Claude Opus 5 vs Ripple-65B Preview
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Winner
Claude Opus 5
Claude Opus 5 wins this comparison with an overall score of 95 vs 45 for Ripple-65B Preview, leading 5 of 5 shared benchmarks.
Claude Opus 5
95.4
Ripple-65B Preview
45.2
Based on 5 of 70 benchmarks scored by all 2 selected models.
Benchmark Scores Comparison
Claude Opus 5
Ripple-65B Preview
Claude Opus 5
Score: 40.0
Ripple-65B Preview
65.0B params
Coverage matrix
2 models × 70 benchmarks — hover a benchmark name for its category
Shading = score relative to the best score among the selected models:
Low
Mid
High
Missing (—)
The totals row shows how many of the 70 benchmarks each model has scores for.
| Benchmark | Ripple-65B Preview Ricursive Intelligence | Claude Opus 5 Anthropic |
|---|---|---|
| GPQA Diamond | 85.2 | 93.7 |
| ArXivMath | — | 71.5 |
| Hy-LifeSearch (Internal) | — | 56.1 |
| Automation-Bench | — | 48.7 |
| SWE-bench Pro | 61.42 | 79.2 |
| BioMysteryBench | — | 72.1 |
| AA-LCR | 75 | — |
| AIME 26 | 95 | — |
| Agents' Last Exam | — | 25.1 |
| Toolathlon Verified | — | 76.5 |
| Hy-Backend 2.0 (Internal) | — | 40.3 |
| Hy-SWE Max Verified (Internal) | — | 70.1 |
| Hy-BrowseComp-Pro2 (Internal) | — | 61.3 |
| AutomationBench (Public) | 36.4 | — |
| OfficeQA Pro | — | 66.9 |
| StrongREJECT v2 (adaptive) | 97.5 | — |
| SWE Atlas - TW | — | 68.7 |
| LOCA-Bench (256k) | — | 53.7 |
| SWE-bench Pro v2.0 Hard | 79.1 | — |
| SWE Atlas - QnA | — | 57.5 |
| NL2Repo | — | 75.3 |
| PostTrainBench | — | 35 |
| BabyVision | — | 94.1 |
| Apex-Agents | — | 41.8 |
| WorkSpaceBench | — | 75 |
| MMLU-Pro | 84.2 | — |
| BankerToolBench | — | 81.9 |
| E-Bench-Code (Internal) | — | 82.7 |
| HLE (with tools) | — | 60.9 |
| CharXiv (RQ) | — | 83.7 |
| GDP.pdf | — | 21.6 |
| AIME 2024 | 97.1 | — |
| CritPt (no tools) | — | 29.1 |
| NL2Repo-Bench | — | 75.3 |
| DRACO | — | 88.6 |
| SWE-bench Multilingual | — | 89.5 |
| MMLU | 89.6 | — |
| Hy-FinAgentBench (Internal) | — | 82 |
| IFBench | 79.2 | — |
| SWE-bench Verified | 76.5 | — |
| Humanity's Last Exam | — | 54.9 |
| SUPERChem | — | 76.7 |
| HorizonMath (pass@4) | — | 5.3 |
| Terminal-Bench 2.1 (Terminus-2) | 80.5 | 86.7 |
| DeepSWE | — | 68.8 |
| BrokenArXiv | — | 77.7 |
| HMMT Feb 26 | 90.5 | — |
| Hy-FinmodelBench v2 (Internal) | — | 66 |
| MathArena Apex 2025 | — | 91.4 |
| Terminal Bench 2.1 | 80.5 | — |
| AIME 2025 | 98.3 | — |
| JobBench | — | 68 |
| $OneMillion-Bench | — | 68.1 |
| OSWorld 2.0 (Binary) | — | 70.6 |
| WideSearch | — | 84 |
| SkillsBench Avg5 | — | 63.7 |
| TauBench V3 Banking | 31.27 | — |
| E-Bench (Internal) | — | 77.8 |
| ProgramBench | — | 39.5 |
| MCP-Atlas | 71.67 | 85.7 |
| SWE-Marathon | — | 50 |
| Terminal-Bench 4.0 | — | 51.8 |
| SWE Atlas - RF | — | 60 |
| DeepSWE 1.1 | 44.3 | 74 |
| FORTRESS Benign | 95.5 | — |
| Hy-CompanyBench V2 (Internal) | — | 72.7 |
