anonzzzies2 hours ago
From this thread [0] I can assume that because, while 1.6T, it is A49B, it can run (theoretically, very slow maybe) locally on consumer hardeware, or is that wrong?
Quasimarionan hour ago
Theoretically with streaming, any model that fit the disk can run on consumer hardware, just terribly slow.
gwern32 minutes ago
Main discussion: https://news.ycombinator.com/item?id=47884971
woeirua2 hours ago
Hmm. Looks like DeepSeek is just about 2 months behind the leaders now.
anonzzzies2 hours ago
If that is really so, it would be now be good enough to replace claude for us; we use sonnet only; with our setup, use cases and tooling it works as well as opus 4.6, 4.7 so far. We won't replace sonnet as long as they have subscriptions but it is good to have alternatives for when they force pay per use eventually.
arunkant4 minutes ago
Yep, it should be better and more efficient then sonnet.
statementsan hour ago
The quality of this model vs the price is an insane value deal.
statements7 minutes ago
Models like Deepseek is the only reason we are able to categorize and measure quality of thousands of MCP servers (https://glama.ai/blog/2026-04-03-tool-definition-quality-sco...). That's billions of tokens – an expense that would be otherwise very hard to swallow.
cmrdporcupineop2 hours ago
Pricing: https://api-docs.deepseek.com/quick_start/pricing
"Pro" $3.48 / 1M output tokens vs $4.40 for GLM 5.1 or $4.00 for Kimi K2.6
"Flash" is only $0.28 / 1M and seems quite competent
(EDIT: Note that if you hit the setting that opencode etc hit (deepseek-chat / deepseek-reasoner) for DeepSeek API, it appears to be "flash".)
taosx2 hours ago
I estimated that even with heavy usage it would cost your around 30-70$ depending on caching at around 40M tokens. That would give you around double the usage compared to gpt-5.5 on the 200$ sub
mudkipdev2 hours ago
This is refreshing right after GPT-5.5's $30
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taosx2 hours ago
So the R line (R2) is discontinued or folder back into v4 right?
mudkipdev2 hours ago
I believe the R stood for reasoning, just like OpenAI had their own dedicated o1/o3 family, but now every model just has it built-in.
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