📡 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: 95
latency: 0.48
contextWindow: 1000000
inputPrice: 0.26
outputPrice: 1.56
benchmarkMmlu: 88.5
benchmarkHumanEval: 89.5
benchmarkMath: 90
benchmarkHellaSwag: 89.5
benchmarkGpqa: 63
benchmarkMmluPro: 67
reasoningScore: 79
codingScore: 86.4
benchmarkSweBench: 41
Q

Qwen: Qwen3.5 Plus 2026-02-15

qwen🔒 Proprietary
7.3
LLM Stats Scores
79.0
Reasoning
86.4
Coding
🎯
63.0%GPQA Diamond — graduate-level science accuracy
67.0%MMLU-Pro
Published benchmark evidence
Task scores are reported independently by each publisher; they are not combined into a hidden quality score.
41.0%
SWE-bench
Quality Score
76.0
Overall (0–100)
Speed
95 c/s
characters/second
Latency (TTFT)
0.48s
to first token
Input Price
$0.26
per 1M tokens
Output Price
$1.56
per 1M tokens
Context Window
1M
tokens
Release Date
2026-02-16

30-Day Rank History

📊 Benchmark Scores

Reported scores · % accuracy
0%25%50%75%100%GPQA ◆MMLU-ProMMLUHumanEvalMATHHellaSwag
What do these benchmarks test?
🎯
GPQA Diamond63.0%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-Pro67.0%Solid
The harder successor to MMLU — more options per question eliminate single-answer guessing. Tests depth of professional knowledge across 14 disciplines.
🧠
MMLU88.5%Top tier
The classic academic breadth benchmark. Top frontier models now score above 85%, so it best distinguishes mid-tier from strong generalist models.
💻
HumanEval89.5%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 Benchmark90.0%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%.
🌐
HellaSwag89.5%Solid
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
$0.26
Output cost
$0.78
Total / month
$1.04
Annual cost
$12.48
Input: $0.26/1M
Output: $1.56/1M
Rate: 1 USD = 1.00 USD · 2026-11-10
68.3% cheaper than average
Cheaper alternatives:
Z.ai: GLM 5.2$0.007/1M · Q73

AI Score

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7.8/10

"Slightly older than the 3.6 variant, still strong but a bit slower and less cost‑effective."

🤖 AI Analysis