Experimental run record

Run 4a0b7258

An inspectable execution record: configuration, deterministic outcomes, attempts, artefacts, and failure traces. Comparison applies across the configurations in this run only.

· pack geoworkbench-0.1 · accepted · sealed snapshot 243b17d4

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Trials
12
Accepted
5
Configurations
4
Tasks
3
Cost USD
0.02806

In shortKimi K2.6 led this run: 3/3 tasks accepted (100%) for 0.0082 USD total. This ranking holds inside this run only — it is not a general model ranking.

Comparison across the configurations in this run only

JSON · CSV
Ranked by accepted rate, then total cost. Not comparable across runs or pack versions.
#ModelArchitectureAcceptedRateFirst-attempt successFalse-success rejectedCost USDCost / acceptedMedian msp95 ms
1Kimi K2.6single-retry3/3100%33.3%00.00820.002770451 ms77379 ms
2GLM-4.7 Flashsingle-shot1/333.3%33.3%20.00510.005137812 ms49096 ms
3GLM-4.7 Flashsingle-retry1/333.3%33.3%20.00900.009079605 ms80983 ms
4Kimi K2.6single-shot0/30%0%30.00580.000048695 ms49410 ms

Trials

attempt traces expand beneath each trial
Trial outcomes are deterministic verifier results, not model-judge opinions.
TaskConfigurationRetryResultAttemptsCost USDLatency ms
crs-reproject-munichGLM-4.7 Flashsingle-shotrejected10.0019 USD37812 ms
Attempt trace undefined
# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.0019 USD — 37812 ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced

crs-reproject-munichGLM-4.7 Flashsingle-retryrejected20.0037 USD80983 ms
Attempt trace undefined
# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.0016 USD — 50853 ms
# verifier: FAIL — output not in WGS84 Munich coords
# artifact: download (582 bytes)
import geopandas as gpd

# Load the input file
gdf = gpd.read_file('input.geojson')

# Diagnosis: Determine the CRS based on coordinate magnitude.
# Large coordinates (millions) indicate a projected CRS.
# Web Mercator (EPSG:3857) covers approximately -20,000,000 to 20,000,000.
if gdf.crs is None:
    # Check if any coordinate is in the millions
    if (gdf['geometry'].x.abs() > 1_000_000).any():
        gdf.crs = 'EPSG:3857'

# Reproject to WGS84 (EPSG:4326)
gdf_wgs84 = gdf.to_crs(epsg=4326)

# Write the output
gdf_wgs84.to_file('output.geojson', driver='GeoJSON')
Attempt trace undefined
# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.0021 USD — 80983 ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced

raster-zonal-meanGLM-4.7 Flashsingle-shotrejected10.0019 USD49096 ms
Attempt trace undefined
# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.0019 USD — 49096 ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

raster-zonal-meanGLM-4.7 Flashsingle-retryrejected20.0038 USD79605 ms
Attempt trace undefined
# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.0019 USD — 38163 ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

Attempt trace undefined
# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.0019 USD — 79605 ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

vector-buffer-1kmGLM-4.7 Flashsingle-shotaccepted10.0013 USD27210 ms
Attempt trace undefined
# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — accepted — cost 0.0013 USD — 27210 ms
# verifier: PASS — 1000m buffers verified
# artifact: download (5935 bytes)
import geopandas as gpd

gdf = gpd.read_file("sites.geojson")
gdf_projected = gdf.to_crs(epsg=3857)
gdf_projected['geometry'] = gdf_projected.buffer(1000)
gdf_final = gdf_projected.to_crs(epsg=4326)
gdf_final.to_file("buffers.geojson", driver="GeoJSON")
vector-buffer-1kmGLM-4.7 Flashsingle-retryaccepted10.0015 USD49203 ms
Attempt trace undefined
# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — accepted — cost 0.0015 USD — 49203 ms
# verifier: PASS — 1000m buffers verified
# artifact: download (5903 bytes)
import geopandas as gpd
from pyproj import CRS

# Read the input file
gdf = gpd.read_file("sites.geojson")

# Reproject to a projected CRS (EPSG:3857) to ensure 1000m is calculated correctly
gdf_projected = gdf.to_crs("EPSG:3857")

# Create 1000 metre buffers
gdf_projected['buffer'] = gdf_projected.geometry.buffer(1000)

# Extract the buffer geometries and reproject back to WGS84 (EPSG:4326)
buffers = gdf_projected[['buffer']].copy()
buffers = buffers.set_geometry('buffer')
buffers = buffers.to_crs("EPSG:4326")

# Write the result to the output file
buffers.to_file("buffers.geojson", driver="GeoJSON")
crs-reproject-munichKimi K2.6single-shotrejected10.0019 USD47932 ms
Attempt trace undefined
# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — rejected — cost 0.0019 USD — 47932 ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced

crs-reproject-munichKimi K2.6single-retryaccepted20.0033 USD70451 ms
Attempt trace undefined
# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 1 — rejected — cost 0.0019 USD — 41471 ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced
import geopandas as gpd
from pyproj import CRS

gdf = gpd.read_file('input.geojson')
source_crs = CRS.from_epsg(3857)
target_crs = CRS.from_epsg(4326)
gdf = gdf.set_crs(source

