Comment by aftbit
14 hours ago
#!/bin/sh
export ANTHROPIC_BASE_URL=https://api.deepseek.com/anthropic
export ANTHROPIC_AUTH_TOKEN=sk-secret
export ANTHROPIC_MODEL=deepseek-v4-flash
export CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1
exec claude $@
ANTHROPIC_MODEL=deepseek-v4-pro[1m] ANTHROPIC_SUBAGENT_MODEL=deepseek-v4-flash
This is what I’ve been using for non-confidential projects for about a week now (soon after v4 came out). I honestly can’t tell the difference, but I’m not doing anything crazy with it either.
Worth noting that I don’t think DeepSeek‘s API lets you opt out of training. Once this is up on other providers though… (OpenRouter is just proxying to DeepSeek atm)
For those that don't want their data trained on, OpenRouter allows you to have account-wide or per-request routing with either provider.data_collection: "deny" or zdr: true (zero data retention).
Also, you can use HuggingFace Inference for DeepSeek V4 or Kimi K2.6, both of which work quite well and route through providers that you can enable/disable (like Together AI, DeepInfra, etc) - you'll have to check their policies but I think most of those commercial inference providers claim to not train on your data either.
That doesn't work, if you do that it will mark DeepSeek's models with a warning symbol along with the error "paid model training violation".
I wonder why the question about data security and training comes often with DeepSeek, Kimi, Glm and never with Anthropic, OpenAI, and Google models.
Why is that?
IIRC, USA data protection protects data of US citizens only, foreigners data is not protected, and the companies are not even allowed to disclose when they collect those data.
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As of now, OpenRouter offers multiple providers for DeepSeek with ZDR (not sure if they respect it but still).
At several times the price of DeepSeek, though, so it's a tradeoff... Even then Pro is still cheaper than Haiku.
I wanted to try this. To bring back opus and sonnet do I just reset those env's?
yes, this is pretty much just rerouting Claude to call Deepseek's Anthropic-style-compatible endpoints instead of its own defaults Once removed, it'll work just like before
Correct.
The more interesting part of deepclaude is the local proxy it runs to switch models mid-session and do combined cost tracking. Though these features seem quite buried in the LLM-generated readme. Looking at the history, it appears they were added later, and the readme wasn't restructured to highlight this.
Also, the author checked in their apparently effective social media advertising plan: https://github.com/aattaran/deepclaude/commit/a90a399682defc... (which seems to be working)
How come such slop is allowed here, what value do these vibe coded zero shot "projects" add? Why not just post the prompt?
Seriously. When I first looked this project had been pushed the first commit two hours prior. Projects should be at least 3 months old or automatically removed.
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For the same reason that GitHub has a releases page for uploading binaries.
Convenience? Am I supposed to take the prompt and use my own tokens on it? Why should I have to do that?
Recruiters used to use the candidate's Github "sources" page for evaluating candidates as a kind of proof-of-work.
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It seems like any project that makes fun of Claude is bound to reach the top spot on Hacker News. Even if it’s just a project consisting of four lines of code.
You're just mean. I count 6 lines of code!
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So I created https://getaivo.dev, one can use model in the coding agent directly. Just `aivo claude -m deepseek-v4-pro`
does it support aws bedrock provider support,does i can use any model in this
Ah, for aws bedrock, just use `aivo keys add` add baseurl and apikey, everything is ready, `aivo models` to see models
Currently no, but it can be added
This in essence is what allows one to use any model with CC -- including local.
I know. I'm struggling to understand how this is a github repo/HN article. I've been using claude-code with a llama.cpp server and a dummy API key, and all that is required is to define 2 environmental variables to point claude at the local endpoint. Am I missing something?
thanks, that was super easy.
I have been wanting to try CC with different models since Opus went downhill last month..
What limitations or issues have you noticed when using DeepSeek with Claude Code if any?
The AI wars have begun
And they are enticing human agents to further their agendas using techniques learned from the white mice.
This has been possible since the beginning.
those who use deepseek v4, what level of output you get? Codex 5.3 or GPT 5.4?
is flash version on level of gpt 5.4 mini
I tried it on a non trivial, but also well documented and self contained task. It did amazingly well. I used deepseek v4 pro via deepseek platform. The model is very fast and also it is super cheap. I burned only 0.06 USD (I reckon how the same task would have cost me had I used e.g., amp).
PS. mentioning amp because i used to use it and I pay directly for token. I topped up 5 usd so I will be going to use it and see how far can it take me. But my impression so far is even when model subsidization is done, those open source models are quite viable alternatives.
> But my impression so far is even when model subsidization is done, those open source models are quite viable alternatives.
My understanding is that DeepSeek V4 Pro is going to be uniquely good at working on consumer platforms with SSD offload, due to its extremely lean KV cache. Even if you only have a slow consumer platform, you should be able to just let it grind on a huge batch of tasks in parallel entirely unattended, and wake up later to a finished job.
AIUI, people are even experimenting with offloading the KV cache itself to storage, which may unlock this batching capability even beyond physical RAM limits as contexts grow. (This used to be considered a bad idea with bulky KV caches, due to concerns about wearout and performance, but the much leaner KV cache of DeepSeek V4 changes the picture quite radically.)
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have you used it for non coding tasks via MCP, like Figma/Paper for design or Ableton MVP for sound design?
The token cost makes it tempting to use for token-heavy tasks like this
> even when model subsidization is done, those open source models are quite viable alternatives.
Model inference was never subsidized. Inference is highly profitable with today's prices. That's why you have many inference providers. My guess, the prices for inference will go down, as more competition starts cutting the margin.
It's model training, development and R&D that cost a lot, and companies creating closed models don't have any business model except astroturfing and trying to recover training costs through overpriced inference.
It's close to Opus 4.5 for me