Updated 1 h ago · first seen 11 Sept 2026
model_01M29A5CA6Y841K30N0EXZMRWK
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 recordedofficial_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
- None recorded
- API aliases
- qwen3-omni-30b-a3b-instructqwen3-omni-30b-a3b-reasoningIdentifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 1Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.
Openness
Open weights— weights downloadable; 7 dimensions unknown.
Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.
Weights
Yes
Inference code
—
Training code
—
Training data
—
Dataset
—
Commercial use
—
Redistribution
—
Derivatives
—
dimensions marked null are unknown, not false
Capabilities
Modalities
Modalities unavailable.
Capabilities
Tool calling
Unavailable
Structured output
Unavailable
Reasoning
No
Artificial Analysis · T2
Vision
Unavailable
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:Artificial AnalysisT2observed 10 h agomedium
Benchmarks28
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
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. 28 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 →
Versions & Artifacts0
Version history
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.
Timeline14
Full timeline →qwen3-omni-30b-a3b-instruct scores 1.52% on Terminal-Bench
artificial_analysisqwen3-omni-30b-a3b-instruct scores 16.37% on τ²-bench
artificial_analysisqwen3-omni-30b-a3b-instruct scores 55.49% on MMMU-Pro
artificial_analysisqwen3-omni-30b-a3b-instruct scores 31.16% on IFBench
artificial_analysisqwen3-omni-30b-a3b-instruct scores 4.63% on Humanity's Last Exam
artificial_analysisqwen3-omni-30b-a3b-instruct scores 62.02% on GPQA Diamond
artificial_analysisqwen3-omni-30b-a3b-instruct scores 6.01 on Artificial Analysis Intelligence Index
artificial_analysisqwen3-omni-30b-a3b-instruct scores 3.79% on Terminal-Bench
artificial_analysisqwen3-omni-30b-a3b-instruct scores 21.35% on τ²-bench
artificial_analysisqwen3-omni-30b-a3b-instruct scores 60.23% on MMMU-Pro
artificial_analysisqwen3-omni-30b-a3b-instruct scores 43.4% on IFBench
artificial_analysisqwen3-omni-30b-a3b-instruct scores 7.46% on Humanity's Last Exam
artificial_analysisqwen3-omni-30b-a3b-instruct scores 72.63% on GPQA Diamond
artificial_analysisqwen3-omni-30b-a3b-instruct scores 7.76 on Artificial Analysis Intelligence Index
artificial_analysis
Change history
Reasoningreasoning2
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
8
Source tiers
T28
Freshest observation
1 h ago
Conflicts
None
Source documents 1
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (48/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →