Claude Opus 5.5 (max) vs GPT-6 Sol (medium)
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 Opus 5.5 (max) is not yet ranked and GPT-6 Sol (medium) is not yet ranked.
- Cost per task
- $0.83 vs $0.047
- Time per task
- 4.5 min (estimated) vs 0.3 min
- Tokens per attempt
- 530k vs 86k
- Image input
- Yes vs Yes
Claude Opus 5.5 (max), Claude Code scores higher on GS-QA2 and Vision agents; GPT-6 Sol (medium), Codex scores higher on Earth-Bench V2 and GeoBenchX. GPT-6 Sol (medium), Codex is cheaper and faster: $0.047 against $0.83 per task, and 0.3 min against 4.5 min.
Not yet ranked. Claude Opus 5.5 (max), Claude Code; GPT-6 Sol (medium), Codex. 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 Opus 5.5 (max) | GPT-6 Sol (medium) |
|---|---|---|
| Making maps | 77 | 100 |
| Climate and time series | 60 | 76 |
| GIS analysis | 93 | 83 |
| Recognising infeasible requests | 79 | 75 |
Charts for each: Claude Opus 5.5 (max), Claude Code · GPT-6 Sol (medium), Codex.
Side by side
| Metric | Claude Opus 5.5 (max), Claude Code | GPT-6 Sol (medium), Codex |
|---|---|---|
| Geospatial Agent Index: Text only | 79 | 80 |
| Geospatial Agent Index: Text + vision | No data | No data |
| Earth-Bench V2 score | 71 | 77 |
| GeoBenchX score | 74 | 75 |
| GS-QA2 score | 92 | 87 |
| Vision agents score | 98 | 91 |
| GeoAgentBench score (Guided workflows; not in the Agent Index) | 100 | 100 |
| GeoAnalystBench score (Guided workflows; not in the Agent Index) | 100 | No data |
| OGD4All score (standalone; in no index) | 95 | No data |
| GeoNatureAgent score (standalone; in no index) | 100 | No data |
| MultiGlobeQA score (standalone; in no index) | 76 | No data |
| GeoAgentEval score (standalone; in no index) | 100 | No data |
| Remote sensing and raster analysis score | 88 | 88 |
| GIS analysis score | 93 | 83 |
| Climate and time series score | 60 | 76 |
| Spatial statistics score | 50 | 50 |
| Making maps score | 77 | 100 |
| Recognising infeasible requests score | 79 | 75 |
| Cost per task | $0.83 | $0.047 |
| Time per task (at 100 output tokens/s) | 4.5 min (estimated) | 0.3 min |
| Tokens per attempt | 530k | 86k |
| Turns per attempt | 12.0 | 6.4 |
| Input price per 1M tokens | $4.00 | $2.00 |
| Output price per 1M tokens | $20.00 | $10.00 |
| Context window | 1,000,000 | 1,050,000 |
| Image input | Yes | Yes |
| Developer | Anthropic | OpenAI |
