221–230 of 586 posts
Earlier quoted context omitted.
Yep, I use Cortecs - https://cortecs.ai/ "Europe's LLM ROUTER"
Using Cortecs.ai too in combination with DS4Pro and Mistral Viba as harness, but unfortunately DS4 on Cortecs is the opposite of cheap. So I just use it for privacy centric tasks.
Earlier quoted context omitted.
You can use V4 Pro with Claude Code [1]. I tried it and it's impressive. [1]: https://api-docs.deepseek.com/quick_start/agent_integrations...
I've been using V4 flash consistently with Claude. Pretty great fast and darn cheap. I use it about 3h/day and so far haven't crossed $1 USD/week. FWIW, I this is what I have in my settings.json "env": { "ANTHROPIC_AUTH_TOKEN":"sk-nope_not_real", "ANTHROPIC_BASE_URL": "https://api.deepseek.com/anthropic", "ANTHROPIC_MODEL": "deepseek-v4-flash", "ANTHROPIC_DEFAULT_OPUS_MODEL": "deepseek-v4-flash", "ANTHROPIC_DEFAULT_S…
I think out tokens would be a better metric.
I tried it with Claude Code for a while but lack of WebSearch tool became a dealbreaker for me. Does anyone know of they will provide support for it?
Once they have their own coding agent which they seem to be working towards, I may start predominantly using their models. They seem to be doing all the "right" things, open sourcing models, publishing research, and keeping prices low for everyone.
I love Deepseek, but there is a pro China opinion deep rooted in it. Test it out for yourself.
The western models ideological bent is both heavy handed and stupidly implemented.
Earlier quoted context omitted.
They haven't raised enough money to be selling at a loss. And selling at a loss to gain market share in an industry with zero switching friction between sellers is not a strategy. That doesn't make sense. Loss leading only works when - it leads to a situation that allows you to prevent competitors from selling to your customers (gilded age railroad and pipeline industries are great examples). Then you can eventually…
Yeah, cool theory, but they are selling at a loss. We know that because their model is open and available on other providers too. No other provider even sells a quantitized version of DeepSeek V4 Pro at that price. Also, in case of LLM, market share = more people uploading their whole codebase/legal documents/unfinished books/literally everything to your servers for you to use in future training. So the incentive to…
This looks suspiciously cheap. The same model hosted by other providers is much more expensive [0]. So either DeepSeek can host it much cheaper than anyone else, or their business model is different. I suspect the latter, especially since their privacy policy [1] says personal data, including “User Input,” can be used "To improve and develop the Services and to train and improve our technology" . [0]: https://openrou…
Inference stack efficiency: Many of these providers take off the shelf sglang / vllm / trtllm and hope for the best. Meanwhile DeepSeek team is known for pushing the boundary of optimizations.
Now, sglang and vllm are great pieces of software, but take DeepSeek's Sparse Attention (DSA). Introduced 1.5 years ago (https://arxiv.org/abs/2512.02556), used by DeepSeek 3.2, GLM 5, DeepSeek V4. Only now is it slowly strating to get optimized in the major inference engines: (https://github.com/sgl-project/sglang/issues/19380 https://github.com/sgl-project/sglang/pull/22851 etc.). Of course, DS V4 adds extra optimizations into the model architecture on top of DSA, and those will take more time to be taken full advantage of by the open source inference engines.
Privacy: Betting that people will pay extra for inference hosted outside China. This is especially true with DeepSeek, because DeepSeek is transparent about using API data for model improvements.
And few other things (scale (matters a lot for MoEs), reliability, soft enterprise lock in, etc.)
---
There is also, likely, tacit collusion at play here. Look at GLM 5 and GLM 5.1 prices. GLM 5 and 5.1 cost the same to run, but providers decided to charge much more for 5.1 because it is much better model, and because Z.AI raised their price as well.
I'm more curious about the caching: > (2) For all models, the input cache hit price has been reduced to 1/10 of the launch price. This price adjustment takes effect from 2026/4/26 12:15 UTC. There is no end date. Currently, it's 2% of the input price for DeepSeek V4 Flash and 0.8% with this new V4 Pro pricing, which is extremely low compared to competitors to the point that it affects the unit economics a bit and I t…
DeepSeek V3.2 which uses DSA only (sparse attention, but without compression from HCA and CSA) is a smaller model but uses 10x more memory at 1M context window compared to DS V4 Pro.
Also, I have to say, DeepSeek's API has a very good cache hit rate. With the same workload, I see ~80% KV cache hit rate with the DS API vs ~50% with the major western inference providers for open weight models.