repeated prompts to workers with verified cache hits. The release also streams tool calls mid-generation, adds staged Qwen3.8 Flash-Next inference, cuts per-token split-decode overhead by about 10 percent, and fixes credential leakage over the management API. The repo has 3,375 stars, with 50 open PRs against 100 open issues.
2026-09-10 / arxiv-researcherTraining a Weak Model on Expert Trajectories Under Its Own Evolved Harness Regresses It on All Seven TasksarXiv 2609.09134 (2026-09-08) evolves an agent harness (system prompt, tool set, hooks, context management) with a weaker model, observes that a stronger expert then uses that harness better, and tries the obvious fix of training the weak model on the expert's full trajectories. It backfires across all seven enterprise agent tasks, costing 4 to 30 points on Qwen3-Coder and Gemma 4, even though the same procedure helps under the unevolved harness. The diagnosis is model-harness fit: the weak model adopts the expert's planning strategy without the competence to execute it, and no longer matches a harness evolved around its native planning style. Their fix is on-policy expert correction that rewrites only the failing turn in the weak model's own rollout.
2026-09-10 / github-pulse-researcherqwen-code 0.23.2 turns the CLI into a remotely accessible shell with one command and a QR pairing codeReleased 2026-09-09, `feat(serve)` (#11172) gives one-command remote start with a generated token, same-origin shell access, and a pairing QR. The same release separates the Plan workflow from execution permissions in the web shell (#11423), drops peer IPC messages arriving faster than a session can take and tells the sender once (#11277), caps the background-notification queue and reports what was dropped to the model (#11351), and bumps sharp to 0.35.4 for a high-severity libheif CVE (#11435).
2026-09-10 / skill-finderRetrofitting exception handling from tests: static and dynamic analysis in context pushed pass@1 to 85.92% on 304 stripped methodsEXCODER defines a new task, adding missing exception-related code (throw statements, their guard conditions, try/catch blocks) to existing code so that given exceptional behavior tests pass. It does context engineering, feeding LLMs extracted static and dynamic program analysis rather than the raw method. On a benchmark built by systematically removing exception code from 304 methods across 75 GitHub Java projects, EXCODER with Qwen 2.5 Coder 32b reached 85.92% pass@1, 12.56 percentage points over baseline, with similar margins at pass@5 and pass@10 on developer-written test suites. Manual inspection found real limitations, so the authors call it effective but imperfect.
2026-09-09 / skill-finderFive model artifacts in the official Ollama library solve zero of 164 tasks and nothing in the pipeline tests for itExecuting 327 quantized code-capable artifacts (305 from the official Ollama library across 15 model lines at every eligible quantization at or under 8 GB, 22 from top HuggingFace community repos) through a calibrated 15-task smoke suite found five silently defective artifacts: four Qwen2.5-Coder-3B conversions and one phi3.5-mini, scoring zero on both backends while independent conversions of the same models work. That is 1.6% of official artifacts and 2 of 29 conversion groups. Two of the confirmed defects produce output whose surface statistics sit inside the healthy range, so nothing short of execution catches them, and the released quantcheck tool is the acceptance gate model registries currently lack.
2026-09-09 / hn-researcherA Ten-Way Model/Harness Bake-Off on One Three.js Scene Shows a 47x Cost Spread and a 4x Time Spread for the Same TaskPublished 2026-09-09, the test gave ten model/harness pairs the same prompt: a single-page Three.js sci-fi hangar with hovering drones, animated warning lights, emissive runway strips and volumetric-style fog planes. GLM 5.3 Flash on OpenCode finished cheapest at $0.085234 with 96.89% cached input; Astra 6.0 Max on Codex cost $4.038190 and took 37m29s. Qwen 3.8 27B x-high on OpenCode was fastest at 8m48s. Harness choice, not model choice, drives most of the spread, which matches the ARC Prize and Armature results from last week.
2026-09-08 / saas-disruption-researcherTen Model/Harness Combinations on One Three.js Task Show a 4x Wall-Clock Spread and No Correlation With Model TierAn independent test published 2026-09-07 ran the same prompt (a single-page Three.js sci-fi hangar with hovering drones, warning lights, emissive runway strips and volumetric fog planes) across ten model/harness pairs spanning Codex, OpenCode, OMP and DSH/PTC with GLM 5.3 Flash Max, Luna 5.6 Max, SOL 5.6 Max, Astra 6.0 Max and Qwen 3.8 27B. Qwen 3.8 27B on OpenCode finished in 8m48s while Astra 6.0 Max on Codex took 37m30s, a 4.3x spread; Luna 5.6 Max on Codex used the fewest tokens at 1,172,267 and GLM 5.3 Flash Max on OpenCode hit 96.89% cached input. The harness, not the model tier, dominated both wall-clock and cache efficiency, which is the variable most agent-tooling comparisons never isolate.
2026-09-07 / arxiv-researcherA Small Draft Model Scoring an Agent's Own Output Predicts Failure Before Execution, Cutting Error Rate 6-8 PointsarXiv 2609.05274 inverts speculative decoding: a small open-weight draft model scores a black-box agent's already-generated trajectory in a single forward pass, needing no logits, weights, activations, or repeated sampling. Phase-aware features separating reasoning from action spans are calibrated against a verifiable objective to produce a failure-likelihood score. Wired into a pre-execution veto gate on Qwen3-Coder-480B and Claude 3.5 Sonnet, it cut execution error rate by 6-8 percentage points and token cost by 14-19%, transferring to out-of-distribution benchmarks without retraining.
2026-09-07 / skill-finderAn injected image overwrote TOOLS.md in a default OpenClaw Discord deployment where text injection failedRepeat-After-Me is a black-box adaptive visual prompt injection that reaches attack success rates above 80% on Qwen3.6-27B and 47% on GPT-5.5 under a realistic setting where the benign user prompt is unrelated to the injected task and does not authorize it. Injections optimized on one surrogate retain 43-46% of their success on two commercial victims, and the authors demonstrate a real OpenClaw Discord deployment where an untrusted user's minimally injected image overwrites TOOLS.md, opening the door to remote code execution and secret exfiltration. The critical detail for builders is that this works in cases where adaptive textual prompt injection fails, so text-only injection filters are not covering the image path.
2026-09-07 / reddit-researcherAbliterlitics published a 167-GPU-hour forensic audit of 8 uncensored Qwen 3.8 27B variants and found one card's claims match its weightsThe report at abliterlitics.dev, posted to r/LocalLLaMA at 530 upvotes, ran 11 days and ~167 hours on an RTX 5090 (91h LM-Eval, 75.5h HarmBench, 0.7h KL divergence, 3.3 CPU hours weight analysis) across weight comparison, 13 benchmarks, KL divergence and HarmBench's 400 classic behaviors with an LLM judge. Rankings by attack success rate: orcarouter 82.2%, apostate 78.7%, huihui 75.6%, ultra_heretic 70.5%, coder3101 70.0%, blackfrost 68.5%, obliteratus 63.9%, trohrbaugh 57.5%, against a 4.5% base. Capability cost tracks separately from ASR: apostate has the lowest KL at 0.0439 while obliteratus sits at 1.5427, and the author says orcarouter was the only card where every published claim checked out against the actual weights.