--- stderr ---
  File "/tmp/arena/solution.py", line 7
    gdf = gdf.set_crs(source
                     ^
SyntaxError: '(' was never closed
Attempt trace undefined
# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — accepted — cost 0.0014 USD — 70451 ms
# verifier: PASS — CRS reproject to WGS84 verified
# artifact: download (591 bytes)
import geopandas as gpd
from pyproj import CRS

gdf = gpd.read_file('input.geojson')
source_crs = CRS.from_epsg(3857)
target_crs = CRS.from_epsg(4326)
gdf = gdf.set_crs(source_crs, allow_override=True)
gdf = gdf.to_crs(target_crs)
gdf.to_file('output.geojson', driver='GeoJSON')
raster-zonal-meanKimi K2.6single-shotrejected10.0019 USD49410 ms
Attempt trace undefined
# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — rejected — cost 0.0019 USD — 49410 ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

raster-zonal-meanKimi K2.6single-retryaccepted20.0035 USD77379 ms
Attempt trace undefined
# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — rejected — cost 0.0019 USD — 41332 ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

Attempt trace undefined
# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — accepted — cost 0.0016 USD — 77379 ms
# verifier: PASS — zonal mean verified by independent recompute
# artifact: download (14 bytes)
import json
import numpy as np
import rasterio
import rasterio.mask

with open("zone.geojson") as f:
    geojson = json.load(f)

if geojson["type"] == "FeatureCollection":
    geometry = geojson["features"][0]["geometry"]
elif geojson["type"] == "Feature":
    geometry = geojson["geometry"]
else:
    geometry = geojson

with rasterio.open("grid.asc") as src:
    nodata = src.nodata
    out_image, _ = rasterio.mask.mask(src, [geometry], crop=True)
    band = out_image[0]

    valid_mask = np.ones(band.shape, dtype=bool)
    if nodata is not None:
        valid_mask &= band != nodata
    valid_mask &= ~np.isnan(band)

    valid_pixels = band[valid_mask]
    mean_value = float(np.mean(valid_pixels)) if valid_pixels.size > 0 else None

with open("stats.json", "w") as f:
    json.dump({"mean": mean_value}, f)
vector-buffer-1kmKimi K2.6single-shotrejected10.0019 USD48695 ms
Attempt trace undefined
# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — rejected — cost 0.0019 USD — 48695 ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced
import geopandas as gpd

gdf = gpd.read_file('sites.geojson')
gdf = gdf.set_crs(epsg=4326, allow_override=True)
gdf = gdf
vector-buffer-1kmKimi K2.6single-retryaccepted10.0013 USD31421 ms
Attempt trace undefined
# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — accepted — cost 0.0013 USD — 31421 ms
# verifier: PASS — 1000m buffers verified
# artifact: download (5935 bytes)
import geopandas as gpd

gdf = gpd.read_file('sites.geojson')
if gdf.crs is None:
    gdf.set_crs(epsg=4326, inplace=True)
gdf = gdf.to_crs(epsg=3857)
gdf.geometry = gdf.buffer(1000)
gdf = gdf.to_crs(epsg=4326)
gdf.to_file('buffers.geojson', driver='GeoJSON')

Cite this record

Axis Spatial. "Experimental run 4a0b7258." Axis Spatial Arena, run 4a0b7258-6a07-4da3-a8cb-83c98c43af3e. Benchmark pack geoworkbench-0.1. https://www.axisspatial.com/arena/runs/4a0b7258-6a07-4da3-a8cb-83c98c43af3e (accessed 19 Sep 2026).
@misc{axis-spatial-arena-run-4a0b7258,
  author = {{Axis Spatial}},
  title = {Experimental run 4a0b7258},
  howpublished = {Axis Spatial Arena, run: https://www.axisspatial.com/arena/runs/4a0b7258-6a07-4da3-a8cb-83c98c43af3e},
  note = {Benchmark pack geoworkbench-0.1},
  year = {2026}
}

Glossary

full protocol in the methodology
Pack version
The pinned set of task definitions a run executed. Results from different pack versions are never compared directly.
Configuration
A complete comparison unit: model, prompt version, tools, retry policy, and pinned task, data, and verifier versions. A model name alone is not comparable.
Lane
One configured route through which a model is reached. Duplicate upstream models across lanes count as adapter evidence, not extra capability.
False-success rejection
A trial whose output looked plausible but failed independent deterministic checks, such as an empty file or a fabricated value.
Token-cost proxy
Cost estimated from reported token usage and list prices at recording time; actual billing may differ.
Sealed snapshot
An immutable, content-addressed copy of a leaderboard computed from a finished run.