| Harbor-Index | — | 56.9 |
| SWE Refactor Bench | — | 31 |
| SciCode | 39.4 | — |
| GDPVal-AA v2 | — | 1831 |
| Covered | 21/70 | 54/70 |
Scorecard
Overall 0–100 score — category strengths (50%), shared-benchmark wins (30%), coverage (20%)
| Model | Overall score | Shared benchmark wins | Coverage | Strongest at | Weakest at |
|---|---|---|---|---|---|
| Claude Opus 5 Winner | 95.4 | 5 of 5 | 54 of 70 (77.0%) | STEM & Reasoning | Agentic Coding |
| Ripple-65B Preview | 45.2 | 0 of 5 | 21 of 70 (30.0%) | STEM & Reasoning | Agentic Coding |
Category strengths
Where each model stands, per benchmark category — score relative to the best model, adjusted for benchmark coverage. This also ranks models when they share few benchmarks.
| Category | Claude Opus 5 | Ripple-65B Preview |
|---|---|---|
| Agentic Coding 23 benchmarks | 100 | 76 |
| General Agents 19 benchmarks | 100 | 80.8 |
| STEM & Reasoning 14 benchmarks | 100 | 83.7 |
Fully comparable benchmarks
Scored by all 2 selected models (5)
| Benchmark | Category | Claude Opus 5 | Ripple-65B Preview |
|---|---|---|---|
| GPQA Diamond | stem_reasoning | 93.7 | 85.2 |
| SWE-bench Pro | coding_agent | 79.2 | 61.42 |
| Terminal-Bench 2.1 (Terminus-2) | coding_agent | 86.7 | 80.5 |
| MCP-Atlas | general_agent | 85.7 | 71.67 |
| DeepSWE 1.1 | coding_agent | 74 | 44.3 |
Partial coverage benchmarks
Scored by at least one but not all selected models (65) — missing scores show as —
| Benchmark | Category | Claude Opus 5 | Ripple-65B Preview |
|---|---|---|---|
| ArXivMath 1/2 models | stem_reasoning | 71.5 | — |
| Hy-LifeSearch (Internal) 1/2 models | general_agent | 56.1 | — |
| Automation-Bench 1/2 models | general_agent | 48.7 | — |
| BioMysteryBench 1/2 models | stem_reasoning | 72.1 | — |
| AA-LCR 1/2 models | long_context | — | 75 |
| AIME 26 1/2 models | stem_reasoning | — | 95 |
| Agents' Last Exam 1/2 models | general_agent | 25.1 | — |
| Toolathlon Verified 1/2 models | general_agent | 76.5 | — |
| Hy-Backend 2.0 (Internal) 1/2 models | coding_agent | 40.3 | — |
| Hy-SWE Max Verified (Internal) 1/2 models | coding_agent | 70.1 | — |
| Hy-BrowseComp-Pro2 (Internal) 1/2 models | general_agent | 61.3 | — |
| AutomationBench (Public) 1/2 models | general_agent | — | 36.4 |
| OfficeQA Pro 1/2 models | general_agent | 66.9 | — |
| StrongREJECT v2 (adaptive) 1/2 models | safety | — | 97.5 |
| SWE Atlas - TW 1/2 models | coding_agent | 68.7 | — |
| LOCA-Bench (256k) 1/2 models | long_context | 53.7 | — |
| SWE-bench Pro v2.0 Hard 1/2 models | coding_agent | — | 79.1 |
| SWE Atlas - QnA 1/2 models | coding_agent | 57.5 | — |
| NL2Repo 1/2 models | coding_agent | 75.3 | — |
| PostTrainBench 1/2 models | coding_agent | 35 | — |
| BabyVision 1/2 models | vision_language | 94.1 | — |
| Apex-Agents 1/2 models | general_agent | 41.8 | — |
| WorkSpaceBench 1/2 models | general_agent | 75 | — |
