Appreciate the shout-out, @AMULETAnalytics We’re thrilled to share Jamba Reasoning 3B with the world.
LLMS
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Ant Ling releases 1T-params open-source coding model
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Ant Ling introduced a new 1T-params, non thinking open source model with a good performance on coding tasks. 1T
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Ollama’s bloated wrapper fails to match ggml’s efficiency
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do not use Ollama ggerganov wrote blazing-fast
C++ inference (ggml, llama.cpp) then Ollama wrapped it
in a bloated binary and is now somehow the face of local LLMs
soaking up VC hype and it's not even a good wrapper lol -
ChatGPT Transforms Confusing Math Equations Into Friendly Explanations
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Some math equations look like they want to fight.
Then ChatGPT explains them and suddenly we’re friends again. -
Continuous Learning Improves Model Credibility Through Linear Source Reading
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If we sort out continuous learning such that large models don’t just get a batch of snippet stew out of a blender, and read sources linearly, it may help with credibility assessment.
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Run Claude Code Locally on Your Own GPU Setup
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tired of Anthropic’s weekly limits and nerfed models? with one command and a few GPUs,
you can route Claude Code to your own local LLM Buy a GPU p.s. full video tutorial pinned at the top of my profile -
Jamba 1.5 Large Now Available for Local Inference Download
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5/5 Available today for download & local inference on @huggingface
, @kaggle
, @lmstudio
, and llama.cpp. -
Jamba Achieves Superior Mobile Performance with Extended Context Lengths
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4/5 The same efficiency gains apply on mobile. Running at 16K context lengths on an iPhone 16 Pro, Jamba outputs nearly 16 tokens/second, outpacing token outputs from Llama 3.2 3B, Qwen 3 1.7B, and Phi-4 Mini. Jamba is the only one that can handle up to 64K.
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Jamba Reasoning 3B: Exceptional Performance on Extended Contexts
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3/5 Where most other tiny models choke at context lengths above 8K, Jamba Reasoning 3B stays steady, with a consistent 30-40 tokens/second on an M3 MacBook Pro, regardless of context size. This is up to an order of magnitude faster than other on-device models.
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Jamba Reasoning 3B Excels in Knowledge and Instruction-Following
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2/5 Jamba Reasoning 3B excels in general knowledge benchmarks (MMLU-Pro, HLE) and instruction-following (IFBench), making it reliable and performant