📡 LLM Pulse|🆕 New on leaderboard: Baidu: ERNIE-Light-DT-1.0 by Baidu — $1.13/M tokens1/10
Measurement sources and verification status (17 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: 115
latency: 0.38
contextWindow: 262144
inputPrice: 0.12
outputPrice: 0.8
benchmarkMmlu: 81.2
benchmarkHumanEval: 92.7
benchmarkMath: 81
benchmarkGpqa: 48
reasoningScore: 65
codingScore: 92.7
benchmarkSweBench: 51
aaIntelligenceIndex: 9
aaCostPerTask: 0.47
aaOutputSpeed: 82
aaLatency: 1.37
aaEndToEndTime: 6.99
Q

Qwen: Qwen3 Coder Next

qwen🔒 Proprietary

Qwen3-Coder-Next is an open-weight causal language model optimized for coding agents and local development workflows. It uses a sparse MoE design with 80B total parameters and only 3B activated per...

7.4
LLM Stats Scores
65.0
Reasoning
92.7
Coding
🎯
48.0%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 ↗
10.1%
Humanity's Last Exam
51.0%
SWE-bench
Artificial Analysis measurements
Published operational results. Cost per task, speed, and latency are kept separate from provider API prices.
View source ↗
Intelligence
9
AA Index
Cost / task
$0.47
AA measured
Output speed
82
tokens / second
TTFT
1.37s
AA measured
Response time
6.99s
end to end
Collected 11/11/2026
Quality Score
76.0
Overall (0–100)
Speed
115 c/s
characters/second
Latency (TTFT)
0.38s
to first token
Input Price
$0.12
per 1M tokens
Output Price
$0.8
per 1M tokens
Context Window
262K
tokens
Release Date
2026-02-04

30-Day Rank History

📊 Benchmark Scores

Reported scores · % accuracy
0%25%50%75%100%GPQA ◆MMLUHumanEvalMATH
What do these benchmarks test?
🎯
GPQA Diamond48.0%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.
🧠
MMLU81.2%Solid
The classic academic breadth benchmark. Top frontier models now score above 85%, so it best distinguishes mid-tier from strong generalist models.
💻
HumanEval92.7%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 Benchmark81.0%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%.

💰 Cost Calculator

Input cost
$0.12
Output cost
$0.40
Total / month
$0.52
Annual cost
$6.24
Input: $0.12/1M
Output: $0.8/1M
Rate: 1 USD = 1.00 USD · 2026-11-10
84.1% cheaper than average
Cheaper alternatives:
Z.ai: GLM 5.2$0.007/1M · Q73

AI Score

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7.4/10

"Excellent coding specialization and low inference cost, though general‑purpose ability is modest"

🤖 AI Analysis