Observed Signal · Jul 9, 2026 · Technical Release · Source: DEV Community · Impact: 2/5 · Sentiment: Positive
Mitii Agent Scores 78% on 515-Task Local LLM Benchmark
An author benchmarked Mitii, an AI coding assistant with a multi-mode architecture, on 515 adversarial and real-world coding tasks. Running entirely locally with qwen3-coder:30b via the Ollama runtime, Mitii passed 400 tasks (78%). The system processed ~4.8 million tokens (avg ~9,329 tokens/task). Mitii offers three interaction modes (Agent, Plan, Ask); Ask Mode achieved an 87% win rate on hard tasks. The benchmark highlights local LLM viability for private, secure coding agents while noting areas for improvement such as semantic retrieval (63%) and medium-difficulty routing.
Shows a practical, private/local LLM deployment for agentic coding with strong security and adversarial robustness—relevant to organizations seeking private AI tooling, but it's a niche benchmark rather than an industry-wide platform change.
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Key Takeaways & Evidence Grounding
- Mitii is an AI coding assistant with a multi-mode architecture (Agent, Plan, Ask).
- The benchmark ran 515 distinct tasks and Mitii passed 400 tasks (78% overall pass rate).
- Mitii was powered locally by qwen3-coder:30b running via the Ollama runtime.
- Total tokens processed were approximately 4.8 million, with an average of ~9,329 tokens per task.
- Ask Mode achieved an 87% win rate on Hard tasks; security-related hard tasks reached an 87% pass rate (45/52).
Connected Companies & Entities
1 Entity mapped“For this gauntlet, I powered Mitii using qwen3-coder:30b running locally via Ollama....”
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