AI Model Profile
Qwen3-235B-A22B
Qwen3-235B-A22B is a Qwen3 mixture-of-experts model described in Qwen release materials as open-weight and useful across coding, math, general capabilities, and agent workflows.
Before you buy
Best for: Candidate for open-weight, local/private, and research evaluations where teams can manage deployment complexity.
Price: C$0 weight download; license restrictions and compute costs apply
Included: Qwen3-235B-A22B is a Qwen3 mixture-of-experts model described in Qwen release materials as open-weight and useful across coding, math, general capabilities, and agent workflows.
Main limits: Qwen's Qwen3 release post describes Qwen3 open-weight models under Apache 2.0; verify exact model-card terms before redistribution. Official Qwen materials point to deployment frameworks and local tools; actual hardware depends on model variant, quantization, and serving stack. Deployment cost, latency, and hardware needs vary widely by serving stack and quantization.
What Kingy showed: Related coverage: Qwen3-235B-A22B-Instruct-2507 Review: How Alibaba's Latest LLM Achieves 95% on ZebraLogic and Supports 119 Languages. This review does not treat that article as a new test of this exact model, plan or current release.
Buying details checked 2026-10-23 with region and currency stated above. Historical demonstrations and the broader fact ledger keep their own dates.
See the demonstration and disclosure · Compare these workflows
- Family
- Qwen3
- Release date
- Unknown
- Status
- Current
- Context window
- 128K tokens
- Output limit
- Unknown
- API
- Unknown
- Open weights
- yes
- Local/self-hosted
- yes
- Pricing
- Open weights available; hosting, inference, and API costs depend on deployment platform or third-party provider.
- Evidence state
- Recheck due
Benchmark Caveat
Provider documentation and provider-published capability notes are directional, not universal rankings. Real results depend on prompts, tools, latency targets, pricing tier, safety filters, context length, and workload mix.
Best for
Candidate for open-weight, local/private, and research evaluations where teams can manage deployment complexity.
Skip if
Skip if your team needs independently benchmarked performance claims or contractual guarantees not present in the official provider documentation.
Strengths
Official Qwen materials describe open weights, multiple deployment paths, hybrid thinking modes, and large context.
Weaknesses
Deployment cost, latency, and hardware needs vary widely by serving stack and quantization.
Agent suitability
Candidate for agent experiments because Qwen materials describe tool and agent capabilities.
Kingy AI take
Use this profile as a source-backed reference point, not a ranking. Re-check official provider docs before making production or budget decisions.
Kingy AI Product Facts
Qwen3-235B-A22B
Current statusUnknown
- Company
- Not yet reviewed
- Primary job
- Not yet reviewed
- Audience
- Not yet reviewed
- Evidence
- Source-backed; coverage expanding
- Latest source check
- October 23, 2026
See all tracked product factsPricing, platforms, dependencies, data claims, regions, and timeline
Sources and checks
- Coverage
- 1 of 88 tracked fields currently verified
- Sources
- 1
Source-check dates apply to the tracked facts. Editorial updates elsewhere on this page may have a different date.
Plans and pricing units
Not yet structured in this Kingy record.
Where it runs
- Availability
- Not yet reviewed
Stack and integrations
- Model / provider dependencies
- Not yet reviewed
- Integrations
- Not yet reviewed
Data and regions
- Vendor data-use claim
- Not yet reviewed
- Vendor retention claim
- Not yet reviewed
- Regions
- Not yet reviewed
Launch and latest material update
- Launch
- Not yet reviewed
- Latest material update
- Not yet reviewed
Full Model Notes
Who should consider it
Candidate for open-weight, local/private, and research evaluations where teams can manage deployment complexity. Qwen3-235B-A22B is a Qwen3 mixture-of-experts model described in Qwen release materials as open-weight and useful across coding, math, general capabilities, and agent workflows.
Plan, price and billing scope
C$0 weight download; license restrictions and compute costs apply. Qwen3-235B-A22B is a Qwen3 mixture-of-experts model described in Qwen release materials as open-weight and useful across coding, math, general capabilities, and agent workflows. Prices use the currency and billing term stated here. Where a numeric rate, region or current entitlement could not be verified, it remains explicit; no checkout was completed.
Limits that affect the decision
Qwen's Qwen3 release post describes Qwen3 open-weight models under Apache 2.0; verify exact model-card terms before redistribution. Official Qwen materials point to deployment frameworks and local tools; actual hardware depends on model variant, quantization, and serving stack. Deployment cost, latency, and hardware needs vary widely by serving stack and quantization.
What the existing evidence shows
Related coverage: Qwen3-235B-A22B-Instruct-2507 Review: How Alibaba's Latest LLM Achieves 95% on ZebraLogic and Supports 119 Languages. This review does not treat that article as a new test of this exact model, plan or current release. Product coverage; original publication date and evidence scope retained. Read the related article.
Sources and buying-review date
Buying review completed October 23, 2026. This is a source-based buying assessment. No paid product test, new generation, checkout or performance benchmark was performed. Vendor descriptions and historical examples remain distinct from independently measured results. The date does not renew the broader canonical fact ledger.
Check the official offer · Compare related options
Earlier profile, sources and dates
This older record retains its original scope. Current buying qualifications above take precedence where terms have changed.
Qwen3-235B-A22B is a flagship Qwen3 mixture-of-experts model described in Qwen release materials as open-weight and useful across coding, math, general capabilities, and agent workflows.
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Coding notes
Official Qwen materials describe coding capability in the Qwen3 release.
Reasoning notes
Qwen materials describe thinking and non-thinking modes for task-specific reasoning control.
Creative notes
Primarily text-focused in this profile; not a media-generation model.
Research notes
Candidate for open-weight research, local deployment tests, and long-context experiments.
License notes
Qwen's Qwen3 release post describes Qwen3 open-weight models under Apache 2.0; verify exact model-card terms before redistribution.
Hardware requirements
Official Qwen materials point to deployment frameworks and local tools; actual hardware depends on model variant, quantization, and serving stack.
Official Model Links
Model Intelligence Research Map
Use these internal paths to move from this model profile into provider pages, static comparison pages, related Kingy records, and the broader AI launch graph. These are research paths, not rankings.