Qwen Code Signals
What engineering leaders and their teams report about Qwen Code, with every finding tied to its evidence.
Read the findingsWhat the evidence says
Practitioner sentiment, all practitioners
−50 Strong negative from 42 sources that take a side
How this figure is madeStrong negative overall signal, net 50 points negative
Each from a different author and a different discussion. Use a task pilot to measure accepted work and review time.
- Analyzed
- 53 total sources
- Top praise
- MCP & Editor Integrations (5 of 6 sources) See praise evidence
- Top concern
- Bugs & Stalled Tasks (16 of 16 sources) See concern evidence
Oct 2025 to Oct 2026.
47 sources from practitioners, by month and sentiment.
Across 47 sources, 8 are positive, 5 mixed, and 29 negative. Bugs and stalled tasks are raised in 16 sources, and MCP and editor integrations draw praise in 5.
Positive, mixed and negative sources
The score counts each source once, as the split does. See How the numbers work.
See the evidenceBelow: 2 praise themes and 2 concerns.
Findings
Counted for All practitioners, from 47 sources. Change group
What practitioners praise
Every capability practitioners describe positively, ranked by how many sources say so. Open one to read who said it.
MCP & Editor Integrations5 of 6 sources on it praise itMCP servers, IDE plugins, and Claude Code plugins connect Qwen Code to a team's tools.
Counted for All practitioners.
Positive, 5
Positive
Mario Taddeucci, collaborator on caipora-labs' Curupira
Provider: add Qwen Code CLI adapterGitHub pull request
Adds a built-in Qwen Code adapter with native model, approval-mode, turn limit, resume and stream-JSON handling to Curupira.
Positive
Idris Olubisi, owner of agent-lookout
Qwen Code adapterGitHub issue
Qwen Code stores running sessions and transcripts in the same shape as Claude Code, so agent-lookout's existing adapter pattern reads it with no setup.
Positive
tenequm, owner of pond
adapter wanted: Qwen CodeGitHub issue
Qwen Code's session storage follows Claude Code's JSONL model and replaces Gemini CLI's schema. It is append-only with one file per session, and local-model sessions are captured too.
Mixed
jcleira, member of Partio
Add Qwen Code (Alibaba) coding agent integrationGitHub issue
Users running Qwen Code in Partio-enabled repositories get no session capture today; its per-session JSONL history matches Claude Code's layout, so an adapter follows the existing pattern.
Positive
konart, Hacker News commenter speaking for their company
Comment on: MCP is dead?Hacker News comment
The commenter's company runs Qwen Code as its base agent with MCP servers for Jira, Confluence, GitLab, an in-house logs and metrics platform, and Mattermost.
Mixed or negative, 1
Negative
imrehg, Senior Machine Learning Engineer at Faculty AI
MCP server never successfully get tool and resource listingGitHub issue
Fastmail's MCP server authenticated but never listed its tools in Qwen Code; the same server works in LM Studio and Claude Code.
Harness for Local Models5 of 9 sources on it praise itQwen Code runs against local models served through Ollama, vLLM, LM Studio, or llama.cpp.
Counted for All practitioners.
Positive, 5
Positive
jonsoft, Hacker News commenter
Comment on: Why isn't the industry freaking out about DeepSeek 4.1 Flash?Hacker News comment
Built a 3D web game in two days with Qwen Code as the agent on a local Qwen 3.8 Flash Next model.
Mixed
aeltawela, owner of an Ollama fork
launch: align Qwen Code context with OllamaGitHub pull request
Makes Ollama's launcher write the local model's real context to Qwen Code's provider settings; a real qwen3.8:27b-mlx launch reported a 262,144-token context in both places.
Positive
tenequm, owner of pond
adapter wanted: Qwen CodeGitHub issue
Qwen Code's session storage follows Claude Code's JSONL model and replaces Gemini CLI's schema. It is append-only with one file per session, and local-model sessions are captured too.
