Model Releases
I collected every single LLM coding benchmark, and computed their Intelligence Density
The intelligence in my context is an aggregate index, I called the Agentic Coding Index, across most relevant agentic coding benchmarks: SWE-bench Pro, DeepSWE v1.1, Terminal-Bench (v4, v3, v2.1), Cod
The intelligence in my context is an aggregate index, I called the Agentic Coding Index, across most relevant agentic coding benchmarks: SWE-bench Pro, DeepSWE v1.1, Terminal-Bench (v4, v3, v2.1), Code Arena Elo, and LiveCodeBench v6. Intelligence/Parameter=Scale x (Agentic Index / Norm) ^ (Super_Linear_Exponent) / sqrt(PCount + PLowerBound) Norm: sets a neutral baseline (= 50). Super_Linear_Exponent: non-linear scale to avoid rewarding very small models (otherwise, small models that can barely write code would artificially dominate the leaderboard), while rewarding true autonomous mastery. Scale = 2.5354. PCount: model parameter count (in Billions). PLowerBound: minimum count of model parameters (regularization term, to avoid models <1B shooting up the score), =8B. Agentic Coding Index: DeepSWE v1.1 (20%), Code Arena Elo (20%), Terminal-Bench v4.0 (15%), SWE-bench Pro (15%), Terminal-Bench v3.0 (13%), Terminal-Bench v2.1 (12%), and LiveCodeBench v6 (5%). Data Integrity: All benchmark scores are curated from verified public and official sources (model creators, peer-reviewed evaluation reports). submitted by /u/Informal-Trouble2183 [link] [comments]
Related
- DeepSeek v4 Flash has a nice bump in Capability
- Deepseek V4 flash - Hy3 or is Qwen3.6 27B still the most solid for agentic/coding?
- DeepSeek v4 Flash vs. Qwen3.6-27B, 3.5-122B, and Gemma 4 31B Benchmark
- DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks
- Local agentic coding Benchmark : Qwen 3.8 27B (in many weights quants / cache quants / engine / reasoning effort) vs others.
Source: r/LocalLLaMA | 2026-08-30