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coding benchmarks

8 articles · Page 1 of 1
Machine Heart
Machine Heart
Oct 22, 2026 · Artificial Intelligence

Flint-40B-A2B: AI-Built MoE Coding Model Hits 125 tok/s on MacBook Pro

Recursive_SI's first model Flint-40B-A2B, a 40B MoE model activating 2.5B parameters per token, was built in under four months using the automated Eureka Machine system. It achieves state-of-the-art local coding performance on benchmarks like SWE-Bench while running at 125+ tokens/sec on MacBook Pro M4 Pro and 150+ tokens/sec on NVIDIA RTX Spark, with open weights on Hugging Face under Apache 2.0.

Apple SiliconEureka MachineFlint-40B-A2B
0 likes · 10 min read
Flint-40B-A2B: AI-Built MoE Coding Model Hits 125 tok/s on MacBook Pro
Top Architect
Top Architect
Oct 18, 2026 · Artificial Intelligence

Google Releases Three Gemini Models, Begins 'Most Aggressive' Gemini 4 Training

Google DeepMind released three new Gemini models—3.6 Flash with 65% token reduction, 3.5 Flash-Lite outperforming its larger sibling at lower cost, and 3.5 Flash Cyber for vulnerability detection—while confirming the start of pre-training for Gemini 4, signaling continued rapid advancement in production-ready AI agents.

AI AgentsGeminiGoogle DeepMind
0 likes · 8 min read
Google Releases Three Gemini Models, Begins 'Most Aggressive' Gemini 4 Training
AI Engineering
AI Engineering
Apr 22, 2026 · Artificial Intelligence

Qwen3.6-27B Runs Locally on 18 GB RAM and Outperforms a 397 B‑Parameter Model

Alibaba’s open‑source Qwen3.6‑27B model can be run on consumer hardware with as little as 18 GB of RAM using 4‑bit quantization, and its hybrid attention architecture delivers higher accuracy on coding benchmarks such as Terminal‑Bench 2.0 and SWE‑bench Pro than the much larger 397‑B‑parameter Qwen3.5‑397B‑A17B MoE model.

4-bit quantizationLLMQwen3.6-27B
0 likes · 5 min read
Qwen3.6-27B Runs Locally on 18 GB RAM and Outperforms a 397 B‑Parameter Model
Node.js Tech Stack
Node.js Tech Stack
Apr 8, 2026 · Artificial Intelligence

Anthropic’s Mythos Preview Crushes Opus 4.6 and Remains Unreleased

Anthropic introduced the Mythos Preview model, which outperforms its flagship Opus 4.6 across coding benchmarks and uncovers thousands of high‑severity security bugs, yet the company keeps the model private and launches a $100 million Project Glasswing initiative with major tech partners to secure critical software.

AI securityAnthropicLarge Language Models
0 likes · 9 min read
Anthropic’s Mythos Preview Crushes Opus 4.6 and Remains Unreleased
PaperAgent
PaperAgent
Dec 12, 2025 · Artificial Intelligence

What Makes GPT‑5.2 and Gemini‑3‑Pro So Fast? Inside Their Key Features and Real‑World Tests

Gemini‑3‑pro’s surprise debut and OpenAI’s emergency release of GPT‑5.2 highlight a shift toward faster inference, deeper reasoning, and lower hallucination rates, with detailed performance metrics, three‑tier model options, extended context windows, and mixed community test results that reveal both strengths and shortcomings.

AI model performanceGPT-5.2Gemini 3 Pro
0 likes · 4 min read
What Makes GPT‑5.2 and Gemini‑3‑Pro So Fast? Inside Their Key Features and Real‑World Tests