Positive
Total_Activity_7550, r/LocalLLaMA member
My website development flowReddit post
Uses Qwen Code on a local Qwen3.5-27B on two RTX 3090s for private projects.
Mixed
FPham, r/LocalLLaMA member
My real-world Qwen3-code-next local coding test. So, Is it the next big thing?Reddit post
Wired a local Qwen3-Coder-Next to the Qwen Code CLI; first tasks went well before a larger rewrite tested its limits.
Mixed or negative, 4
Negative
tonydiep, consultant at Tony Diep Consulting
400 Failed to initialize samplers in 0.22.3GitHub issue
After an update to 0.22.3, his local Qwen models on llama-server failed with HTTP 400 while Pi and OpenCode kept working; the previous version had worked.
Negative
abdoulayesow, founder of friasoft
User message dropped from follow-up request after tool call, breaking all tool use on OllamaGitHub issue
Against Ollama, every prompt that needed a tool failed after the first tool call, with HTTP 500 errors or a generic greeting, while prompts that needed no tool worked.
Mixed
Takafumi Endo, CEO of ROUTE06
Why My Local Coding Agent Could Act but Couldn't FinishPersonal blog post, DEV Community
Over three sessions with local models, Qwen Code built a video-site UI, but in the last session 232 of 240 tool calls went through and the bug was still there at the end. He calls the write-up a log, since nothing in it was controlled.
Negative
Kim Se-Won, GitHub user
It seems Qwen code does not use 'no_proxy' environment variable.GitHub issue
The company's in-house Qwen3 service sits outside the corporate proxy, but Qwen Code 0.0.14 ignored no_proxy and failed with connection errors.
GILD's fact checks, which don't count as sources
Checked Oct 28, 2026.The README states support for OpenAI, Anthropic, Gemini, and Qwen APIs and any third-party provider or local model through Ollama or vLLM, switchable at runtime. Qwen Code README
Open them in the record
What concerns them
Every concern practitioners raise, most raised first.
Bugs & Stalled TasksAll 16 sources on it raise it as a concernTasks that stop silently, failed tool calls, lost work, and limits that block a deployment.
Counted for All practitioners.
Negative
zhuanyi, University of Waterloo
bug(core): a native api.anthropic.com session 400s forever when a persisted thinking part lost its signatureGitHub issue
A session on Anthropic's own endpoint failed with the same HTTP 400 on every retry, because each retry re-sends the same history; only a new session or another model got past it.
Negative
Suaroman, formerly an SRE at Microsoft
Headless -p (default/Auto approval): managed auto-memory can never saveGitHub issue
In headless runs the memory agents made 19 write_file or edit calls and all 19 failed, so the project's memory file stayed empty.
Negative
p-poppe, Simply.IN
Active Goal holds ordinary user input until the Goal leaves active stateGitHub issue
Messages typed during an active Goal stayed queued until the Goal ended, so on long Goals they appear to hang for many turns.
Negative
princelundgren, GitHub user
On Qwen Code 0.26.1 with an Anthropic key, side queries that request JSON fail with HTTP 400 on Claude Sonnet 5.5 and Opus 5.5 because they force a tool choice those models reject.
Negative
waynegault, hobby developer at NHS Grampian
bug(vscode): the companion keeps every conversation in one globalState keyGitHub issue
The VS Code companion stored 1,006 conversations in one 75 MB state value, with no retention or eviction, and VS Code warned about it.
Negative
alekskos, MWS
memory.agentMaxTurns ignored by user-scoped memory dream (hardcoded maxTurns = 8)GitHub issue
With agentMaxTurns set to 60, the user-scope memory run still stopped at 8 turns.
Negative
ojhughes, Senior Software Engineer at Neo4j
Fireworks: Qwen3 tool-call continuation fails with 400 due to mirrored messages[].reasoningGitHub issue
On Qwen Code 0.23.3 with Qwen 3.8 Max on Fireworks, the first tool call works, then every request that continues after a tool result fails with HTTP 400.
