Matrix overall
60.2
AVG 48.9 across matrix cells
ActiveModel portfolio
Qwen-7B
Tap a star to rate
Alibaba · Open
Cadle Score
106.6
#58 in index
Benchmark average
48.9
Not enough benchmark results yet
Pricing
$0.20
$0.20 / 1M out · 150.5 pts/$
MODEL MATRIX · TRUTH CENTER CELLS
Overall
60.2
Intelligence
60.2
Coding
—
Reasoning
67.1
Language
47.3
Knowledge
41.3
Agentic
—
MMLU
26.7
GPQA
—
Math
51.7
LiveCodeBench
—
HumanEval
—
Reason
67.1
ARC-AGI
—
Coverage AVG
48.9
Pillar Coverage:5 / 7 Core Pillars (71%)
Cadle Cap ranks models with within-benchmark percentiles so ARC-AGI ~40 and MMLU ~90 never compete raw. Coverage AVG is an importance-weighted mean of filled expert cells only — blanks are skipped, not zeroed.
ANALYSIS · TRUTH CENTER
Hard benches (GPQA · ARC-AGI · LCB · Agentic) sit left — a mid-40 on ARC-AGI can still be frontier. Broader benches on the right are easier and often higher.
CADLE INSIGHTS
Only measured signals
Benchmark avg
53.2
8 tracked scores
Strongest signal
epoch-eci
Score 106.6
Blended $/1M
$0.40
In $0.20 · Out $0.20
Value index
150.5
Quality ÷ blended $/1M (higher is better)
Intel index
60.2
Matrix AA IQ cell
SPEED · COST · QUALITY
Measured matrix and verified gateway observations only.
- Cadle Score
- 106.6
- Overall (Matrix)
- 60.2
- Cadle Intelligence
- 60.2
- Input $/1M
- $0.20
- Output $/1M
- $0.20
- Value pts/$
- 150.50
DESCRIPTION + DETAILS
PROVIDER
Alibaba
STATUS
ACTIVE
COMMUNITY REVIEWS
Community Reviews & Field Notes
Verified EngineersReal operator evaluations, prompt robustness observations, and deployment notes for Qwen-7B.
4.5(2)
Leave a Field Observation
Rating:5 - Frontier benchmark
Role:
Tag topic:
Reviews are publicly visible to the engineering community.
Inference OperatorProduction Deployer Verified
Nov 1, 2026
Tested Qwen-7B on high-concurrency tool loops. Token generation remains consistent under sustained context load, with minimal prompt drift on complex JSON schemas.
Autonomous Agent LeadEval Maintainer Verified
Oct 28, 2026
Evaluated Qwen-7B on multi-turn code synthesis. Code reasoning and diff application succeed on ~88% of test suites. Best paired with strict system prompt guardrails.
MODEL COMPARISON
| Metric | |
|---|---|
| Provider | Alibaba |
| Release | |
| Input / 1M | $0.20 |
| Output / 1M | $0.20 |
| Context | No data yet |
| Cadle Cap | 107 |
| Cap board | Cadle Language Cap 107 |
| training-compute-flops | 23.0 |
| piqa | 55.8 |
| mmlu | 26.7 |
| lambada | 67.9 |
| gsm8k | 51.7 |
| bbh | 26.7 |
| arc-ai2 | 67.1 |
| epoch-eci | 106.6 |
DATA PROVENANCE
Scores may use different scales — check the Benchmarks tab for source links.
- Supabase models
- Cadle public observations
SOURCE TRACKING
Evidence linked to this model — listing, hub, benchmarks, or live gateway prices.
API
Alibaba listing
MEASURED CELLS
Same Truth Center numbers as the datasheet above. Accuracy, reliability, safety, and cost scores are not invented.
Overall60.2
AA IQ60.2
MMLU26.7
Math51.7