EmbeddingGemma 2: an open, lightweight multimodal embedding model
Introducing EmbeddingGemma 2, an open multimodal embedding model optimized for privacy-first use cases
Google AI Blog4 min read
vLLM
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TAI #225: OpenAI’s DevDay: Cheaper Intelligence, Unfinished Agents
TAI #225: OpenAI’s DevDay: Cheaper Intelligence, Unfinished Agents Also, Gemini 4 Argon, GPT-6.1 Sol, Dots, NVIDIA DGX Spark 64GB, Microsoft MAI-Transcribe-2-Streaming, and Cohere Embed 5. What …
Towards AI21 min readReflection Beam - 501B-A23B American Open Model
It’s been over a year since Reflection launched with us with big goals on coding (and hinted about their RL approach):
Latent Space10 min readRunning Mistral offline: the tokenizer is on disk, but the library can't find it
An inference server cut off from the Internet. A dedicated disk for models. Mistral's tokenizer downloaded in advance, sitting in its folder. And at startup: FileNotFoundError: No local files found for the repo ID mistralai/Mistral-7B-v0.1 and revision None. The file is there.
Dev.to AI3 min readThe AI safety check that runs on a laptop and nearly matched a 35B model
Guardrail selection has typically meant choosing between a purpose-built classifier and an LLM acting as a judge. Decision models such The post The AI safety check that runs on a laptop and nearly matched a 35B model appeared first on The New Stack.
The New Stack - AI6 min readAI infrastructure and compute: 48% of organizations running AI in production name a Google platform as their primary AI platform, more than twice OpenAI's share
VentureBeat Intelligence surveyed respondents at organizations with 100 or more employees in August. We asked how they choose, run and judge their AI infrastructure.
VentureBeat AI21 min readInference, optimized: How we benchmarked Runpod Overdrive
See how Runpod benchmarked four models across sixteen workload profiles to measure Overdrive inference performance, efficiency, and scaling behavior.
RunPod4 min readClosing the Loop Between Inference and Post-Training
CoreWeave RL Rollouts, CoreWeave Model Distillation, and the programmable training API on CoreWeave. Three new features that connect post-training back to inference.
CoreWeave Blog8 min readPyTorch Hardware Enablement: Updates from the Accelerator Integration Working Group
TL;DR The Accelerator Integration Working Group plays a vital role in standardizing how new hardware architectures connect to the open source AI ecosystem. As compute platforms diversify across cloud, edge,...
PyTorch Blog13 min readWakeKV: Reactive, Reversible KV Residency for Heads That Change Their Minds
Most KV-cache compression methods classify attention heads once, either offline or during prefill, and keep this classification fixed throughout generation.
arXiv - cs.CL (NLP)2 min readDGX Spark Alternatives 2026: 6 Cheaper Options From $0
DGX Spark now costs $6,950 and runs Linux only. Six cheaper alternatives ranked by price, from free Ollama and cloud APIs to Strix Halo PCs and Mac Studio M5.
BetterClaw Blog37 min readMiMo-V2.6-Pro for AI Agents: Setup, Cost vs GLM and MiniMax
MiMo V2.6 Pro tops open-weight models at $0.435/$0.87 per million tokens. Agent setup, tool calling, real costs vs GLM-5.3 and MiniMax M3.
BetterClaw Blog10 min readPrime Inference 📈, agent population 📈, Claude academy 🎓
PyTorch, vLLM, Ray: the open source stack behind modern AI is moving fast. At PyTorch Conference, Oct 20–21 in San Jose, learn from the engineers and researchers building it.
TLDR AI5 min readHolo4 API vs Local Deployment: Which Fits Your Agent?
Holo4 API vs local deployment compares setup burden, data control, and task economics for one computer-use agent workflow.
WaveSpeed Blog5 min readHolo4 27B vs 35B-A3B: Which Fits Your Agent?
Holo4 27B vs 35B-A3B compares long-task reliability, task economics, and weight licenses so builders can choose an agent model.
WaveSpeed Blog5 min readThe State of Serene, September 2026
Issue #4 of The State of Serene: faster search on every core and from a cold cache, regex and fuzzy search that always answer, text analyzers as expressions, HNSW, the docs inside the binary, OpenTelemetry ingestion, faster time histograms, MATCH_RECOGNIZE, spatial and AI functions.
SereneDB Blog26 min readKV Cache: What It Stores and How Much Memory It Needs
KV cache explained: what it stores, a per-model memory table from 8K to 128K context, and the Ollama, llama.cpp, LM Studio and vLLM settings that shrink it.
Zentask Blog10 min readLlama.cpp alternatives for running local agents: ds4, Magnitude and Strata against llama.cpp, vLLM and Ollama
ds4 runs big MoE models on 96 GB Macs, Magnitude tunes kernels to your device, Strata puts one model on a gaming PC. Every speed claim is self-reported.
Stackness Blog10 min read
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