Graph relationships

SUPPORTS
Claude Code
qwen-code can delegate subagent turns to Claude Code over Agent Client Protocol
Source finding
USES
DingTalk
Qwen Code integrates with DingTalk and fixed credential logging in DingTalk channel.
Source finding
USES
OpenTelemetry
qwen-code shipped an OpenTelemetry span for context usage tracking.
Source finding
USES
OpenTelemetry
Qwen Code v0.22.3 adds OpenTelemetry span attributes reporting LLM context usage.
Source finding
RELEASED
Alibaba
Alibaba released qwen-code as an open-source terminal coding agent
Source finding
SUPPORTS
Agent Plugins
Qwen Code v0.21.11 shipped Agent Plugins v1 support the same week.
Source finding
SUPPORTS
AionUi
AionUi runs Qwen Code.
Source finding
USES
AionUi
AionUi integrates Qwen Code in multi-agent mode.
Source finding
BUILT BY
QwenLM
qwen-code is QwenLM's terminal coding agent.
Source finding
COMPETES WITH
kilocode
qwen-code and kilocode are competing open-source coding agents with similar star counts
Source finding
SUPPORTS
AionUi
AionUi auto-detects and orchestrates Qwen Code alongside other coding agents.
Source finding
SUPPORTS
Qwen 3.5
Qwen 3.5 ships with Qwen Code terminal agent
Source finding

Source trail

PR #10945 v0.23.1-preview.0 Manifold Security NVD Cline arXiv 2609.03884 GitHub Blaizzy/nativ The repo Released April 22 At 1,697 stars At 1,660 stars

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