OpenGPTAI decision intelligenceResolved75.8%Cost per successful taskNot publishedPublished result rangeNot published
Agent details →Shared benchmark scope · SWE-bench Verified
Same-benchmark agent comparison
The entries below share the same benchmark scope. Their exact scaffolds, model versions, dates, and original source values remain visible.
A higher source value only means better performance on this benchmark and configuration. It is not a cross-benchmark or production-readiness score.
Compare like with like
Decision overview
Only configurations from the same benchmark version and task scope can be placed in one comparison.
Resolved76.8%Cost per successful taskNot publishedPublished result rangeNot published
Agent details →17 identical or entirely unreported fields hidden
| Agent system | mini-SWE-agent + MiniMax M2.5 (high reasoning) | mini-SWE-agent + Claude 4.5 Opus (high reasoning) |
|---|---|---|
| Configuration | ||
| Base model | MiniMax M2.5 (high reasoning) | Claude 4.5 Opus (high reasoning) |
| Source model ID or label | minimax-m2.5 | claude-4-5-opus |
| Outcome | ||
| Resolved | 75.8% | 76.8% |
| Reported benchmark cost | $36.64 | $376.95 |
| Source | ||
| Open source | Open source ↗ | Open source ↗ |
Configuration
mini-SWE-agent + MiniMax M2.5 (high reasoning)
- Base model
- MiniMax M2.5 (high reasoning)
- Source model ID or label
- minimax-m2.5
mini-SWE-agent + Claude 4.5 Opus (high reasoning)
- Base model
- Claude 4.5 Opus (high reasoning)
- Source model ID or label
- claude-4-5-opus
Outcome
mini-SWE-agent + MiniMax M2.5 (high reasoning)
- Resolved
- 75.8%
- Reported benchmark cost
- $36.64
mini-SWE-agent + Claude 4.5 Opus (high reasoning)
- Resolved
- 76.8%
- Reported benchmark cost
- $376.95
Source
mini-SWE-agent + MiniMax M2.5 (high reasoning)
mini-SWE-agent + Claude 4.5 Opus (high reasoning)
Source-reported data; missing values remain unknown.
Validate before adoption
Public rankings create a shortlist. A small private trial decides whether the configuration fits your work.
- 1
Choose 10–20 representative tasks and define a clear pass condition.
- 2
Lock the agent, model, tools, permissions, and budget before testing.
- 3
Run each important task more than once; record success, cost, time, and takeovers.
- 4
Review failures and data-handling risks before a production decision.