Ship AI changes with proof, not vibes
A2ZAI Checks runs evals on your repo: a PR scorecard plus a public benchmark card you can drop in READMEs and launch posts. Same site: builder radar for model launches, API shifts, pricing, and outages—so you know when to re-run.
Builder signals
5
Funding tracked
30
Models watched
5
Agents spotted
0+
Top builder-critical changes
What could break your stack this week
- highdiffusiongemma-26B-A4B-it momentum +3%Google
- highMiniMax-M3 momentum +30%MiniMaxAI
- highLocateAnything-3B momentum +24%nvidia
- highgemma-4-12B-it momentum +1%Google
- highKimi-K2.7-Code momentum +13%moonshotai
Sourced from the same live signal pipeline as River. Pin your evals with Checks.
Is your AI stack at risk?
Pick your providers, see critical changes in 10 seconds. Free, no signup, shareable.
Score my prompt
Compare two models on your prompt and get a shareable benchmark URL.
Live River
Quick bytes on launches, deprecations, pricing moves, benchmarks, and breakage risk.
A2ZAI Checks
GitHub-native evals that turn prompt and agent changes into PR scorecards.
Builder Stack
Discover agents today, with MCPs, plugins, SDKs, and technical products rolling in next.
Capital Radar
Funding rounds, acquisitions, and investor moves with builder-first context.
Best places to start
Choose an artifact, not a browse path
The strongest A2ZAI surfaces now end in a public object you can use, share, or route teammates into.
Utility artifact
Run Checks and publish a benchmark card
Best for shipping teams who want a PR scorecard, public benchmark artifact, and shareable proof of improvement.
Open ChecksSignal artifact
Open the live river and jump into quick bytes
Best for scanning launches, deprecations, pricing shifts, and benchmark moves, then opening the strongest byte pages.
Open Live RiverDestination artifact
Use company pages as operating dashboards
Best for sending someone one link that combines official posts, live intel, quick bytes, and capital context.
Explore company pagesCompany Spotlight
NVIDIA
NVIDIA Blackwell Leads on First Agentic AI Infrastructure Benchmark
Meta
Scaling How We Build and Test Our Most Advanced AI
We’re strengthening our presence in Alabama through new investments and community support.
Microsoft
Allie K. Miller: Find your “weirdos”—and let them lead
OpenAI
From model to agent: Equipping the Responses API with a computer environment
Anthropic
TCS and Anthropic partner to bring Claude to regulated industries
What changed for builders
Use this stream to spot the change, then move into a stronger destination page: river for the wider feed, company pages for operator context, and Checks for a public benchmark artifact.
diffusiongemma-26B-A4B-it momentum +3%
google • diffusiongemma-26B-A4B-it
MiniMax-M3 momentum +30%
MiniMaxAI • MiniMax-M3
LocateAnything-3B momentum +24%
nvidia • LocateAnything-3B
Kimi-K2.7-Code momentum +13%
moonshotai • Kimi-K2.7-Code
xAI raised $6B (Series C)
Funding Radar • xAI
Databricks raised $10B (Series J)
Funding Radar • Databricks
Perplexity raised $500M (Series B)
Funding Radar • Perplexity
Physical Intelligence raised $400M (Series A)
Funding Radar • Physical Intelligence
A2ZAI Checks
Catch prompt and agent regressions before merge, then turn the result into a shareable benchmark card.
Explore Checks5 Things in AI Today
A fast daily read on the biggest AI stories, tools, launches, demos, and deals.
5 Things in AI Today
The biggest AI stories, tools, launches, demos, and deals in a quick daily read.
Or stay in the loop
Funding Radar
View allxAI
$6BSeries C • Foundation Models
Databricks
$10BSeries J • AI Infrastructure
Perplexity
$500MSeries B • AI Applications
Physical Intelligence
$400MSeries A • Robotics
Chosen builder wedge
A2ZAI Checks is the utility layer on top of builder radar
The site stays useful as launch radar and discovery, but the product edge is a shareable scorecard builders can produce every time they ship. Supporting surfaces like learn still exist with 15 lessons and 126+ terms, but they are now secondary to shipping workflows.
Viral Artifact
GitHub PR scorecard
A2ZAI Checks
Prompt regression check for `support-agent.yaml`
Quality
+8.4%
Latency
+220ms
Cost
-31%
Passing: `refund-policy`, `invoice-lookup`, `cancel-subscription`
Regressed: `edge-case-promotions` on `gpt-4.1-mini`
Recommendation: merge after fixing one retrieval prompt and rerunning the pack.
Public Card
Benchmark card
Repo benchmark
support-agent / checkout-recovery
Best model route
Claude Sonnet + GPT-4.1-mini fallback
Win summary
12% better success at 29% lower cost
This is the artifact that spreads on X, GitHub, and founder launches: a benchmark card builders can link to when they ship.
AI Stock Pulse
NVIDIA
Microsoft
Meta
Apple
Market data delayed. For informational purposes only.
Latest Research
View allGaze Heads: How VLMs Look at What They Describe
How a vision-language model internally solves the task of describing an image is far from obvious. We find that the model develops a specific mechanism for this: a small set of attention heads in its language-model backbone, which we call gaze heads, whose attention tracks the image region the model...
arXivOmniVideo-100K: A Dataset for Audio-Visual Reasoning through Structured Scripts and Evidence Chains
Current automated pipelines for audio-visual Question Answering (QA) generally adopt a ``video-caption-QA'' paradigm. However, these methods typically segment videos into short clips and generate separate descriptions for audio and visual modalities. This decoupled processing severs inherent associa...