Benchmark avg
41.6
6 tracked scores
ActiveModel portfolio
claude-opus-4-20250514_16K
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Anthropic · Closed · Context 200K tokens
Cadle Score
142.3
#116 in index
Benchmark average
—
Not enough benchmark results yet
Pricing
Unlisted
no list price
MODEL MATRIX · TRUTH CENTER CELLS
Overall
—
Intelligence
—
Coding
—
Reasoning
35.7
Language
83.6
Knowledge
—
Agentic
—
MMLU
—
GPQA
71.2
Math
—
LiveCodeBench
—
HumanEval
—
Reason
—
ARC-AGI
22.2
Coverage AVG
46.2
Pillar Coverage:2 / 7 Core Pillars (29%)
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
Strongest signal
lech-mazur-writing
Score 83.6
Blended $/1M
Unlisted
No published list price
Context
200K
Provider context window (not max output)
SPEED · COST · QUALITY
Measured matrix and verified gateway observations only.
- Cadle Score
- 142.3
DESCRIPTION + DETAILS
PROVIDER
Anthropic
CONTEXT
200K tokens
STATUS
ACTIVE
COMMUNITY REVIEWS
Community Reviews & Field Notes
Verified EngineersReal operator evaluations, prompt robustness observations, and deployment notes for claude-opus-4-20250514_16K.
4.5(2)
Leave a Field Observation
Rating:5 - Frontier benchmark
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Inference OperatorProduction Deployer Verified
Oct 31, 2026
Tested claude-opus-4-20250514_16K 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 27, 2026
Evaluated claude-opus-4-20250514_16K 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 | Anthropic |
| Release | |
| Input / 1M | No data yet |
| Output / 1M | No data yet |
| Context | 200K tokens |
| Cadle Cap | 142 |
| Cap board | Cadle Language Cap 142 |
| arc-agi-2 | 8.6 |
| arc-agi | 35.7 |
| vpct | 7.0 |
| lech-mazur-writing | 83.6 |
| weirdml | 43.7 |
| gpqa-diamond | 71.2 |
DATA PROVENANCE
Scores may use different scales — check the Benchmarks tab for source links.
- Supabase models
- Cadle public observations
MEASURED CELLS
Same Truth Center numbers as the datasheet above. Accuracy, reliability, safety, and cost scores are not invented.
GPQA71.2
ARC-AGI22.2