We're excited to bring you Flint by @Recursive_SI in LM Studio on day 0!
• 40B MoE, 2.5B active
• 262K token context window
• Apache 2.0
• Trained for local agentic coding model
Requires about 24GB to run locally on your machine, performs impressively on benchmarks.
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine.
• Best-in-class fast local coding
• Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark
• Built from
DeepSeek-V4.1-Flash-1017 is now live in LM Studio Bionic!
1M context • image input • highly cost effective
US-hosted with full ZDR.
Try it out for coding tasks!
🚀 DeepSeek-V4.1-Flash-1017 is here!
Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy,
