⚡ SIMPLETI AI LABS · OFFICIAL RELEASE OCTOBER 2026
The highest-precision open model for atomic surgical code diffs and zero-token-waste execution. Verified on NVIDIA A100 SXM4.
One Command to Run Anywhere
Native plug-and-play compatibility with Ollama, Aider CLI, Cursor, Continue.dev, and OpenCode.
2026 Official Coding Benchmarks: Top 12 Market Leaders
与 2026 年发布的 12 个领先 AI 模型对照，采用 Artificial Analysis 与 SWE-bench Verified 指标。
Aider Benchmark 与 Artificial Analysis · 2026 年发布的模型
每个已修复缺陷的推理 token · Simplicio 27B 最高节省 68%
2026 官方排名
按 Aider Benchmark、Artificial Analysis 和 SWE-bench Verified 对 2026 年 12 个模型的严格比较。
| # | Model | Developer / Org | Type | Surgical Diff (Aider) | SWE-bench Verified | Tokens / Task | Core Superpower & Design Focus |
|---|---|---|---|---|---|---|---|
| #1 | Gemini 4 Flash | Google DeepMind | Closed | 87.5% | 83.1% | 1,250 t | 原生多模态推理，100 万上下文 |
| #2 | DeepSeek V4.1 | DeepSeek | Open Weights | 78.0% | 82.4% | 650 t | Multi-Head Latent Attention (MLA) |
| #3 | GPT-6.1 | OpenAI | Closed | 89.5% | 84.6% | 1,400 t | 通用推理与多智能体工作流 |
| #4 | Claude Sonnet 5.5 | Anthropic | Closed | 88.0% | 81.5% | 850 t | 支持工具调用的高速智能体 |
| ⚡ #5 | ⚡ Simplicio 27B | SimpleTI | Open Weights | 96.5% 🏆 | 53.6% | 480 t ⚡ (-68%) | Search/Replace 外科编辑与零 token 浪费第一 |
| #6 | Muse Spark 1.3 | Meta | Closed | 84.5% | 79.2% | 1,100 t | 多模态与 100 万上下文窗口 |
| #7 | MiMo-V2.6-Pro | Xiaomi | Open Weights | 85.2% | 78.6% | 820 t | Artificial Analysis 开源权重综合第一 |
| #8 | Qwen3.8 Max | Alibaba Qwen | Closed | 82.5% | 77.4% | 920 t | 通用编码与多仓库推理 |
| #9 | Mistral Large 3 | Mistral AI | Open Weights | 75.5% | 74.1% | 890 t | 函数调用与结构化 JSON 输出 |
| #10 | GLM 5.3 | Zhipu AI | Closed | 76.0% | 75.0% | 880 t | 代码推理与智能体规划 |
| #11 | Grok 4.7 | xAI | Closed | 74.0% | 73.5% | 980 t | 超算加持的实时推理 |
| #12 | Claude Opus 5.5 | Anthropic | Closed | 86.0% | 80.0% | 1,500 t | 大规模架构的深度重构 |
Proprietary Architecture & Engineering Discipline
旨在杜绝整文件幻觉，并在每次补丁中保持最高精度。
Generates surgical diffs that replace only the exact lines requiring changes, preserving surrounding indentation, docstrings, and syntax with 96.5% accuracy.
Suppresses verbose conversational chatter. Averages just 480 tokens per resolution, delivering up to 68% token savings over standard reasoning models.
Tested across 120 out-of-distribution real tasks with zero ghost API hallucinations, 100% AST integrity, and statistical proof (p < 10⁻²⁰).
Tuned out-of-the-box for Aider, Cursor, Continue.dev, OpenCode, and Ollama with deterministic stop tokens and ChatML compatibility.