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Measurement sources and verification status (14 fields)

Collected third-party figures are not independent tests. A source link and collection date do not establish reproducibility. Exact model version, dataset and test settings may be missing. No independent verification date is supplied.

speed: 80
latency: 0.55
contextWindow: 200000
inputPrice: 3
outputPrice: 15
benchmarkMmlu: 88
benchmarkHumanEval: 92
benchmarkMath: 88
benchmarkHellaSwag: 94.5
benchmarkGpqa: 62
benchmarkMmluPro: 68
reasoningScore: 81
codingScore: 92
benchmarkSweBench: 70.3

Anthropic: Claude Sonnet 4

anthropic🔒 Proprietary

Published BenchLM leaderboard evidence.

7.2
LLM Stats Scores
81.0
Reasoning
92.0
Coding
🎯
62.0%GPQA Diamond — graduate-level science accuracy
68.0%MMLU-Pro
Published benchmark evidence
Task scores are reported independently by each publisher; they are not combined into a hidden quality score.
View HLE source ↗
10.7%
Humanity's Last Exam
70.3%
SWE-bench
Quality Score
86.0
Overall (0–100)
Speed
80 c/s
characters/second
Latency (TTFT)
0.55s
to first token
Input Price
$3
per 1M tokens
Output Price
$15
per 1M tokens
Context Window
200K
tokens
Release Date
2025-Q2

30-Day Rank History

📊 Benchmark Scores

Reported scores · % accuracy
0%25%50%75%100%GPQA ◆MMLU-ProMMLUHumanEvalMATHHellaSwag
What do these benchmarks test?
🎯
GPQA Diamond62.0%Below avg
Designed so that even PhD-level human experts average ~65–70%. A score above 80% signals near-expert scientific reasoning that goes far beyond memorisation.
📚
MMLU-Pro68.0%Solid
The harder successor to MMLU — more options per question eliminate single-answer guessing. Tests depth of professional knowledge across 14 disciplines.
🧠
MMLU88.0%Top tier
The classic academic breadth benchmark. Top frontier models now score above 85%, so it best distinguishes mid-tier from strong generalist models.
💻
HumanEval92.0%Top tier
Measures whether a model writes functionally correct code — not just plausible-looking syntax. Strong scores (>85%) indicate reliable day-to-day coding assistance.
∑
MATH Benchmark88.0%Top tier
Tests multi-step mathematical reasoning under strict correctness. Even a 60% score requires strong chain-of-thought; top reasoning models now exceed 90%.
🌐
HellaSwag94.5%Top tier
Tests grounded, everyday common sense rather than memorised facts. Most frontier models now score 90%+, so it best separates small/mid models from large ones.

💰 Cost Calculator

Input cost
$3.00
Output cost
$7.50
Total / month
$10.50
Annual cost
$126.00
Input: $3/1M
Output: $15/1M
Rate: 1 USD = 1.00 USD · 2026-11-10
220.3% pricier than average
Cheaper alternatives:
Z.ai: GLM 5.2$0.007/1M · Q73

AI Score

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7.5/10

"Solid general‑purpose model, but older architecture limits reasoning depth."

🤖 AI Analysis