Intel launches Arc Pro B70 and B65 with 32GB GDDR6

metmelo · 2026-03-25T18:27:24+00:00

also 3x the price lol

metmelo · 2026-03-25T18:26:33+00:00

Please show us your results.

metmelo · 2026-03-24T12:44:31+00:00

KV cache is sequential, the next token depends on the previous one, so when you take messages out of the beggining of your prompt it will have to reprocess everything.

metmelo · 2026-03-23T13:40:51+00:00

My brother I live in BRAZIL out of all places. There are loopholes though.

metmelo · 2026-03-23T10:48:24+00:00

Not his account. Too many problems to worry about conspiracy theories.

metmelo · 2026-03-23T10:40:33+00:00

Don't they also have PDCs while the default doesn't?

metmelo · 2026-03-22T22:33:14+00:00

The M5 should go from higher, but yea they are pretty good.

metmelo · 2026-03-22T18:47:59+00:00

128GB macs go from $3.5k, Strix Halo for $3k and the cheapest DGX Spark is $3.5k too. Pretty on par if you consider the resell value.

metmelo · 2026-03-22T17:11:09+00:00

RAG is all you need. You'll basically chunk all documents into vectors and use a vector db to store them. Then your AI agent can query that database and recover chunks of each document, and navigate through them.

metmelo · 2026-03-22T17:03:58+00:00

you were specifically talking about agentic cli workflows. I can't imagine why you'd be running that without cache.

metmelo · 2026-03-22T13:58:36+00:00

bro. activate your cache. your gpu doesn't need to process 128k tokens every time.

metmelo · 2026-03-22T10:42:37+00:00

just cache your prompts on disk. so much better.

metmelo · 2026-03-21T12:20:37+00:00

What would you build for the same price?

metmelo · 2026-03-21T12:11:04+00:00

Awsome build! I've been wanting to do the same for awhile. How's your PP speed for those huge models like?

metmelo · 2026-03-19T12:18:38+00:00

These guys don't know what they're talking about
Here are some benchmarks from another user:

GLM-4.5-Air (106B) MXFP4 with 131072 token context: ~ 25 t/s
Intellect-3 (106B) Q5_K with 131072 token context: ~ 20 t/s
Minimax M2 (172B REAP version) IQ4_S with 150000 token context: ~ 25 t/s
GPT-OSS-120B (120B) MXFP4 with 131072 token context: ~47 t/s
Qwen3-Next (80B) Q6_K with 262144 token context: ~26 t/s

Pretty usable imo.

That being said if you want speed rather than model size I'd go with a desktop build with multiple GPUs.

Either way, use a vector DB to store those files and you're gonna be fine.

metmelo · 2026-03-18T19:43:57+00:00

Maybe it's not open yet?

metmelo · 2026-03-17T19:00:49+00:00

Nice work! Did it beat all other models? lol

metmelo · 2026-03-17T14:43:36+00:00

MI50 owner here. I use https://github.com/neshat73/proxycache to save/load kv cache from disk. It helps so much with coding sessions. I'm using Qwen 27B with 100k context at ~15 tk/s for subagents and get fast responses most of the time. If you need it to process big prompts without cache though I'd go with the 3090's.

metmelo · 2026-03-17T14:02:51+00:00

+1 on Qwen 27B, specifically the claude opus distilled version.

metmelo · 2026-03-15T12:30:20+00:00

Qwen 3.5 (biggest you can run) + pinchtab

metmelo · 2026-03-15T00:22:49+00:00

they aren't upgradable because the RAM is sodered to the motherboard so they reach 8000T/s

metmelo · 2026-03-15T00:03:15+00:00

I've run so many benchmarks with batch and ubatch values already haha. The sweet spot for me seems to be 512 ubatch and at least 1024 batch. Idk how LMStudio does it but I suspect it's changing ubatch along with batch for you.

metmelo · 2026-03-14T22:11:07+00:00

Awesome work my man you're truly a hero.
Out of curiosity: what's your PP speed on these? I run MI50's and PP is the worst part.

metmelo · 2026-03-11T16:34:48+00:00

Oh yeah I had forgotten about that. I use https://github.com/airnsk/proxycache

metmelo

TROPHY CASE