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ModelActiveClosed / proprietaryIdentity probable

qwen-turbo

Alibaba Groupfamily · Qwen

Open in Graph
data quality63

Updated 6 h ago · first seen 11 Sept 2026

model_01M29A5C36ES7GA4HYDP26HXNK

Overview

Identity

Canonical model
Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
Official checkpoints
None recorded — closed weightsofficial_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
Artifacts
None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
Provider deployments
1
API aliases
qwen-turboIdentifiers under which providers and evaluators refer to this model.
Folded evaluation variants
0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.

Openness

Closed / proprietary— weights not available; 7 dimensions unknown.

Weights are not available; the model is reachable only through an API or a product.

  • Weights

    No

  • Inference code

    —

  • Training code

    —

  • Training data

    —

  • Dataset

    —

  • Commercial use

    —

  • Redistribution

    —

  • Derivatives

    —

dimensions marked null are unknown, not false

Key facts

Release date

Source:Qwen — official blogT2observed 16 h agomediumLLM-extracted

Status

Source:Qwen — official blogT2observed 16 h agomediumLLM-extracted

Version

Source:Qwen — official blogT2observed 16 h agomediumLLM-extracted

Official page
qwen.ai

Source:Qwen — official blogT2observed 16 h agomediumLLM-extracted

Architecture

Architecture

Source:Qwen — official blogT2observed 16 h agomediumLLM-extracted

Capabilities

Modalities

Modalities
text
Input
text
Output
text

Capabilities

  • Tool calling

    Yes

    Qwen — official blog · T2

  • Structured output

    Yes

    Qwen — official blog · T2

  • Reasoning

    No

    Artificial Analysis · T2

  • Vision

    Unavailable

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

Context window

Source:Artificial AnalysisT2observed 14 h agomedium

Languages

Source:Qwen — official blogT2observed 16 h agomediumLLM-extracted

Benchmarks6

Compare with another model →

Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric

Benchmark results grouped by comparability group
Benchmark · groupBest scoreTrustConfigurationResultsvs leaderEvaluatedSource
Artificial Analysis Intelligence Indexcomposite · indexIndependentreasoningoffversion4.3conditions differ across rows → partially comparable2−46.9vs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
Humanity's Last Examknowledge · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoningoffconditions differ across rows → partially comparable2−55.0 ptvs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantDiamondreasoningoffconditions differ across rows → partially comparable1non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=GPQA Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantGPQA Diamond1−55.3 ptvs gpt-6-astraobs. 11 Sept 2026artificialanalysis.aiT2

Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 6 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →

Providers & Pricing1

All offers in the price terminal →
Provider deployments, cheapest output first
ProviderContextInput / 1MOutput / 1MStatusObservedSource
Alibaba Cloud Model Studioqwen-turbo-latest1M—active16 h agosince 11 Sept 2026qwenlm.github.ioT2

USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →

Price history

Step lines per provider; amber markers are recorded changes. Click a marker or a row for the evidence behind that price.

Output price · USD / 1M tokens 1 provider

Price history starts with the first observation — no change recorded yet for this side (1 row).

    Input price · USD / 1M tokens 1 provider

    Price history starts with the first observation — no change recorded yet for this side (1 row).

    • Alibaba Cloud Model Studiofirst observed $0.3011 Sept 2026

    Versions & Artifacts0

    Version history

    Status1 change

    11 Sept 2026→11 Sept 2026

    Context windowfirst observation only

    11 Sept 2026current

    Opennessfirst observation only

    11 Sept 2026current

    Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.

    Artifacts 0

    No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.

    Timeline3

    Full timeline →

    Change history

    Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.
    1 claims · 1 propertiesShow all properties

    Aa opennessaa_openness1

    Claim history for Aa openness
    ValueValid from → toStatusSourceConfidenceExtractor
    proprietary → currentcurrentArtificial AnalysisT2mediumdeterministic

    Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

    Provenance

    Attributed facts

    20

    Source tiers

    T220

    Freshest observation

    6 h ago

    Conflicts

    None

    Source documents 3

    Source documents
    SourceDocumentTypeTierLast observedSnapshots
    Qwen — official blogqwenlm.github.io/blog/qwen2.5 newsT1· Official16 h ago1
    Qwen — official blogqwenlm.github.io/blog/qwen2.5-turbo newsT1· Official16 h ago1
    Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary6 h ago2

    Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

    Data quality (63/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →