Claude Code – Claude Haiku 4.5 (thinking 32k) vs. Claude Code – GLM-5.3-Flash (max): geospatial agent comparison
Comparison between Claude Code – Claude Haiku 4.5 (thinking 32k) and Claude Code – GLM-5.3-Flash (max) 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 – Claude Haiku 4.5 (thinking 32k) | Claude Code – GLM-5.3-Flash (max) |
|---|---|---|
| Geospatial Agent Index | 39* (partial: attempt 1 on 113 of 565 tasks) | 41* (partial: attempt 1 on 135 of 565 tasks) |
| Earth-Bench V2 score | 31 | 43 |
| GeoBenchX score | 47 | 38 |
| GS-QA2 score | No data | No data |
| GeoAgentBench score (guided GIS workflow; outside the index) | 69 | No data |
| GeoAnalystBench score (guided GIS workflow; outside the index) | 100 | No data |
| Raster and remote sensing score | 42 | 44 |
| Vector and overlay score | 100 | 50 |
| Networks and routing score | No data | No data |
| Climate and time series score | 26 | 67 |
| Spatial statistics and interpolation score | 40 | 0 |
| Mapping and cartography score | 60 | 0 |
| Recognising infeasible requests score | 31 | 44 |
| Cost per task | $0.150 | $0.139 |
| Time per task | 2.4 min | 18.3 min |
| Tokens per attempt | 467k | 1.26M |
| Turns per attempt | 13.7 | 25.9 |
| Attempts decided | 110 | 89 |
| Input price per 1M tokens | $1.00 | $0.15 |
| Output price per 1M tokens | $5.00 | $0.50 |
| Context window | 200,000 | 1,048,576 |
| Image input | Yes | Yes |
| Developer | Anthropic | Z.ai |
Charts
Partial coverage. Claude Code – Claude Haiku 4.5 (thinking 32k): 59 of 147 Earth-Bench V2 tasks; 54 of 173 GeoBenchX tasks; GS-QA2 being added; 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) |
|---|
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 – Claude Haiku 4.5 (thinking 32k), Claude Code – GLM-5.3-Flash (max).
Data table: Cost per task
| Model | Creator | Cost per task | Coverage (attempts) |
|---|
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 – Claude Haiku 4.5 (thinking 32k), Claude Code – GLM-5.3-Flash (max).
Data table: Output tokens per task
| Model | Creator | Output tokens per task | Coverage (attempts) |
|---|
Frequently asked questions
Which scores higher on the Geospatial Agent Index, Claude Code – Claude Haiku 4.5 (thinking 32k) or Claude Code – GLM-5.3-Flash (max)?
Which is cheaper per task, Claude Code – Claude Haiku 4.5 (thinking 32k) or Claude Code – GLM-5.3-Flash (max)?
Which writes fewer output tokens per task, Claude Code – Claude Haiku 4.5 (thinking 32k) or Claude Code – GLM-5.3-Flash (max)?
Which has the larger context window, Claude Code – Claude Haiku 4.5 (thinking 32k) or Claude Code – GLM-5.3-Flash (max)?
More: Claude Code – Claude Haiku 4.5 (thinking 32k) · Claude Code – GLM-5.3-Flash (max) · all comparisons