Rnj-1 is an 8B-parameter, dense, open-weight model family developed by Essential AI and trained from scratch with a focus on programming, math, and scientific reasoning. The model demonstrates strong performance across multiple programming languages, tool-use workflows, and agentic execution environments (e.g., mini-SWE-agent).
| 信号 | 强度 | 权重 | 影响 |
|---|---|---|---|
| Capabilitiesjust now | 50 | 30% | +15.0 |
| Recencyjust now | 100 | 15% | +15.0 |
| Context Windowjust now | 72 | 15% | +10.7 |
| Output Capacityjust now | 20 | 15% | +3.0 |
| Pricingjust now | 0 | 25% | +0.0 |
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成本估算器
每月比类别平均节省$41.04