Claude Sonnet 5.5 (max) vs GPT-6 Luna (xhigh)
Results updated 3 November 2026 · In Claude Code and Codex, so part of any gap can come from the harness · How we benchmark
Verdict
Not comparable yet: Claude Sonnet 5.5 (max) is not yet ranked.
- Cost per task
- $0.54 vs $0.0070
- Time per task
- 5.6 min (estimated) vs 1.4 min
- Tokens per attempt
- 649k vs 182k
- Image input
- Yes vs Yes
Claude Sonnet 5.5 (max), Claude Code scores higher on GeoBenchX, GS-QA2 and Vision agents; GPT-6 Luna (xhigh), Codex scores higher on Earth-Bench V2. GPT-6 Luna (xhigh), Codex is cheaper and faster: $0.0070 against $0.54 per task, and 1.4 min against 5.6 min.
Not yet ranked. Claude Sonnet 5.5 (max), Claude Code. Not in the Agent Index, cost and time charts until it has a score on every index evaluation. Results so far are in the side-by-side table.
Where they differ most
By kind of work, share of tasks passed, 0 to 100 · Higher is better
| Kind of work | Claude Sonnet 5.5 (max) | GPT-6 Luna (xhigh) |
|---|---|---|
| Spatial statistics | 100 | 46 |
| GIS analysis | 95 | 78 |
| Climate and time series | 58 | 73 |
| Remote sensing and raster analysis | 88 | 73 |
Where the tasks are set: each kind of work links to its tasks and scoresCharts for each: Claude Sonnet 5.5 (max), Claude Code · GPT-6 Luna (xhigh), Codex.
Side by side
| Metric | Claude Sonnet 5.5 (max), Claude Code | GPT-6 Luna (xhigh), Codex |
|---|---|---|
| Geospatial Agent Index: Text only | 75 | 73 |
| Geospatial Agent Index: Text + vision | No data | 72 |
| Earth-Bench V2 score | 57 | 67 |
| GeoBenchX score | 77 | 73 |
| GS-QA2 score | 92 | 78 |
| Vision agents score | 89 | 70 |
| GeoAgentBench score (Guided workflows; not in the Agent Index) | 100 | 96 |
| GeoAnalystBench score (Guided workflows; not in the Agent Index) | 100 | 100 |
| OGD4All score (standalone; in no index) | 97 | No data |
| GeoNatureAgent score (standalone; in no index) | 100 | No data |
| MultiGlobeQA score (standalone; in no index) | 78 | No data |
| GeoAgentEval score (standalone; in no index) | 100 | No data |
| Remote sensing and raster analysis score | 88 | 73 |
| GIS analysis score | 95 | 78 |
| Climate and time series score | 58 | 73 |
| Spatial statistics score | 100 | 46 |
| Making maps score | 78 | 72 |
| Recognising infeasible requests score | 75 | 80 |
| Cost per task | $0.54 | $0.0070 |
| Time per task (at 100 output tokens/s) | 5.6 min (estimated) | 1.4 min |
| Tokens per attempt | 649k | 182k |
| Turns per attempt | 12.8 | 8.8 |
| Input price per 1M tokens | $2.00 | $0.10 |
| Output price per 1M tokens | $10.00 | $0.50 |
| Context window | 1,000,000 | 1,050,000 |
| Image input | Yes | Yes |
| Developer | Anthropic | OpenAI |