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import marimo
__generated_with = "0.23.10"
app = marimo.App(width="full")
@app.cell
def _():
import marimo as mo
import pandas as pd
import altair as alt
return alt, mo, pd
# https://artificialanalysis.ai/leaderboards/models
@app.cell
def _(pd):
COLUMNS = ["name", "aai_score", "price", "tok_per_sec"]
ROWS = [
["DeepSeek V4 Flash", 37, 0.08, 101],
["DeepSeek V4 Pro", 44, 0.18, 85],
["Claude Opus 4.7", 54, 3.85, 51],
["Claude Opus 4.8", 56, 3.85, 58],
["Claude Sonnet 4.6", 47, 2.31, 50],
["Claude Haiku 4.5", 30, 0.77, 93],
["Gemini 3.5 Flash", 50, 1.31, 161],
["MiMo 2.5", 40, 0.06, 79],
["Nemotron 3 Ultra", 38, 0.58, 164],
["Gemma 4 E2B (local)", 9, 0.0, 60],
["GLM 5.2", 51, 0.90, 82],
["MiniMax M3", 44, 0.22, 68],
]
df = pd.DataFrame(ROWS, columns=COLUMNS)
return df
@app.cell
def _(df, mo):
mo.md(f"""
# 🤖 LLM Stats Tracker
**{len(df)} models tracked**
""")
return
@app.cell
def _(alt, df):
scatter = (
alt.Chart(df)
.mark_circle(size=200)
.encode(
x=alt.X("price", title="Blended Price $/1M"),
y=alt.Y("aai_score", title="AAI Score"),
color=alt.Color("tok_per_sec:Q", title="tok/sec", scale=alt.Scale(scheme="viridis")),
tooltip=["name", "aai_score", "price", "tok_per_sec"],
)
)
labels = (
alt.Chart(df)
.mark_text(dy=-12, fontSize=10)
.encode(
x="price",
y="aai_score",
text="name",
)
)
chart_price_quality = (scatter + labels).properties(width="container")
chart_price_quality
return
@app.cell
def _(alt, df):
bubble = (
alt.Chart(df)
.mark_circle(size=120, opacity=0.7)
.encode(
x=alt.X("tok_per_sec:Q", title="Tokens/sec"),
y=alt.Y("aai_score:Q", title="AAI Score"),
color=alt.Color("price:Q", title="Price $/1M", scale=alt.Scale(scheme="viridis")),
tooltip=["name", "aai_score", "price", "tok_per_sec"],
)
)
bubble_labels = (
alt.Chart(df)
.mark_text(dy=-14, fontSize=10, fontWeight="bold")
.encode(
x="tok_per_sec:Q",
y="aai_score:Q",
text="name:N",
)
)
chart_speed_quality = (bubble + bubble_labels).properties(width="container")
chart_speed_quality
return
if __name__ == "__main__":
app.run()
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