Flint
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Headlines · 8
- Transformers v5.21.0 Adds OCR, MoE, Vision and TTS Models
Transformers v5.21.0 adds support for OpenBMB’s MiniCPM-OCR document-understanding model, Recursive’s Flint mixture-of-experts language model, UltraVBert for visual document understanding and retrieval, Gradium Phonon TTS and Kyutai’s Pocket TTS. The release notes describe MiniCPM-OCR as specialized for text-dense images such as scanned pages, screenshots, receipts and tables. Quantization changes address DeepSeek-V4.1’s FP4 experts and prevent TimesFM 2.5 from casting float inputs to integer weight dtypes when loaded with 4-bit or 8-bit quantization. The release also includes bug fixes and infrastructure updates.
Transformers Releases · 🔥 0 - Ollama v0.40.9 expands Flint support and improves AI request handling
Ollama v0.40.9 adds support for running Flint on Linux and Windows, joining its existing macOS availability. The release also improves streaming error reporting for OpenAI Responses and Anthropic Messages, passes cloud-model context lengths and capabilities to coding tools, and applies supported thinking settings to follow-up Anthropic-compatible web searches.
Ollama Releases · 🔥 0 - Microsoft Research details Flint-interactive for interactive visualizations
Microsoft Research describes Flint-interactive, a language for creating interactive data visualizations on top of Flint. Users and AI agents can define behaviors through high-level semantic events and update operators, while Flint’s compiler manages interaction logic, visual dependencies, hit testing and rendering. The report says the system supports clicking, filtering, zooming, highlighting and linked interactions across charts, text, tables and application widgets. Microsoft Research also claims the approach can reduce layout, rendering and debugging problems and lower development effort, but the supplied report provides no independent validation.
Microsoft Research Blog · 🔥 0 - Kapitsa adds Flint support, claims SOTA Apple Silicon decode
A contributor to Kapitsa, an open-source inference engine written with custom Metal kernels and targeted at Apple Silicon from M1 through M6, posted that the project (version 0.2.7) has added support for Recursive's newly released Flint model, which Recursive says is optimized for coding on Macs with 32GB or more and beats Qwen's 35B sparse MoEs while nearing Qwen's 27B dense model. On a single MacBook Pro M4 Pro with 48GB, the contributor's own benchmarks put Kapitsa at 127.9 tok/s short-context decode versus 126.6 for Recursive's rec 0.1.0 and 79.6 for llama.cpp b11804, with Kapitsa's lead over rec growing from 1.06x at 8K context to 1.30x at 128K. The author notes only one Mac was tested, that Flint has not been run on an M5, that prefill on M5+ is not yet optimized, and that a KFlash tree drafter trained on eight H200s for Flint Q4, claimed to give an internal 1.4x decode speedup without accuracy loss, is due Monday; running it requires a Mac with at least 32GB and a 22.6GB download.
r/LocalLLaMA · 🔥 0 - Flint MoE model support merged into llama.cpp, Reddit post says
A post on r/LocalLLaMA says a pull request adding Flint (FlintForCausalLM) support to llama.cpp, PR #30928 in the ggml-org repository, was merged after about six hours. The post describes Flint as a decoder-only mixture-of-experts Transformer from developer Recursive with 39.8B total parameters and roughly 2.5B active parameters per token including the output head, spread over 49 layers — 2 dense followed by 47 MoE layers. It lists 256 routed experts with 6 selected per token plus an always-active shared expert, 35 sliding-window and 14 full-attention layers, a documented context configuration of 262,144 tokens, and a stated knowledge cutoff of June 2026; these details come from the post alone and have not been independently confirmed.
r/LocalLLaMA · 🔥 0 - Recursive releases the open-weight Flint local coding model
Recursive released Flint, an Apache 2.0-licensed mixture-of-experts model with 40 billion total parameters and 2.5 billion active parameters per token, optimized for coding agents on local hardware. Recursive says its Eureka Machine automated most of the development pipeline, while reported benchmark and speed figures are based on the company’s own tests.
WIRED AI · 🔥 0 - Ollama v0.40.8 adds Recursive's Flint coding model with 262K context
Ollama release v0.40.8 brings Recursive's Flint coding model into its model library, runnable with the command ollama run flint. According to the changelog, Flint is designed for repository-scale coding-agent work such as understanding unfamiliar code, tracing bugs, implementing features and adding tests, aided by reasoning, multi-turn tool use and a 262K-token context window. The model is described as an Apache 2.0-licensed 40B-parameter mixture-of-experts with roughly 2.5B parameters active per token, and Recursive's own release evaluations report 54.9% on Terminal-Bench 2.1 and 74.2% on SWE-bench Verified; Ollama notes Flint is currently supported on macOS, with other GPU support to follow in a later release.
Ollama Releases · 🔥 0 - vLLM adds day-0 support for Recursive's Flint 40B MoE
vLLM said it supports Recursive's Flint from day 0, with both the NVFP4 and BF16 checkpoints running on a single GPU. Flint is a 40B-parameter mixture-of-experts model that activates about 2.5B parameters per token, uses sliding-window attention in most of its 49 layers and carries a 262K-token context. vLLM reports that a single request decodes at roughly 500 tokens/s on one GB200 even with 100K tokens of context, and that its Flint-specific kernels cut NVFP4 decode from 4.81 ms to 1.78 ms and reduced a forward pass from 1,096 kernels to 346.
vLLM Blog · 🔥 0
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