Even with the V4 Pro discount, the V4 Flash model gives you the best performance per unit dollar, and better performance overall for agentic, tool-heavy workloads. V4 Pro is smarter in one-shot reasoning, but at a significant speed difference. The performance, cost, and speed, makes V4 Flash our top flash model today by far.
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 am curious - Is there a way to switch between models depending on the task? Because I believe Deepseek V4 is not multimodal and it will be good to switch back to Claude if vision or other capabilities are required.
That's interesting. I thought Claude Code is not as good, therefore people want to use Claude model with other alternatives. This is the other way around.
Which begs the question, regardless of the model, which Claude Code alternative is better? (I keep saying "Claude Code alternative" because I don't know the term... LLM CLI?)
At this point in the AI wars, it is probably better to have more users of Claude code rather than restrict which LLMs it can connect to. Claude code is probably (currently at least) stickier than the LLM model itself. Getting people into the Claude code ecosystem is worth it.
Later, they can always lock it down more or add Claude LLM only features to it.
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.
I probably have an unfounded assumption that whatever coding agent they make will work really well with their models, better than external harnesses. I don't have a good sense for how all the model + harness combinations compare, nor any good way to compare them myself, but generally believe model companies train their models to work best with their own harness.
I've noticed that models have gotten less finicky with this over time. Harnesses don't need to be complex to get good coding performance from models, they just need to implement some sane primitives for code exploration and editing.
Using it with Pi and can only report good thing so far. I'm very impressed by how good it is (also it's way slower than Claude Sonnet and GPT-5.5 and often thinks "too much" before starting).
I'll keep running Flash locally for the stuff I care about data privacy, but the value of Pro through their API is unreal for anything else (and I want to give them my training data as long as they keep putting out open models).
If you have not tried DeepdeekV4 you're missing out. The pricing makes it unbelievably good.
The chains of thought for Deepseek are very very interesting reads. Open code won't show them but do read them and you'll be surprised at how underrated the model is.
My model usage is very low but I still do pay directly to Deepseek regularly as my tribute and contribution to them open sourcing their models as my gratitude and showing support for what I deem positive for overall social good.
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.
That is some insane value.
I've been using GLM Coding Plan Max with GLM 5.1 for a while and i've tested DeepSeek V4 Pro maybe for 3 weeks now and I found it to be better than GLM 5.1 for complex coding tasks. I've used 65m tokens and with that price it cost me $1.5, that's really cheap.
their MLA architecture cuts KV cache by ~5-13x vs standard attention. that's why inference is actually cheaper to run, not just a price war to gain market share.
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.
I am more worried about accidental data leak (agent reading env file for example) with the Chinese hosted models compared to the US hosted models. Am I wrong to suspect that the Chinese government might be more likely to scan all chats and save useful information compared to the US government or company?
I hesitated to even post this comment as it sounds biased and xenophobic. I would love for someone to convince me I am wrong. Does anyone have any insight into the company behind deepseek hosting, and what their history of respecting data privacy is?
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.
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.
Props to them. That makes DeepSeek v4 Pro extremely cheap compared to others, even in the same category. Look at these prices per million outputs tokens:
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.
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.
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.
I've had a ton of success when pairing Opus 4.7 for planning w/ DeepSeek V4 Flash in opencode. Best part is DeepSeek V4 Flash is Free through opencode Zen.
Anyone using deepseek through a gateway (not sure if right term) so there's no data retention? At work we're going through a few hundred million tokens a day in our app (using anthropic models), and we're looking for something significantly cheaper
I have been using deepseek via deepinfra, afaik they provide no data retention. Im probably going to deploy the full model on their infra instead of paying credits at some point, so far the experience has been pretty good
Even at these prices I find claude and codex subscriptions to be cheaper than per-token pricing when my usage is hovering around the session limits. I guess the subscriptions are heavily subsidized.
Data at https://gertlabs.com/rankings
I tried it and it's impressive.
[1]: https://api-docs.deepseek.com/quick_start/agent_integrations...
Which begs the question, regardless of the model, which Claude Code alternative is better? (I keep saying "Claude Code alternative" because I don't know the term... LLM CLI?)
Later, they can always lock it down more or add Claude LLM only features to it.
I'll keep running Flash locally for the stuff I care about data privacy, but the value of Pro through their API is unreal for anything else (and I want to give them my training data as long as they keep putting out open models).
The chains of thought for Deepseek are very very interesting reads. Open code won't show them but do read them and you'll be surprised at how underrated the model is.
My model usage is very low but I still do pay directly to Deepseek regularly as my tribute and contribution to them open sourcing their models as my gratitude and showing support for what I deem positive for overall social good.
I'm not sure if it's when you run out of crypto, or when your bank gets hit by ransomeware.
I hesitated to even post this comment as it sounds biased and xenophobic. I would love for someone to convince me I am wrong. Does anyone have any insight into the company behind deepseek hosting, and what their history of respecting data privacy is?
We use it that way and it works great.
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...
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.
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.
DeepSeek V4 Pro: $0.87
Qwen 3.7 Max: $7.50
Grok 4.3: $2.50
GLM 1.5: $3.08
Opus 4.7: $25.00
GPT-5.5: $30.00
Deepseek has made some incredible advancements in model efficiency, and more importantly actually publishes those advancements so everyone can benefit from them.
RIP.
Claude literally refuses to finish tasks in auto mode and just keeps saying, now is a good stopping point, when it's 1% done.
Codex literally does not follow directions.
May as well pay 1/20th the price.
Claude seems to have something that looks at how long you've been a customer and then just massively degrades quality.
When I started my subscription, Claude had none of these problems.
When I first started using Codex, it followed directions and performed well (and fast).
2 months into subscriptions they are both unusably terrible.
Remember Jevons paradox? [0] It isn't at Anthropic or Microsoft [0], but it is at DeepSeek.
[0] https://www.thelowdownblog.com/2026/05/microsoft-cancels-int...
First accessible model with useable 1 million context window for me.
You don't get the discount that Deepseek is providing, but it's still a cheap model (v4-pro is cheaper than sonnet)
I recall reading about that in an issue or in their Discord server.
But I would contact them formally to verify that.