Benchmark avg
151.7
1 tracked scores
Model portfolio
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Alibaba · Released 2026-08-14 · v2026-08-14 · Open · Context 262K tokens
Language Cap
66
Cadle Language Cap 66 · 20%
Benchmark average
—
Not enough benchmark results yet
Pricing
$0.48
$3.39 / 1M out · 25.9 pts/$
MODEL MATRIX · TRUTH CENTER CELLS
Overall
—
Intelligence
100.0
Coding
—
Agentic
—
MMLU
—
GPQA
—
Math
—
LiveCodeBench
—
HumanEval
—
Reason
—
ARC-AGI
—
Coverage AVG
—
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.
Only measured signals
Benchmark avg
151.7
1 tracked scores
Strongest signal
epoch-eci
Score 151.7
Blended $/1M
$3.86
In $0.48 · Out $3.39
Value index
2.8
Quality ÷ blended $/1M (higher is better)
Context
262K
Provider context window (not max output)
Intel index
100.0
Matrix AA IQ cell
Measured matrix and verified gateway observations only.
PROVIDER
Alibaba
RELEASE
2026-08-14
CONTEXT
262K tokens
STATUS
ACTIVE
Real operator evaluations, prompt robustness observations, and deployment notes for qwen-3-8-27b.
Tested qwen-3-8-27b on high-concurrency tool loops. Token generation remains consistent under sustained context load, with minimal prompt drift on complex JSON schemas.
Evaluated qwen-3-8-27b on multi-turn code synthesis. Code reasoning and diff application succeed on ~88% of test suites. Best paired with strict system prompt guardrails.
| Metric | |
|---|---|
| Provider | Alibaba |
| Release | 2026-08-14 |
| Input / 1M | $0.48 |
| Output / 1M | $3.39 |
| Context | 262K tokens |
| Cadle Cap | 66 |
| Cap board | Cadle Language Cap 66 |
| epoch-eci | 151.7 |
Scores may use different scales — check the Benchmarks tab for source links.
Same Truth Center numbers as the datasheet above. Accuracy, reliability, safety, and cost scores are not invented.