We simplify search for complex enterprises.
Glen Allen VA
Joined June 2009
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Native Inference built into SearchAI 12.2. Install SearchAI and supported models run inside the application - no external inference service to deploy, and no per-token costs.
searchblox.com/searchblox-12…
Every enterprise AI program eventually hits the same wall, and it is not a technical one.
blog.devgenius.io/the-end-of…
SearchBlox retweeted
Introducing 𝙻𝙵𝙼𝟹: 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.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding
> 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages.
> 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language.
> 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: 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.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 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.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒
Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device.
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How do you deliver a truly 1:1 AI experience without turning customer data into an external AI dependency?
searchblox.com/private-ai-pe…
Stop Making One Model Do Two Jobs: Pipelines of Inference That Speed Up Both Decisions and Generation
medium.com/@tselvaraj/stop-m…
SearchBlox retweeted
Lots of discussion out there about our next model(!), so I wanted to give an early look as soon as possible. Introducing Gemini 4 Argon!
It shows frontier performance in complex workflows, cyber defense and software engineering. Teams are using it extensively at Google, from coding to quantum computing, great feedback.
Here’s a look at the benchmarks:
SearchBlox retweeted
The Cohere Embeddings team has been cooking 🍳
Several key innovations in the model:
- The model not only retrieves relevant results, but finds the most human preferred documents based on new training & evaluation techniques.
- Strong focus on multilinguality 🇺🇳 - just retrieving English docs is boring
- Massive throughput gains - scale to any data size
Together with a strong focus on privacy - your data stays private, always.
SearchBlox retweeted
1M+ downloads for Spark X2.5! 💜
661K+ across 6 official channels, plus 382K+ from 99 community builds (GGUF, MLX, ONNX and more).
Thank you to every developer and builder.
Try the 1.7B and 4B models, and upvote the collection 👍 huggingface.co/collections/X…
Until now, using an LLM with SearchAI meant running a separate inference service or paying for an external API. With 12.2, the model runs inside the platform, so AI search, RAG, chatbots and agents can all run on hardware you own or rent.
searchblox.com/searchblox-12…
Six things enterprises actually do with a private AI server — measured, end to end
September 2026 · SearchAI Inference Server team
inference-server.searchblox.…
Understand how entities and relationships form the core of a Knowledge Graph.
Break down the building blocks: entities, attributes, and relationships.
See why structured relationships improve search and AI understanding.
searchblox.com/what-is-a-kno…
380 validated prompts. 13 industries. Ready to run.
Every install ships with a built-in console of 380 tested prompts — document understanding, extraction to JSON, function calling, classification, multilingual, vision, video, and speech scenarios.
inference-server.searchblox.…
