📡 LLM Pulse|🆕 New on leaderboard: Baidu: ERNIE-Light-DT-1.0 by Baidu — $1.13/M tokens1/10
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: 160
latency: 0.26
contextWindow: 131072
inputPrice: 0.02
outputPrice: 0.04
benchmarkMmlu: 73
benchmarkHumanEval: 72.6
benchmarkMath: 56.7
benchmarkHellaSwag: 82
benchmarkGpqa: 28
benchmarkMmluPro: 48
reasoningScore: 42
codingScore: 72.6
benchmarkSweBench: 21

Meta: Llama 3.1 8B Instruct

meta-llama🔒 Proprietary
5.6
LLM Stats Scores
42.0
Reasoning
72.6
Coding
🎯
28.0%GPQA Diamond — graduate-level science accuracy
48.0%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 ↗
5.3%
Humanity's Last Exam
21.0%
SWE-bench
Quality Score
58.0
Overall (0–100)
Speed
160 c/s
characters/second
Latency (TTFT)
0.26s
to first token
Input Price
$0.02
per 1M tokens
Output Price
$0.04
per 1M tokens
Context Window
131K
tokens
Release Date
2024-07-23

30-Day Rank History

📊 Benchmark Scores

Reported scores · % accuracy
0%25%50%75%100%GPQA ◆MMLU-ProMMLUHumanEvalMATHHellaSwag28.0%48.0%73.0%72.6%56.7%82.0%
What do these benchmarks test?
🎯
GPQA Diamond28.0%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-Pro48.0%Below avg
The harder successor to MMLU — more options per question eliminate single-answer guessing. Tests depth of professional knowledge across 14 disciplines.
🧠
MMLU73.0%Below avg
The classic academic breadth benchmark. Top frontier models now score above 85%, so it best distinguishes mid-tier from strong generalist models.
💻
HumanEval72.6%Below avg
Measures whether a model writes functionally correct code — not just plausible-looking syntax. Strong scores (>85%) indicate reliable day-to-day coding assistance.
∑
MATH Benchmark56.7%Below avg
Tests multi-step mathematical reasoning under strict correctness. Even a 60% score requires strong chain-of-thought; top reasoning models now exceed 90%.
🌐
HellaSwag82.0%Below avg
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
$0.020
Output cost
$0.020
Total / month
$0.040
Annual cost
$0.48
Input: $0.02/1M
Output: $0.04/1M
Rate: 1 USD = 1.00 USD · 2026-11-10
98.8% cheaper than average
Cheaper alternatives:
Z.ai: GLM 5.2$0.007/1M · Q73

AI Score

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7.2/10

"8B size with 131K context and very low cost make it a strong all‑round choice"

🤖 AI Analysis