| MMLU-Pro 1/2 models | knowledge | — | 84.2 |
| BankerToolBench 1/2 models | general_agent | 81.9 | — |
| E-Bench-Code (Internal) 1/2 models | coding_agent | 82.7 | — |
| HLE (with tools) 1/2 models | stem_reasoning | 60.9 | — |
| CharXiv (RQ) 1/2 models | document_understanding | 83.7 | — |
| GDP.pdf 1/2 models | long_context | 21.6 | — |
| AIME 2024 1/2 models | stem_reasoning | — | 97.1 |
| CritPt (no tools) 1/2 models | stem_reasoning | 29.1 | — |
| NL2Repo-Bench 1/2 models | coding_agent | 75.3 | — |
| DRACO 1/2 models | general_agent | 88.6 | — |
| SWE-bench Multilingual 1/2 models | coding_agent | 89.5 | — |
| MMLU 1/2 models | knowledge | — | 89.6 |
| Hy-FinAgentBench (Internal) 1/2 models | domain_finance | 82 | — |
| IFBench 1/2 models | instruction_following | — | 79.2 |
| SWE-bench Verified 1/2 models | coding_agent | — | 76.5 |
| Humanity's Last Exam 1/2 models | stem_reasoning | 54.9 | — |
| SUPERChem 1/2 models | stem_reasoning | 76.7 | — |
| HorizonMath (pass@4) 1/2 models | stem_reasoning | 5.3 | — |
| DeepSWE 1/2 models | coding_agent | 68.8 | — |
| BrokenArXiv 1/2 models | stem_reasoning | 77.7 | — |
| HMMT Feb 26 1/2 models | stem_reasoning | — | 90.5 |
| Hy-FinmodelBench v2 (Internal) 1/2 models | domain_finance | 66 | — |
| MathArena Apex 2025 1/2 models | stem_reasoning | 91.4 | — |
| Terminal Bench 2.1 1/2 models | coding_agent | — | 80.5 |
| AIME 2025 1/2 models | stem_reasoning | — | 98.3 |
| JobBench 1/2 models | general_agent | 68 | — |
| $OneMillion-Bench 1/2 models | general_capabilities | 68.1 | — |
| OSWorld 2.0 (Binary) 1/2 models | general_agent | 70.6 | — |
| WideSearch 1/2 models | general_agent | 84 | — |
| SkillsBench Avg5 1/2 models | coding_agent | 63.7 | — |
| TauBench V3 Banking 1/2 models | general_agent | — | 31.27 |
| E-Bench (Internal) 1/2 models | general_agent | 77.8 | — |
| ProgramBench 1/2 models | coding_agent | 39.5 | — |
| SWE-Marathon 1/2 models | coding_agent | 50 | — |
| Terminal-Bench 4.0 1/2 models | coding_agent | 51.8 | — |
| SWE Atlas - RF 1/2 models | coding_agent | 60 | — |
| FORTRESS Benign 1/2 models | safety | — | 95.5 |
| Hy-CompanyBench V2 (Internal) 1/2 models | general_agent | 72.7 | — |
| Harbor-Index 1/2 models | coding_agent | 56.9 | — |
| SWE Refactor Bench 1/2 models | coding_agent | 31 | — |
| SciCode 1/2 models | — | — | 39.4 |
| GDPVal-AA v2 1/2 models | general_agent | 1831 | — |
Comparison FAQ
Which model is better, Claude Opus 5 or Ripple-65B Preview?
Claude Opus 5 wins this comparison with an overall score of 95 vs 45 for Ripple-65B Preview, leading 5 of 5 shared benchmarks.
Which model is better at Agentic Coding, Claude Opus 5 or Ripple-65B Preview?
Claude Opus 5 leads the Agentic Coding category (strength score 100/100 across 3 comparable benchmarks).
How reliable is this comparison verdict?
Based on 5 of 70 benchmarks scored by all 2 selected models.