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FP8 Cut Our TPOT by 25%. At High Concurrency, It Also Changed the Answers.

FP8 Cut Our TPOT by 25%. At High Concurrency, It Also Changed the Answers.

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3 min read
Why T Quant is the Secret Weapon for Mobile AI in 2026

Why T Quant is the Secret Weapon for Mobile AI in 2026

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6 min read
LFM2.5-24B-A2B on Your Own Hardware: The RAM, KV Cache and Bandwidth Budget

LFM2.5-24B-A2B on Your Own Hardware: The RAM, KV Cache and Bandwidth Budget

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11 min read
How One Startup Cut Diffusion‑LLM Inference Costs by 45 % – No Calibration Needed

How One Startup Cut Diffusion‑LLM Inference Costs by 45 % – No Calibration Needed

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6 min read
Model Distillation & Quantization: Running 8B Parameter Models at a Fraction of Cloud Cost

Model Distillation & Quantization: Running 8B Parameter Models at a Fraction of Cloud Cost

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10 min read
Four GPUs, One Quantization Ladder: Gemma 4 E2B From a 4 GB Laptop to an NVIDIA L4

Four GPUs, One Quantization Ladder: Gemma 4 E2B From a 4 GB Laptop to an NVIDIA L4

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11 min read
From 1.3 TB to 66 GB: On-Disk Vector Search in OpenSearch

From 1.3 TB to 66 GB: On-Disk Vector Search in OpenSearch

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8 min read
Performance vs Quality: Gemma 4 E2B Quantization on an NVIDIA L4 and a Tesla T4

Performance vs Quality: Gemma 4 E2B Quantization on an NVIDIA L4 and a Tesla T4

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11 min read
Native Quantization: Let OpenSearch Service Compress Your Vectors

Native Quantization: Let OpenSearch Service Compress Your Vectors

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6 min read
4-bit GGUF Quality for MoE Models: Why Only 3B of 180B Params Fire, and How to Prove Parity

4-bit GGUF Quality for MoE Models: Why Only 3B of 180B Params Fire, and How to Prove Parity

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7 min read
Performance vs Quality: Gemma 4 E2B Quantization on an NVIDIA L4 and a Tesla T4

Performance vs Quality: Gemma 4 E2B Quantization on an NVIDIA L4 and a Tesla T4

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11 min read
Running a 180B Model on a Laptop With No GPU: How 4-bit GGUF Keeps Full Accuracy

Running a 180B Model on a Laptop With No GPU: How 4-bit GGUF Keeps Full Accuracy

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6 min read
Qwen3.8-27B on one RTX 3090, and the setting its README says chat clients should leave at default

Qwen3.8-27B on one RTX 3090, and the setting its README says chat clients should leave at default

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4 min read
1.3 TB of RAM for 100M Vectors? Shrink Them Before They Hit OpenSearch

1.3 TB of RAM for 100M Vectors? Shrink Them Before They Hit OpenSearch

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8 min read
Gemma 4 on a 4 GB GPU in Plain PyTorch: From Out of Memory to Faster Than llama.cpp

Includes a tricky broadcast K/V debugging story

Gemma 4 on a 4 GB GPU in Plain PyTorch: From Out of Memory to Faster Than llama.cpp

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13 min read
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