Negative
tonydiep, consultant at Tony Diep Consulting
400 Failed to initialize samplers in 0.22.3GitHub issue
After an update to 0.22.3, his local Qwen models on llama-server failed with HTTP 400 while Pi and OpenCode kept working; the previous version had worked.
Negative
abdoulayesow, founder of friasoft
User message dropped from follow-up request after tool call, breaking all tool use on OllamaGitHub issue
Against Ollama, every prompt that needed a tool failed after the first tool call, with HTTP 500 errors or a generic greeting, while prompts that needed no tool worked.
Negative
ricyoung, Senior AI/NLP Scientist at Optum
OTEL_METRICS_EXPORTER=otlp in environment silently disables metrics export while traces keep flowingGitHub issue
With a common OpenTelemetry environment setting, Qwen Code sent traces but no metrics, and Prometheus held no qwen_code series across 30 days of retention.
Negative
orangewk, game developer
[Desktop 0.1.0 / Windows] Bundled runtime crashes on startupGitHub issue
Qwen Code Desktop 0.1.0 failed to start on Windows when he opened a workspace, because its bundled runtime crashed.
Negative
imrehg, Senior Machine Learning Engineer at Faculty AI
MCP server never successfully get tool and resource listingGitHub issue
Fastmail's MCP server authenticated but never listed its tools in Qwen Code; the same server works in LM Studio and Claude Code.
Negative
docheinestages, Hacker News commenter
Comment on: Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7kHacker News comment
Running Qwen 3.6 27B locally at about 10 tokens per second, file writes often fail even in Qwen Code.
Negative
stuaxo, Hacker News commenter
Comment on: Local AI needs to be the normHacker News comment
Lost work once with hosted Qwen Code when it got confused inside a devcontainer.
Negative
Althar93, r/LocalLLaMA member
With a local model through llama-server, Qwen Code acknowledges tasks and then silently stops, needing constant nudging.
Negative
Kim Se-Won, GitHub user
It seems Qwen code does not use 'no_proxy' environment variable.GitHub issue
The company's in-house Qwen3 service sits outside the corporate proxy, but Qwen Code 0.0.14 ignored no_proxy and failed with connection errors.
Context & Cache Use5 of 6 sources on it raise it as a concernLarge system prompts, subagent context, and cache invalidation that inflate tokens and wait time.
Counted for All practitioners.
Raised as a concern, 5
Negative
Iftekhar Ahmed, Associate Professor of Informatics at UC Irvine, co-author
Hidden in Plain Sight: an Empirical Study about The Instruction Stacks of Coding AgentsResearch paper, arXiv
Capturing each agent's first model request, the study found Qwen Code's the largest of five agents at 124,873 characters, most of it tool definitions.
Negative
Lancelotbronner, GitHub user
Subagents start with a huge amount of context and I don't know where it comes fromGitHub issue
A parent session at 42,000 tokens launches subagents whose prompt the inference engine reports at 105,000 tokens, far above the 1,000-token subagent prompt.
Negative
yanyukang2003-ux, GitHub user
After automatic compaction mid tool loop, Qwen Code counts the pending tool result twice and pads the estimate, so the next turn stops or is sent with one output token.
Negative
edwardyoon, Apache Software Foundation member at Samsung Electronics
a true "disable auto-compaction" switchGitHub issue
Auto-compaction always fired at 85% of the context whatever threshold he set, so long sessions on his own backend were summarized whether he wanted it or not.
Negative
Academic-Tea6729, r/LocalLLaMA member
Is there a coding harness that will not invalidate the entire context cache at each prompt?Reddit post
Cline and the Qwen Code VS Code add-on invalidate about 100,000 tokens of context cache on small follow-up requests, costing about 40 seconds each time.
