Kimi K3 vs Ripple-65B Preview
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Benchmark Scores Comparison
Kimi K3
Ripple-65B Preview
Kimi K3
Score: 15.0
Ripple-65B Preview
65.0B params
Coverage matrix
2 models × 27 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 27 benchmarks each model has scores for.
| Benchmark | Ripple-65B Preview Ricursive Intelligence | Kimi K3 Moonshot AI |
|---|---|---|
| GPQA Diamond | 85.2 | — |
| SWE-bench Pro | 61.42 | — |
| AA-LCR | 75 | — |
| AIME 26 | 95 | — |
| WMDP (Bio) | — | 89.1 |
| AutomationBench (Public) | 36.4 | — |
| StrongREJECT v2 (adaptive) | 97.5 | — |
| SWE-bench Pro v2.0 Hard | 79.1 | — |
| HPCT | — | 59.6 |
| MMLU-Pro | 84.2 | — |
| AIME 2024 | 97.1 | — |
| Lab Bench (ProtocolQA) | — | 81.9 |
| MMLU | 89.6 | — |
| IFBench | 79.2 | — |
| SWE-bench Verified | 76.5 | — |
| WMDP (Chem) | — | 84.2 |
| Terminal-Bench 2.1 (Terminus-2) | 80.5 | — |
| HMMT Feb 26 | 90.5 | — |
| Terminal Bench 2.1 | 80.5 | — |
| AIME 2025 | 98.3 | — |
| TauBench V3 Banking | 31.27 | — |
| MCP-Atlas | 71.67 | — |
| DeepSWE 1.1 | 44.3 | — |
| FORTRESS Benign | 95.5 | — |
| MBCT | — | 58.9 |
| VCT | — | 48 |
| SciCode | 39.4 | — |
| Covered | 21/27 | 6/27 |
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 |
|---|---|---|---|---|---|
| Ripple-65B Preview | 77.8 | — | 21 of 27 (78.0%) | — | — |
| Kimi K3 | 22.2 | — | 6 of 27 (22.0%) | — | — |
Partial coverage benchmarks
Scored by at least one but not all selected models (27) — missing scores show as —
| Benchmark | Category | Kimi K3 | Ripple-65B Preview |
|---|---|---|---|
| GPQA Diamond 1/2 models | stem_reasoning | — | 85.2 |
| SWE-bench Pro 1/2 models | coding_agent | — | 61.42 |
| AA-LCR 1/2 models | long_context | — | 75 |
| AIME 26 1/2 models | stem_reasoning | — | 95 |
| WMDP (Bio) 1/2 models | safety | 89.1 | — |
| AutomationBench (Public) 1/2 models | general_agent | — | 36.4 |
| StrongREJECT v2 (adaptive) 1/2 models | safety | — | 97.5 |
| SWE-bench Pro v2.0 Hard 1/2 models | coding_agent | — | 79.1 |
| HPCT 1/2 models | safety | 59.6 | — |
| MMLU-Pro 1/2 models | knowledge | — | 84.2 |
| AIME 2024 1/2 models | stem_reasoning | — | 97.1 |
| Lab Bench (ProtocolQA) 1/2 models | safety | 81.9 | — |
| MMLU 1/2 models | knowledge | — | 89.6 |
| IFBench 1/2 models | instruction_following | — | 79.2 |
| SWE-bench Verified 1/2 models | coding_agent | — | 76.5 |
| WMDP (Chem) 1/2 models | safety | 84.2 | — |
| Terminal-Bench 2.1 (Terminus-2) 1/2 models | coding_agent | — | 80.5 |
| HMMT Feb 26 1/2 models | stem_reasoning | — | 90.5 |
| Terminal Bench 2.1 1/2 models | coding_agent | — | 80.5 |
| AIME 2025 1/2 models | stem_reasoning | — | 98.3 |
| TauBench V3 Banking 1/2 models | general_agent | — | 31.27 |
| MCP-Atlas 1/2 models | general_agent | — | 71.67 |
| DeepSWE 1.1 1/2 models | coding_agent | — | 44.3 |
| FORTRESS Benign 1/2 models | safety | — | 95.5 |
| MBCT 1/2 models | safety | 58.9 | — |
| VCT 1/2 models | safety | 48 | — |
| SciCode 1/2 models | — | — | 39.4 |