Claude Code – GLM-5.3-Flash (max) vs. Codex – GPT-6.1 Sol (high): geospatial agent comparison
Comparison between Claude Code – GLM-5.3-Flash (max) and Codex – GPT-6.1 Sol (high) on the Geospatial Agent Index, each benchmark, cost, time and token use, from the same tasks, agent and limits. Methodology.
Side by side
| Metric | Claude Code – GLM-5.3-Flash (max) | Codex – GPT-6.1 Sol (high) |
|---|---|---|
| Geospatial Agent Index | 41* (partial: attempt 1 on 135 of 565 tasks) | 70* |
| Earth-Bench V2 score | 43 | 58 |
| GeoBenchX score | 38 | 67 |
| GS-QA2 score | No data | 84 |
| GeoAgentBench score (guided GIS workflow; outside the index) | No data | 100 |
| GeoAnalystBench score (guided GIS workflow; outside the index) | No data | 100 |
| Raster and remote sensing score | 44 | 73 |
| Vector and overlay score | 50 | 80 |
| Networks and routing score | No data | No data |
| Climate and time series score | 67 | 66 |
| Spatial statistics and interpolation score | 0 | 29 |
| Mapping and cartography score | 0 | 78 |
| Recognising infeasible requests score | 44 | 67 |
| Cost per task | $0.139 | $0.062 |
| Time per task | 18.3 min | 1.4 min |
| Tokens per attempt | 1.26M | 116k |
| Turns per attempt | 25.9 | 6.8 |
| Attempts decided | 89 | 565 |
| Input price per 1M tokens | $0.15 | $2.00 |
| Output price per 1M tokens | $0.50 | $10.00 |
| Context window | 1,048,576 | No data |
| Image input | Yes | No data |
| Developer | Z.ai | OpenAI |
Charts
Partial coverage. Claude Code – GLM-5.3-Flash (max): 21 of 147 Earth-Bench V2 tasks; 114 of 173 GeoBenchX tasks; GS-QA2 incomplete. Grey placeholders identify these entries in the index, cost and output token charts; their height does not represent a value. Comparable bars appear when first-attempt coverage is complete. Their available results remain in the side-by-side table.
Geospatial Agent Index
Equal-weight average of the evaluation scores, 0 to 100 · Higher is better
First eight selected entries in metric order. Full results in table view.
Data table: Geospatial Agent Index
| Model | Creator | Geospatial Agent Index | Range while attempts are pending | Benchmarks covered | Coverage (attempts) |
|---|---|---|---|---|---|
| Codex – GPT-6.1 Sol (high) | OpenAI | 70* | No pending judgements; coverage incomplete; 207 results awaiting review | 3 of 3 | 565 of 859 planned attempts (1 excluded) |
Cost per task
Average cost per task (USD) · Lower is better
First eight selected entries in metric order. Full results in table view.
How to read this chart
Not shown: partial coverage. Claude Code – GLM-5.3-Flash (max).
Data table: Cost per task
| Model | Creator | Cost per task | Coverage (attempts) |
|---|---|---|---|
| Codex – GPT-6.1 Sol (high) | OpenAI | $0.062 | 565 of 859 planned attempts (1 excluded) |
Output tokens per task
Average output tokens per attempt, reasoning included · Lower is better
First eight selected entries in metric order. Full results in table view.
How to read this chart
Not shown: partial coverage. Claude Code – GLM-5.3-Flash (max).
Data table: Output tokens per task
| Model | Creator | Output tokens per task | Coverage (attempts) |
|---|---|---|---|
| Codex – GPT-6.1 Sol (high) | OpenAI | 2k | 565 of 859 planned attempts (1 excluded) |
Frequently asked questions
Which scores higher on the Geospatial Agent Index, Claude Code – GLM-5.3-Flash (max) or Codex – GPT-6.1 Sol (high)?
Which is cheaper per task, Claude Code – GLM-5.3-Flash (max) or Codex – GPT-6.1 Sol (high)?
Which writes fewer output tokens per task, Claude Code – GLM-5.3-Flash (max) or Codex – GPT-6.1 Sol (high)?
Which has the larger context window, Claude Code – GLM-5.3-Flash (max) or Codex – GPT-6.1 Sol (high)?
More: Claude Code – GLM-5.3-Flash (max) · Codex – GPT-6.1 Sol (high) · all comparisons