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Building AIβs unified compute layer. We are hiring β modular.com/careers π
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Our Developer Advocate @dunn_oconnor wrote about the elephant in the room at the 2026 @llvmorg Developers' Meeting: the challenge of building durable open-source architecture in the agentic era. This was a major theme across talks, and Michael argues that it's a significant opportunity for MAX and Mojo: modular.com/blog/llvm-dev-β¦
www.modular.com Modular: LLVM Dev Meeting 2026: Durable Infrastructure in the Agentic Era Kristofβs exploration of the question also revealed a lot about the future of open source software projects. Kristof argued that durable open source projects depend on three things: communicating... LFM3 from @liquidai is now running on MAX. π§βπ
All 6 models in the suite are supported, across text, audio, vision, and omni. The implementations are open source, so you can read the code, run it, and build on it: max.modular.com/api/python/pipβ¦
Which modality are you trying first: text, audio, vision, or omni?
All 6 models in the suite are supported, across text, audio, vision, and omni. The implementations are open source, so you can read the code, run it, and build on it: max.modular.com/api/python/pipβ¦
Which modality are you trying first: text, audio, vision, or omni?
max.modular.com max.pipelines.architectures.lfm3 | MAX LiquidAI LFM3 models on ModuleV3. Introducing π»π΅πΌπΉ: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence.
> 6 model instances, across text, audio, vision, and omni modalities, generative and decision models.
> π»π΅πΌπΉ-π·.π½π±: text, 256k context window.
> π»π΅πΌπΉ-π π»-πΈπ±: vision-language model with video-input support for spatial understanding
> π»π΅πΌπΉ-π°ππππ-πΈπ±: tool calls, voice chat, reasoning in 18 languages.
> π»π΅πΌπΉ-πΎπππ-πΈπ±: an omni model combines vision, audio, and language.
> ππ·-πΈπ± and ππ·-πΎπππ-πΈπ±: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input.
> fine-tune on 1 GPU.
> a new tri-hybrid architecture
> architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs.
> π»π΅πΌπΉ-π π»-πΈπ± is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters.
> π»π΅πΌπΉ-π·.π½π± is #1 on the Pareto frontier of device intelligence πππππππ.ππππππ.ππ
Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device.
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Raw throughput can look great while your users wait. Goodput counts only the requests that meet your latency SLOs, and it measures how well your LLM serving system meets both performance and user experience goals.
Explore goodput and many other LLM inference concepts, visualized with interactive tools, in the free LLM Inference Handbook: handbook.modular.com/?utm_source=x
Explore goodput and many other LLM inference concepts, visualized with interactive tools, in the free LLM Inference Handbook: handbook.modular.com/?utm_source=x
handbook.modular.com LLM Inference Handbook A practical handbook for engineers building, optimizing, scaling and operating LLM inference systems in production. Now that MAX is source available, itβs the perfect time to revisit two tech talks from ModCon.
Start with Bing and Ehsanβs deep dive into the MAX stack to learn how a model goes from graph to compiled kernels to serving: youtube.com/watch?v=3H8Orjβ¦
Start with Bing and Ehsanβs deep dive into the MAX stack to learn how a model goes from graph to compiled kernels to serving: youtube.com/watch?v=3H8Orjβ¦
www.youtube.com Inside the MAX Inference Stack: A Technical Deep Dive MAX is Modular's inference stack for running any model on any chip:...