📡 LLM Pulse|🆕 New on leaderboard: Baidu: ERNIE-Light-DT-1.0 by Baidu — $1.13/M tokens1/10
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: 128000
benchmarkMmlu: 78
benchmarkHumanEval: 78
benchmarkMath: 74
benchmarkGpqa: 60
reasoningScore: 67
codingScore: 78
aaIntelligenceIndex: 8
aaOutputSpeed: 91
aaLatency: 1.4
aaEndToEndTime: 28.88
E

Hermes 4 70B

external🔒 Proprietary

Published Artificial Analysis leaderboard evidence.

6.0
LLM Stats Scores
67.0
Reasoning
78.0
Coding
🎯
60.0%GPQA Diamond — graduate-level science accuracy
Published benchmark evidence
Task scores are reported independently by each publisher; they are not combined into a hidden quality score.
View HLE source ↗
3.6%
Humanity's Last Exam
Artificial Analysis measurements
Published operational results. Cost per task, speed, and latency are kept separate from provider API prices.
View source ↗
Intelligence
8
AA Index
Output speed
91
tokens / second
TTFT
1.40s
AA measured
Response time
28.88s
end to end
Collected 10/27/2026
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
—
per 1M tokens
Context Window
128K
tokens
Release Date
2024-09

30-Day Rank History

📊 Benchmark Scores

Reported scores · % accuracy
0%25%50%75%100%GPQA ◆MMLUHumanEvalMATH60.0%78.0%78.0%74.0%
What do these benchmarks test?
🎯
GPQA Diamond60.0%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.
🧠
MMLU78.0%Solid
The classic academic breadth benchmark. Top frontier models now score above 85%, so it best distinguishes mid-tier from strong generalist models.
💻
HumanEval78.0%Solid
Measures whether a model writes functionally correct code — not just plausible-looking syntax. Strong scores (>85%) indicate reliable day-to-day coding assistance.
∑
MATH Benchmark74.0%Solid
Tests multi-step mathematical reasoning under strict correctness. Even a 60% score requires strong chain-of-thought; top reasoning models now exceed 90%.

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AI Score

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6.5/10

"Solid 70B model but trails the latest frontier LLMs in reasoning and instruction-following"

🤖 AI Analysis