MMMU
77.9
Media Cap quality axis
Alibaba · Open weightsQwen-VL-Max-0809
Active
Model portfolio
Qwen-VL-Max-0809
Tap a star to rate
Alibaba · Open · Context 131K tokens
Vision Cap
No data yet
Cadle Vision ranked · 0%
Benchmark average
No data yet
Not enough benchmark results yet
Pricing
$0.23
$0.58 / 1M out
CADLE CAP vs MODEL MATRIX
Cadle Cap ranks models on every published score we have for them — harder benchmarks weigh more. Missing tests are skipped, not zeroed. It answers who is stronger than whom in today's pool.
Model Matrix is the datasheet: Overall, Intelligence, Coding, Agentic, MMLU, GPQA, Math, LiveCodeBench, HumanEval, Reason, ARC-AGI. A dash means unmeasured. AVG is an importance-weighted mean of that model's filled cells only.
MODEL MATRIX · TRUTH CENTER CELLS
Overall
No data yet
Intelligence
No data yet
Coding
No data yet
Agentic
No data yet
MMLU
No data yet
GPQA
No data yet
Math
No data yet
LiveCodeBench
No data yet
HumanEval
No data yet
Reason
No data yet
ARC-AGI
No data yet
Coverage AVG
No data yet
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.
CADLE INSIGHTS
Only measured signals
MATHVISTA
68.3
Media Cap quality axis
OCRBENCH
88.1
Media Cap quality axis
AI2D
88.1
Media Cap quality axis
STRONGEST SIGNAL
MMMU
Cap axis 77.9
BLENDED $/1M
$0.81
In $0.23 · Out $0.58
CONTEXT
131K
Provider context window (not max output)
SPEED · COST · QUALITY
Measured matrix and verified gateway observations only.
- Input $/1M
- $0.23
- Output $/1M
- $0.58
DESCRIPTION + DETAILS
PROVIDER
Alibaba
CONTEXT
131K tokens
STATUS
ACTIVE
COMMUNITY REVIEWS
OPERATOR NOTES
Quality, latency, cost, and failure modes — verified production observations.
4.5
2 notes indexed
SUBMIT OPERATOR NOTE
Tap a star to rate
Topic:
5 - Frontier benchmark
Stored locally · synced to your profile
I
Inference Operator
VerifiedOct 23, 2026
Tested Qwen-VL-Max-0809 on high-concurrency tool loops. Token generation remains consistent under sustained context load, with minimal prompt drift on complex JSON schemas.
A
Autonomous Agent Lead
VerifiedOct 19, 2026
Evaluated Qwen-VL-Max-0809 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 | $0.23 |
| Output / 1M | $0.58 |
| Context | 131K tokens |
| Cadle Cap | 90 |
| Cap board | Cadle Vision ranked |
DATA PROVENANCE
Scores may use different scales — check the Benchmarks tab for source links.
- Supabase models
- Cadle public observations