Discussed without concern, 1
Mixed
aeltawela, owner of an Ollama fork
launch: align Qwen Code context with OllamaGitHub pull request
Makes Ollama's launcher write the local model's real context to Qwen Code's provider settings; a real qwen3.8:27b-mlx launch reported a 262,144-token context in both places.
Where the evidence agrees
Statements this group's sources agree on, then the ones close to agreement.
For all practitioners, no statement reaches 5 sources from 3 authors.
Where it disagrees
Questions the sources split on, with the count on each side.
For all practitioners, no question reaches 5 sources from 3 authors, with 2 on each side.
The evidence
Whose experience this is
The three groups, then every practitioner by the context they work in, and how emphasis changes with scale.
Three groups drawn from the same sources. Choose a group to select whose experience counts. Within that group, each author counts once in the practitioner sentiment, with their latest view. Signals open on All practitioners. Leaders and teams have 6 accounts; GILD prints their sentiment from 20.
Engineering leaders and teams
9 sources. These accounts come from teams and companies wiring Qwen Code into their tools, in-house models, and shared servers, and from two university research groups.
Individual builders
38 sources. These accounts focus on running Qwen Code against local models and on the paid Qwen routes after the free tier ended.
All practitioners
47 sources. This gives the broadest read, but combines hobby setups on local hardware with company rollouts on Alibaba Cloud.
47 sources from practitioners, by the context they work in. Filled rows count for this group.
- Individual practitionerSolo developers and independent builders38 sources, counted here
Emphasizes Local models, stalled tasks, and context use
- Very small team2 to 10 engineers1 sources, counted here
Emphasizes Sign-in on remote servers
- Professional team11 to 50 engineers, or a named company's team8 sources, counted here
Emphasizes Companies building Qwen Code into their tools, in-house models behind a proxy, and MCP servers for company tools
- Technical leadershipLeaders setting adoption across teamsNo sources from this setting yet
- Organization-wideEnterprise or company-wide rolloutNo sources from this setting yet
What changes with scale. Individual builders use Qwen Code as a harness for local Qwen models and raise stalled tasks and context use. Teams that wire it into company systems hit proxy and remote sign-in problems before they reach production.
Where the sources come from
Where this group's sources were published.
Counted for All practitioners, from 47 sources. Change group
53 sources for this group, 6 of them documentation
- Developer Communities43, 81% of 53 sources
- Product Documentation6, 11% of 53 sources
- Engineering Blogs & Reviews4, 8% of 53 sources
Earlier evidence remains when it still applies. Records tied to the ended free tier or fixed bugs carry Needs a recheck or are left out.
See sources by originThe record
Who each source is, how it knows, whether it still applies and what it counts toward.
Newest first, on its own page. Every count above opens its sources there.
Read all 53 sourcesAbout this read
What changed, and how we count
What changed
- Oct 31, 2026: 18 records added from a search for practitioners whose role or employer a page states; a second model checked every record against its stored source and accepted 18 of 22. One, a February 2026 review made on the free tier, is kept as history. 47 remain.
- Oct 30, 2026: a second model checked every record against its stored source. 26 of the 55 records failed and were removed: 10 whose summaries claimed more than their source says, 8 that state no outcome a buyer acts on, 5 written by agents, and 1 each about another product, from a competing harness's benchmark, and misdated. One more keeps its place without the employer its author's profile gives, as history, since its bug was later fixed. 29 remain.
- Oct 28, 2026: first edition, built from the GitHub, Hacker News, Reddit, and X accounts GILD's research missions stored on October 28, 2026.
- Every account links to its public source and names its author and publication date.
- A finding shows only when at least 5 sources from 3 different authors discuss it. A disagreement also requires at least 2 sources on each side.
- Counts practitioners who describe their own use or evaluation of Qwen Code; accounts about Qwen models in other harnesses are excluded.
- Checks the plan, limit, auth, telemetry, and data findings against the Qwen Code documentation and Alibaba Cloud's Coding Plan and privacy pages on the review date.
