It works very well with OpenCode. My team keeps hitting the 5h limits on other subscriptions and it's pretty good to have Deepseek as a backup. I just put 50 bucks on there and it feels like it'll never run out.

It's not good enough to fully replace any of the frontier models yet but it's definitely great to have as a backup!

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...

Why do you need them to provide a coding agent? Just use their model with any off the shelf coding agent. I happen to prefer Pi, but use whatever works for you.

You no longer need "their coding agent". You can hook up claude code to use Deepseek. Works perfectly.

antirez's ds4-agent works quite fine. It runs on any Apple Silicon device with 96GB RAM or more.

open code works with them today. I've been using it fulltime for 2 weeks so far.

It’s good and cheap, but don’t talk about politics to it or it might trigger some sort of censorship rule. You can see it think, then suddenly erase everything and suggest to switch to another subject, without explaining anything. I also had it output some sort of generic message about how the news outlets are in the service of the people. Both times I was surprised because I didn’t make any sensitive requests, neither illegal nor subversive. But it was a remotely political topic and it was enough. There was something both chilling and refreshing about it, since censorship in the west is usually more subtle.

Yes - the model is REALLY good. I try Claude at work and Deepseek personally and this is the only model that works without trying to actively bankcrypt me.

I think Deepseek uses much more tokens than other models.

That's also a game changer for local inference. It unlocks long contexts, batched inference and storing the KV cache to disk on ordinary consumer platforms.

[dead]

I would not be shocked if they do that. I would not be terribly shocked that the US-headquartered models do that for another government either. As far as data confidentiality goes, I wouldn’t hold my breath. Microsoft checks all those enterprise boxes, right? Yet, Azure still gets breached once in a while.

Just use it through something like Azure. They host the entire model and serve it from the US. I'm sure that there are other providers like this.

We use it that way and it works great.

It's not an unreasonable concern, which is why most US companies prefer to go with AWS bedrock, or even one of the AI labs, and typically request zero data retention agreements. But leaking is a concern no matter where it's hosted, it's just the incentives that change IMO. For example, the labs do scan every chat and train on data not covered under enterprise ZDR agreements. Law enforcement can request access to all user data with a valid warrant or in an emergency context [1]

If you're interested in trying DeepSeek V4 privately, you can try Tinfoil (tinfoil.sh) where all models are hosted in an attested secure hardware enclave, making the inference end-to-end private. Full disclosure: I'm one of the cofounders.

[1] https://cdn.openai.com/trust-and-transparency/openai-law-enf...

I think there is a nonzero chance of that happening. Beijing could at any point decide that DeepSeek has become too powerful and/or is a major export and start to insert themselves (assuming they have not already).

There are widespread reports about how foreign actors (not limited to China) have infiltrated critical networks across many industries in the US en masse and are simply waiting for the right time to exploit them. Frontier models are simply another attack vector (and much more easily exploitable when you think about it).

The fact is that there is potential for this with any cloud-hosted model, whether it is intentional by the actual company building the models or a malicious actor is able to exploit a vulnerability.

This is a risk although then this is fortunately a model that isn't tied to Chinese hosting. But indeed something to consider if using straight DeepSeek.com.

User data integrity definitely should be a concern. It's also known that regulations is being outpaced, so the cost of being/using frontier products is a double-edged sword for sure.

More likely? US tech leaders have been fully capitulating to the surveillance state for over a decade. Why do I care what China does with my data? I don’t live in China and never plan to.

The tech bro threat model has always been pure jingoism and xenophobia. Ironically, the worst thing a Chinese company has done with my data is sell Tiktok to an American technofascist.

It's actually even cheaper when you look at the cache read costs. Those costs can dominate in agent workflows and DeepSeek's cost for cache reads is insanely low comparatively. At $.003626/M tokens, the cheapest other thing on your list is >$.2/M tokens. That's on the scale of 100x cheaper.

*GLM 5.1

Small team, cheap electricity, very efficient models. Many western companies operate at a loss to gain market share. Why can't the Chinese?

DeepSeek hasn't raised enough money to be actively selling tokens at a loss. They have a small team, extremely low overhead relative to other labs, operate in a place with the essentially the cheapest commercial electricity rates in the world, and their architecture lends itself very well to cheap inference.

Inference is cheap. I bet the financials of these Chinese companies are much saner looking than any of the big US AI companies which are bloated by investors.

Federal ban incoming then. They did it with cars already.

If you think heavily subsidizing AI models isn’t financially viable, I have some bad news for you about US AI companies.

Deepseek has made some incredible advancements in model efficiency, and more importantly actually publishes those advancements so everyone can benefit from them.

US suppliers are fine and won't go bankrupt, they can just focus on serving bigger "Pro" class models from their large datacenters. In fact cheap AI makes the bigger and smarter models more useful because it's smart enough to draft a clear question to the model, which helps minimize wasted tokens.