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Measurement sources and verification status (13 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: 0.5

contextWindow: 400000

inputPrice: 5

outputPrice: 30

benchmarkMmlu: 91

benchmarkHumanEval: 92

benchmarkMath: 96

benchmarkHellaSwag: 94

benchmarkGpqa: 79

benchmarkMmluPro: 79

reasoningScore: 67

codingScore: 78

OpenAI: GPT Chat Latest

openai🔒 Proprietary

LLM Stats Scores

67.0

Reasoning

78.0

Coding

🎯

79.0%GPQA Diamond — graduate-level science accuracy

79.0%MMLU-Pro

Quality Score

73.0

Overall (0–100)

Speed

80 c/s

characters/second

Latency (TTFT)

0.50s

to first token

Input Price

per 1M tokens

Output Price

$30

per 1M tokens

Context Window

400K

tokens

Release Date

2025-Q2

30-Day Rank History

📊 Benchmark Scores

Reported scores · % accuracy

What do these benchmarks test?

🎯

GPQA Diamond79.0%Solid

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-Pro79.0%Top tier

The harder successor to MMLU — more options per question eliminate single-answer guessing. Tests depth of professional knowledge across 14 disciplines.

🧠

MMLU91.0%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 Benchmark96.0%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%.

🌐

HellaSwag94.0%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.