Method
A running review of what engineering teams report about Qwen Code, from individual builders to professional teams. Each finding links to its sources, and each conflict shows both sides.
Counts cover only the sources GILD reviewed.
Who counts
- Engineering leaders and teams
- Very small team, Professional team, Technical leadership, Organization-wide
- Individual builders
- Individual practitioner
- All practitioners
- Everyone in the leaders and teams and individual builders groups
Choose a group to select whose experience counts. Within that group, each author counts once in the practitioner sentiment, with their latest view. GILD files each source in a group from how the account describes its author. A role or employer marked self-described is what the source states about themselves. Documentation checks facts for every group and never counts toward sentiment.
How the numbers work
- Overall signal. Positive votes minus negative ones, per 100 votes from the sources that take a side. Each author counts once, with their latest view, whoever they are and wherever they posted. The older weighted reading, where accounts GILD matched to a named person count three times when GILD lists the author among engineering leaders and twice otherwise, is shown beside it as a second view. Where an author wrote more than one source, the line beside the split gives the votes, one per author, so the score follows from it. When one author's sources from the same day disagree, that author counts as mixed, and a half point rounds away from zero. Sources with no opinion are listed and not counted. Strong positive is +50 or higher, positive +20 to +49, mixed −19 to +19, negative −20 to −49, strong negative −50 or lower.
- Weighted reading, second view. Counted the older way, where an account GILD matched to a named person counts two or three times, all practitioners read −51 strong negative (method sentiment/S1). GILD printed that number as "GILD score" until October 29, 2026; most of those matches rest on a name or a self-described role.
- Unscored. A group gets a score only with 20 sources from 15 authors. Below that, one source moves the score about 5 points, so the read says "Unscored until 20 sources from 15 authors" and shows its counts.
- Independence. A source whose author works for the vendor, for one of its partners or programs, or for a competitor, and a page the vendor published or ran, is listed with that tie and counts toward nothing. One author counts on at most two records per product. The line under the score says how many authors and how many separate discussions the counted sources come from: comments in one thread are one discussion.
- Praise and concerns. How many of the sources that discuss a theme praise it or raise it.
- Consensus. A statement joins when 20% of the group's sources support it and fewer contradict it. Contradicting sources are counted separately. Below that line a statement shows as building. At 40% or more it reads Strong agreement; below, Recurring point.
- Disagreements. The count on each side. GILD names no winner and gives no share of all users.
- Minimum evidence. A finding needs 5 sources from 3 authors; a disagreement also needs 2 on each side. Smaller counts stay in the table below, marked under the minimum.
Labels on a source
A source's date and whether it still applies are separate: a recent post can describe an old version, and an old one can still hold.
- Documented
- Stated in official documentation.
- Reported
- A practitioner's account of their own use.
- Measured
- Backed by the source's own measurements, such as a comparative test or tracked team metrics.
- GILD analysis
- GILD's check of a claim against official documentation.
- Current
- Describes the product as it is now.
- Still applicable
- Older, and the behavior or lesson still holds.
- Needs a recheck
- May depend on a plan, version or setting that changed since it was written. It keeps counting until GILD rechecks it, since the rest of the account usually holds, and its card says so.
- Out of date
- No longer accurate. Kept in the record; counts toward nothing current.
Flagged for a recheck, of the sources that take a side: leaders and teams 1 of 6, individual builders 0 of 36, all practitioners 1 of 42.
Limits
- These figures describe reviewed sources; they do not represent all Qwen Code users. GitHub issues and pull requests supply 29 of the 47 practitioner sources, most from developers and companies wiring Qwen Code into their own tools, and tilt toward problems, so a bug report counts as negative unless its author also states what works. Reddit's r/LocalLLaMA supplies 7, which tilts them toward developers running Qwen Code on their own hardware. Two arXiv studies by university research groups measured Qwen Code directly. The Qwen team's own posts and benchmark claims are kept out of the count. Five sources count toward nothing. Four of them are pull requests from AgentScope's AgentTeams, a project tied to Alibaba Cloud, or accounts kept as history, and one study takes no position.
