v0.7.0
LLM inference in C/C++. Contribute to ggml-org/llama.cpp development by creating an account on GitHub.
llama.cpp11 min read
Opik Blog
Stay updated with the latest developments in Artificial Intelligence
Agents on live hardware: reason where you must, engineer everywhere else
CoreWeave Blog10 min read
b11669
llama.cpp1 min read
Jev vs. LLM-as-a-Judge for AI Evals
A model that answers yes/no questions instead of writing text came out 3.5× cheaper and 3.8× faster than our gpt-4o-mini judge on 1,000 real production turns, and agreed with it on 897 of them.
Opik Blog1 min readComet Extends Agent Observability and Evaluation to Nebius AI Cloud
Comet’s Opik platform is now listed in Nebius AI Cloud Applications, bringing agent observability, evaluation, and the full Comet AI development platform to one of the most powerful AI cloud platforms available today.
Opik Blog1 min readCapturing a 400-Turn Claude Code Session in a Single Image
We ran a small model over thousands of Claude Code session and discovered how people really use coding agents. Comet Cost Intelligence is a tool for optimizing engineering token spend on Claude Code and Codex.
Opik Blog1 min readPrompt Management for AI Agents: The Best Tools Compared (2026)
Despite how often prompts change once an agent is live, most teams don’t have a real prompt management process. Somewhere on a shared drive is prompt_final_v2.txt, and somewhere else is a version someone pasted into a Slack DM that is two edits newer.
Opik Blog1 min readExport TrueFoundry AI Gateway traces to Opik with OpenTelemetry
When an LLM call is slow, expensive, or wrong, you want to see the whole request: the prompt, the model, the tokens, the tool calls, the latency. If your traces live in one tool and your evaluation lives in another, that picture is split in two.
Opik Blog1 min readUX Without a UI: Notes from Researching Terminal UX for Opik MCP
The way developers interact with products is changing, and opening your app’s dashboard is no longer the obvious entry point. They want to use their apps inside the terminal. Why? Because they’re already there. We’re seeing more users instrumenting MCP and it makes sense.
Opik Blog1 min readDiffusion Language Models, From Scratch to Production
“Language model” used to be a very general term for statistical models trained on language tasks. It included everything from n-gram models to LSTMs and GRUs.
Opik Blog1 min read
What is AI Observability? A Complete Guide to Debugging and Monitoring Modern AI Systems at Scale
Your new AI product is live. Infra dashboards are all green. Latency is low, error rates are flat, and CPU/GPU utilization looks healthy. Yet your Slack channels are full of screenshots from users asking, “Why did it do this?” The same user goal and high-level prompt can still produce wildly…
Opik Blog14 min read
LLM Model Selection: How to Pick the Right Model for Every Agentic Task
Someone on your team defaulted to the latest and greatest model available, which is also the most expensive model. Maybe it was an agent calling the flagship model for every tool call or a coding agent set to its most capable model out of the box. It worked, so nobody revisited it.
Opik Blog8 min read
Best LLM Observability Tools of 2026: Top Platforms & Features
LLM applications are everywhere now, and they’re fundamentally different from traditional software. They’re non-deterministic. They hallucinate. They can fail in ways that are hard to predict or reproduce (and sometimes hilarious).
Opik Blog17 min read
Showing 10 of 10 stories
You're all caught up.
AiByts Weekly Brief
Get the top AI news and tools straight to your inbox every week.
Weekly · AI news from Opik Blog
Join 15,000+ AI enthusiasts