coding model
6 articles tagged with coding model
Recursive releases Flint, a 40B-parameter open coding model that runs on laptops under Apache 2.0
Recursive released Flint, a free, open-weight mixture-of-experts coding model with 40 billion total and 2.5 billion active parameters, under Apache 2.0. The company claims its Eureka Machine automated research system contributed to nearly every stage of development, and that Flint runs at about 131 tokens per second on an M4 Pro MacBook Pro.
Z.ai Releases GLM-5.3-Prime, a High-Throughput Variant of GLM-5.3 with 1M-Token Context
Z.ai has released GLM-5.3-Prime, a high-speed variant of its GLM-5.3 model that delivers 1.5-2x the output throughput through inference acceleration while retaining the full 1M-token context window. The model is priced at $2.80 per 1M input tokens and $8.80 per 1M output tokens, targeting coding and long-horizon agentic workloads.
Z.ai Releases GLM-5.3 with 1M-Token Context and Always-On Reasoning
Z.ai has released GLM-5.3, a large-scale reasoning model aimed at software engineering and long-horizon agent tasks, featuring a 1M-token context window and mandatory reasoning that cannot be disabled. The model is priced at $1.40 per 1M input tokens and $4.40 per 1M output tokens on OpenRouter.
Zhipu AI Releases GLM-5.3, Claims It's the Strongest Open-Weights Coding Model
Zhipu AI has released GLM-5.3, a coding-focused model built on the same base as GLM-5.2 with additional post-training. The company claims it's the strongest open-weights coding model available, with gains concentrated in agentic and cybersecurity tasks, though independent benchmarks are not yet published.
ByteDance Seed Launches Seed-2.0-Code With 262K Context Window for Agentic Coding
ByteDance Seed has released Seed-2.0-Code, a model optimized for agentic coding workflows with a 262K token context window. The model accepts text, image, and video input and is priced at $0.50 per million input tokens and $3.00 per million output tokens.
Moonshot AI releases Kimi K2.7 Code with 1T parameters, 256K context window, 30% lower thinking token usage
Moonshot AI has released Kimi K2.7 Code, a 1 trillion parameter Mixture-of-Experts model designed for long-horizon coding tasks. The model features a 256K context window and reduces thinking token usage by approximately 30% compared to its predecessor K2.6.