Mike Pollard retweeted
we're helping a customer spending $60k/mo move from OpenAI & Anthropic to open source models
they use almost every model offered by the labs, so we needed to find replacements for all of them
after generating evals, this is what we landed on
new cost: $12k/mo, 80% savings
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This is the easiest way to be validate that switching to an open source model will work for your flow without any interruptions.
Want to try GLM 5.2 in production but worried how it might change your product?
Don’t worry, we got you:
1. Install Inference Gateway (docs.inference.net)
2. Keep sending traffic to your current provider
3. Gateway automatically starts sorting through your live data using an RLM to generate evals for your app. This takes ~24 hours.
4. Gateway starts mirroring live traffic to GLM 5.2 to run evals. Traffic is only mirrored - you’re still using your old provider in prod.
5. Once evals look healthy, you get a Slack notification letting you know it’s safe to switch.
6. Switch model identifier in your code to “glm-5.2”
Congrats, you just saved 90% on your monthly token bill, and you own your LLM stack end to end.
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META BRAIN MODEL | NEW AGENT BILL | FABLE BACK SOON? nitter.net/i/broadcasts/1nxeLLOWp…
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We just launched agent signals! Now you can get notified when a user crashes out on your agent.
Write any prompt and it will run on your trace data as it comes in, classifies it, and then optionally notifies you. Track your classifications over time to see trends in agent/user behavior.
Check out this guide to get it set up:
docs.inference.net/guides/me…
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Mike Pollard retweeted
HALO is on the front page of HN :)
We’re releasing HALO Desktop 😇
it's the best way to find bugs in your agents
import traces from Langfuse or Arize & have HALO create a report with failure modes
give the report to your favorite coding agent to build it
runs locally on your machine. 100% free and open source
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Mike Pollard retweeted
We’re releasing HALO Desktop 😇
it's the best way to find bugs in your agents
import traces from Langfuse or Arize & have HALO create a report with failure modes
give the report to your favorite coding agent to build it
runs locally on your machine. 100% free and open source
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HALO just just got a lot more powerful. After you've integrated tracing you can now link your repo so the agent can recommend direct fixes based on all your trace data and the actual code itself. Right now it's free to try and a pretty easy way to improve your agent.
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Put together a video of what we've been building over at @inference_net
Check out how you can optimize your production agents with HALO and Catalyst
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Check out the full written guide here: docs.inference.net/guides/op…
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This is what I wanted agent observability to feel like. Traces that end in a code change.
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It was great working with @oliveholistic to improve their product experience! If you want faster and cheaper inference at frontier model quality, shoot me a DM.
Specialized models are becoming a practical path to better AI UX.
Olive moved from a frontier model to a custom model trained with Inference Catalyst for their food verdict workflow.
After a user scans a product, the model now delivers near-instant verdicts on what to watch out for, making the in-store experience faster and more seamless while cutting inference cost significantly.
Results:
- p50 latency: 2,721ms → 591ms
- p99 latency: 6,414ms → 998ms
- time to first word: ~0.25s
- inference cost: ~70% lower
Great working with @oliveholistic on this!
Full case study here: inference.net/case-study/oli…
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Mike Pollard retweeted
Shout out to @samhogan @AmarSVS @francescodvirga @atbeme @mikepollard_dev and the rest of the Inference dot net team
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Install our SDK, collect traces, improve your agents.
3 weeks ago we open-sourced HALO
this led to talking with dozens of teams running agents at scale
we realized the current agent monitoring tools aren't built for the future that we so clearly see ahead of us
today we’re releasing native OpenTelemetry-compatible agent tracing on @inference_net, powered by the same open-source core behind HALO
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Mike Pollard retweeted
We're releasing Schematron V2, a family of Specialized Language Models for converting messy HTML to structured JSON
frontier performance at 1/10th the cost
Schematron V2 was designed in partnership with some of the largest web-scraping companies in the world to meet the demands of their heaviest workloads
Schematron-V2-Turbo and Schematron-V2-Small are available today on @inference_net
Get started: docs.inference.net/workhorse…
I found out today that two of the largest web scraping companies in the world are using a custom Llama 3 model we released last year to process millions of webpages per day.
Schematron-3b: HTML -> JSON parsing
Frontier quality at dirt-cheap prices.
huggingface.co/inference-net…
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Come train a custom model
Introducing Catalyst: a developer platform to monitor, train & deploy self-improving AI models
built for teams operating AI products at scale
Catalyst can automatically:
- collect traces from your agents
- curate training data & evals
- train & deploy models on par w/ Opus 4.6
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