LU Labs Cloud

DeepSeek V4.1 Flash online, no 510 GB download.

DeepSeek's newest open-weight model, running on our GPUs and answering in your browser. It reads images, holds a million tokens of context and went into our catalog on the day the weights went public. Every plan and every credit pack carries it, so a €5 pack reaches it without a subscription, and the Hosted plan is €19 a month.

Just looking? Open the Studio demo, no account needed

What DeepSeek V4.1 Flash is

A multimodal mixture-of-experts model with a 552 billion parameter backbone, released under the MIT licence on 10 September 2026. It activates 8 billion parameters per token while reading your prompt and 16 billion while writing the answer, which is why it is quick for its size. The context window is 1,048,576 tokens and it reasons on every turn.

The engineering behind it is aimed at one thing: the key value cache, the memory a model keeps for every token it has already seen. DeepSeek puts theirs at 890 bytes per token, so a full million token conversation costs roughly 930 MB of cache instead of the tens of gigabytes this usually implies. On long agent runs, where the conversation grows all day, that is the whole game.

The weights are public and permissively licensed, so running it yourself is allowed. It is also a 510 GB checkpoint whose smallest community quantisation on release day was 168.9 GB, with no released runtime able to execute it yet. Hosted is not a compromise here, it is the only route that exists this week.

What you get

  • Chat in the browser, with no install, no driver and no VRAM check. Open the Studio, pick the model, type.
  • Image input. Paste a screenshot into the composer and ask about it. The older DeepSeek V4 Flash 0731 refuses images; this one reads them.
  • Native tool calls, so Agent mode and the coding agent run on it directly with no prompt translation in between.
  • A million tokens of context that stays affordable, because the cache behind it is small by design rather than by truncation.
  • All 47 chat models on the same account, plus the image, video and audio studios. This is one pick in the list, not a separate product.

Call it from your own code

Create a key under Cloud API keys in account settings, point the base URL at https://lu-labs.ai/api/inference/v1 and send the catalog model id. Anything that speaks the OpenAI chat completions format works, including Aider, LibreChat and a plain curl call. The key spends your credits and cannot read or change your account.

curl https://lu-labs.ai/api/inference/v1/chat/completions \
  -H "Authorization: Bearer YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepseek-ai/DeepSeek-V4.1-Flash",
       "messages":[{"role":"user","content":"Hello"}]}'

How to start in three steps

  1. Buy a €5 credit pack, or take the Hosted plan if you want a monthly budget. Card details go to Stripe and the payment is secured with 3D Secure.
  2. The Studio opens on your account. Pick DeepSeek V4.1 Flash in the model picker.
  3. Type, or paste a screenshot. For scripts, create an API key in account settings and use the base URL above.

What it costs

5
Credit pack, once

165k credits, roughly 1,375,000 output tokens on DeepSeek V4.1 Flash. No subscription, no renewal, and the credits do not expire.

See the packs
19
Hosted, per month

A monthly credit budget for chat, code, image and video, the same full catalog, and API keys. Cancel any time.

Start on Hosted

The honest limits

This model reasons on every turn and there is no way to switch that off, so a short question still buys a short think. That is a property of the model, not a setting we withheld: we measured the off signal and it made the turn longer, not shorter. The token count above is the floor of what a pack buys, not an average of your week, because input tokens draw from the same wallet and a long conversation carries its whole history into every turn. Credits are one pool for text, images and video together. Cloud runs on shared hardware, so at busy hours a request can wait a few seconds before it starts streaming. The catalog is curated: we host open-weight models we have priced and tested, and you cannot upload your own base model. Account data is hosted in the EU and you can delete it yourself. We never train on your data and we never sell it.

Questions

Can I use DeepSeek V4.1 Flash online without a GPU?

Yes. The model runs on our managed NVIDIA H100, A100 and B200 class GPUs and answers in the browser, so your machine only sends the prompt and shows the reply. That matters more here than usual: the published checkpoint is 510 GB and the smallest community quant on release day was 168.9 GB, which is not a desk machine.

Which plan do I need for DeepSeek V4.1 Flash?

Any of them. Every plan and every credit pack carries the whole chat catalog, so you do not need Pro or Max for this one. The cheapest way in is a €5 credit pack with no subscription. The Hosted plan at €19 a month buys more credits, not more access.

Does it read images and call tools?

Both. It takes image input natively, which the older DeepSeek V4 Flash 0731 did not, and its tool calls go through the upstream tool parameter directly, so Agent mode and the coding agent run on it without a translation layer.

Why is there no Think switch on this model?

Because we measured what the off signal actually does. Left alone the model answers in about 42 output tokens with roughly 120 characters of separate reasoning. Told to stop reasoning, the reasoning field comes back empty and the turn grows to between 51 and 82 output tokens, because the monologue moves into the answer instead. A switch that makes a reply longer and dearer is worse than no switch, so the catalog marks this one as always reasoning.

How does it compare with DeepSeek V4 Flash 0731?

They share a word in the name and little else. V4 Flash 0731 is the cheap workhorse and costs a fraction per output token, but it cannot read images. V4.1 Flash reads images, reasons every turn, and its architecture is built around a small key value cache, which is why DeepSeek's own table has it leading on long agent benchmarks rather than on single questions.

Can I call it from my own code?

Yes. Create a personal API key under Cloud API keys in account settings, point any OpenAI-compatible client at https://lu-labs.ai/api/inference/v1 and pass the model id. The key spends your credits and cannot read or change your account.