📡 LLM Pulse|🆕 New on leaderboard: Baidu: ERNIE-Light-DT-1.0 by Baidu — $1.13/M tokens1/10
Measurement sources and verification status (16 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: 1024000
inputPrice: 0.48
outputPrice: 1.8
benchmarkMmlu: 78
benchmarkHumanEval: 78
benchmarkMath: 74
benchmarkGpqa: 60
reasoningScore: 67
codingScore: 78
aaIntelligenceIndex: 26
aaCostPerTask: 0.05
aaOutputSpeed: 32
aaLatency: 2.32
aaEndToEndTime: 20.57
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Xiaomi: MiMo-V2.5-Pro

xiaomi🔒 Proprietary

Published Artificial Analysis leaderboard evidence.

6.9
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 ↗
35.7%
Humanity's Last Exam
Artificial Analysis measurements
Published operational results. Cost per task, speed, and latency are kept separate from provider API prices.
Intelligence
26
AA Index
Cost / task
$0.05
AA measured
Output speed
32
tokens / second
TTFT
2.32s
AA measured
Response time
20.57s
end to end
Quality Score
73.0
Overall (0–100)
Speed
80 c/s
characters/second
Latency (TTFT)
0.50s
to first token
Input Price
$0.48
per 1M tokens
Output Price
$1.8
per 1M tokens
Context Window
1M
tokens
Release Date
2026-04-22

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%.

💰 Cost Calculator

Input cost
$0.48
Output cost
$0.90
Total / month
$1.38
Annual cost
$16.56
Input: $0.48/1M
Output: $1.8/1M
Rate: 1 USD = 1.00 USD · 2026-11-10
57.9% cheaper than average
Cheaper alternatives:
Z.ai: GLM 5.2$0.007/1M · Q73

AI Score

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7.2/10

"Impressive 1.05M context and low price, yet quality lags behind leading models."

🤖 AI Analysis