⚡ 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
2026年に公開された主要12モデルと、Artificial Analysis および SWE-bench Verified の指標で比較。
Aider Benchmark & Artificial Analysis · 2026年公開モデル
解決したバグあたりの推論トークン · Simplicio 27B は最大68%削減
2026 公式ランキング
Aider Benchmark、Artificial Analysis、SWE-bench Verified に基づく2026年12モデルの厳密な比較。
| # | 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 | 100万コンテキストのネイティブマルチモーダル推論 |
| #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 | 一般推論とマルチエージェントワークフロー |
| #4 | Claude Sonnet 5.5 | Anthropic | Closed | 88.0% | 81.5% | 850 t | ツール使用対応の高速エージェント |
| ⚡ #5 | ⚡ Simplicio 27B | SimpleTI | Open Weights | 96.5% 🏆 | 53.6% | 480 t ⚡ (-68%) | Search/Replace の外科的編集とトークン浪費ゼロで第1位 |
| #6 | Muse Spark 1.3 | Meta | Closed | 84.5% | 79.2% | 1,100 t | マルチモーダルと100万トークンのコンテキスト |
| #7 | MiMo-V2.6-Pro | Xiaomi | Open Weights | 85.2% | 78.6% | 820 t | Artificial Analysis のオープンウェイト総合1位 |
| #8 | Qwen3.8 Max | Alibaba Qwen | Closed | 82.5% | 77.4% | 920 t | 一般コーディングと複数リポジトリ推論 |
| #9 | Mistral Large 3 | Mistral AI | Open Weights | 75.5% | 74.1% | 890 t | 関数呼び出しと構造化JSON出力 |
| #10 | GLM 5.3 | Zhipu AI | Closed | 76.0% | 75.0% | 880 t | コード推論とエージェント計画 |
| #11 | Grok 4.7 | xAI | Closed | 74.0% | 73.5% | 980 t | スーパーコンピューティングによるリアルタイム推論 |
| #12 | Claude Opus 5.5 | Anthropic | Closed | 86.0% | 80.0% | 1,500 t | 大規模アーキテクチャの深いリファクタリング |
Proprietary Architecture & Engineering Discipline
ファイル全体の幻覚を止め、すべてのパッチで最大精度を保つための設計。
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.