- Sources cover Qwen Code from version 0.0.14 in October 2025 to 0.26.1 in October 2026, across the end of the free Qwen OAuth tier on April 15, 2026. One October 2025 proxy bug carries Needs a recheck, and a March 2026 IntelliJ plugin bug, later fixed, and a February 2026 review made on the free tier are kept as history.
Every count, and the sources behind it
12 findings for 3 groups
Each row opens its sources for the group you are reading.
| Finding | Engineering leaders and teams | Individual builders | All practitioners | Sources |
|---|---|---|---|---|
| Current readCurrent sentiment | 2 positive, 1 mixed, 3 negative | 6 positive, 4 mixed, 26 negative | 8 positive, 5 mixed, 29 negative | Sources |
| PraiseHarness for Local Models | 0 of 1 positive (under the minimum) | 5 of 8 positive | 5 of 9 positive | Sources |
| PraiseAny Model, Any Endpoint | 0 of 0 positive (under the minimum) | 1 of 2 positive (under the minimum) | 1 of 2 positive (under the minimum) | Sources |
| PraiseMCP & Editor Integrations | 3 of 3 positive (under the minimum) | 2 of 3 positive (under the minimum) | 5 of 6 positive | Sources |
| PraiseOpen Source & Forkability | 0 of 0 positive (under the minimum) | 1 of 1 positive (under the minimum) | 1 of 1 positive (under the minimum) | Sources |
| ConcernBugs & Stalled Tasks | 1 of 1 raise it (under the minimum) | 15 of 15 raise it | 16 of 16 raise it | Sources |
| ConcernQuality Against Frontier Agents | 0 of 0 raise it (under the minimum) | 3 of 3 raise it (under the minimum) | 3 of 3 raise it (under the minimum) | Sources |
| ConcernContext & Cache Use | 1 of 1 raise it (under the minimum) | 4 of 5 raise it | 5 of 6 raise it | Sources |
| ConcernSign-In & Auth Failures | 1 of 1 raise it (under the minimum) | 2 of 2 raise it (under the minimum) | 3 of 3 raise it (under the minimum) | Sources |
| ConcernFree Tier End & Plan Pricing | 0 of 0 raise it (under the minimum) | 2 of 2 raise it (under the minimum) | 2 of 2 raise it (under the minimum) | Sources |
| ConcernTelemetry & Data Use | 0 of 0 raise it (under the minimum) | 2 of 2 raise it (under the minimum) | 2 of 2 raise it (under the minimum) | Sources |
| Current readEvidence mix | 15 sources | 44 sources | 53 sources | Sources |
Fact checks
GILD's checks of claims against official documentation, kept apart from the source counts.
- Harness for Local Models. The README states support for OpenAI, Anthropic, Gemini, and Qwen APIs and any third-party provider or local model through Ollama or vLLM, switchable at runtime. Qwen Code README, checked Oct 28, 2026
- Any Model, Any Endpoint. The authentication guide lists QwenCloud, Alibaba ModelStudio, built-in third-party providers such as DeepSeek, Kimi, and OpenRouter, and custom providers, with /model to switch. Authentication, checked Oct 28, 2026
- Free Tier End & Plan Pricing. The authentication guide states the Qwen OAuth free tier was discontinued on April 15, 2026, and points users to Coding Plan, OpenRouter, Fireworks AI, or another provider. Authentication, checked Oct 28, 2026
- Telemetry & Data Use. The privacy notice states that anonymous usage statistics are enabled by default for every auth method, including your own API key, are sent to an Alibaba Cloud collection endpoint, and can be turned off in settings. Terms of service and privacy notice, checked Oct 28, 2026