Which of them takes image input?

Only Kimi K3. Neither DeepSeek V4 Flash nor DeepSeek V4 Pro accepts an image, and the request is refused at the API layer rather than answered badly. If your prompt has a picture in it, the comparison is settled.

Which plan do I need for each?

Any of them. All three are on every plan and on the pay as you go wallet, so a 5 EUR credit pack with no subscription reaches all three. What changes with the plan is the budget: 165,000 credits on a 5 EUR pack against 2,350,000 a month on the 49 EUR Pro plan.

Is there a cheap DeepSeek without a subscription?

Yes, DeepSeek V3.2 sits in the same picker at 0.026 credits per input token and 0.038 per output token, with a think toggle and no image input. A 5 EUR pack of 165,000 credits is roughly 4.3 million output tokens on it, against about 9.2 million on DeepSeek V4 Flash and about 115,000 on Kimi K3.

How many tokens does a budget buy?

The Pro plan is 2,350,000 credits a month. Spent entirely on output tokens that is about 130 million on DeepSeek V4 Flash, about 9 million on DeepSeek V4 Pro and about 1.6 million on Kimi K3. A 5 EUR pack of 165,000 credits is about 9.2 million, 635,000 and 115,000 on the same three. Input tokens draw from the same wallet, so real usage lands below those figures.

Do all three do tool calls and long context?

Yes. All three call tools natively and all three hold a 1M token context, so Agent and coding modes work on any of them. The cheap model is not a downgrade in the machinery.

Kimi K3 vs DeepSeek V4: price, thinking, vision, plan

Q: Is Kimi K3 better than DeepSeek V4?

On a hard prompt, often yes. On the price sheet, not by anything like enough. Kimi K3 output is roughly 79 times the price of DeepSeek V4 Flash output, and no quality gap is 79 times. Keep the cheap model as the default and switch for the prompts that need it.

Short version, because most comparisons bury it: DeepSeek V4 Flash is the volume model and Kimi K3 is the one that reads pictures. If that settles it for you, stop here. The rest is the numbers behind it and what a fixed budget buys on each.

The table

	Kimi K3	DeepSeek V4 Flash	DeepSeek V4 Pro
Plan	All three on every plan, including a credit pack with no subscription
Image input	Yes	No	No
Thinking	Toggle, and switching it off really stops it	Toggle	Toggle
Context	1M tokens	1M tokens	1M tokens
Tool calls	Native	Native	Native
Credits per input token	0.285	0.008	0.13
Credits per output token	1.425	0.018	0.26

One credit is $0.00001 of wholesale inference cost, and the meter charges what the compute costs, so those rows are the real bill and not a marketing rate card. Current per model rates sit next to each model on the pricing page, because upstream prices move.

The price gap is not close

Kimi K3 output is roughly 79 times the price of DeepSeek V4 Flash output and about 5 times DeepSeek V4 Pro. Nothing in the quality comparison is 79 times anything. That is the whole shape of this decision: you are not choosing a better model, you are choosing where a fixed number of credits goes.

Concretely, spent entirely on output tokens, from the smallest budget we sell and from the 49 EUR Pro plan:

Budget	DeepSeek V4 Flash	DeepSeek V4 Pro	Kimi K3
5 EUR pack, 165,000 credits	about 9.2 million	about 635,000	about 115,000
Pro, 2,350,000 credits	about 130 million	about 9 million	about 1.6 million

Input tokens come out of the same wallet, so a long context chat lands below every figure in that table. The ordering does not change.

Where Kimi K3 earns it

Two places, and they are narrow but real.

The first is image input. Neither DeepSeek V4 model takes a picture. Ask them to and the request comes back refused at the API layer, not answered badly. If your prompt has a screenshot, a photo or a diagram in it, this comparison is already over.

The second is a genuinely hard prompt where you want a reasoning pass from a very large generalist. Kimi K3 is a 2.8 trillion parameter multimodal reasoner and it does hold more of a tangled input in its head. That is worth credits on the prompt that actually needs it, and it is worth nothing on the other ninety turns of the session.

Where DeepSeek wins outright

Agent loops, coding loops, long roleplay, bulk summarising, anything that emits a lot of tokens. All three call tools natively, all three hold a 1M context, so the cheap one is not a downgrade in the machinery, it is a downgrade in nothing you can feel until the prompt gets hard. The split between the two DeepSeek sizes has its own page: DeepSeek V4 Flash vs V4 Pro.

What a plan actually buys

All three are on every plan and on the pay as you go wallet, so a 5 EUR credit pack with no subscription reaches Kimi K3, DeepSeek V4 Flash and DeepSeek V4 Pro alike. A bigger plan buys more credits, never a longer model list.

So the token price is the only thing left to weigh. On a 5 EUR pack of 165,000 credits, spent on output, that is roughly 9.2 million tokens on DeepSeek V4 Flash and roughly 115,000 on Kimi K3. If you want a cheap DeepSeek that is cheaper still to keep open all day, DeepSeek V3.2 sits in the same picker at 0.026 credits per input token and 0.038 per output token, with a think toggle and no image input, which is roughly 4.3 million output tokens on the same pack. Same wallet, same picker, one click apart.

The decision table

What you are doing	Pick	Why
Any prompt with an image in it	Kimi K3	The only one of the three that takes image input at all.
Agent or coding loops with many tool calls	DeepSeek V4 Flash	Loops emit a lot of tokens and all three call tools natively.
Long sessions, roleplay, bulk drafting	DeepSeek V4 Flash	Volume problems are won by the cheaper model, every time.
One hard reasoning prompt that came back wrong twice	Kimi K3	This is the case worth spending credits on.
No subscription, a 5 EUR pack	DeepSeek V4 Flash for volume, Kimi K3 for pictures	The pack reaches all three, so pick on the token price rather than on access.
Bigger budget, mixed workload	Flash by default, K3 on demand	Same account, same picker. The mistake is picking one and staying there out of habit.

Setting either of them up

Both live behind the same browser Studio, the same Cloud switch in the desktop app, and the same OpenAI compatible endpoint at https://lu-labs.ai/api/inference/v1. The model ids are moonshotai/Kimi-K3, deepseek-ai/DeepSeek-V4-Flash-0731 and deepseek-ai/DeepSeek-V4-Pro-0813. Step by step in the Kimi K3 online guide and DeepSeek V4 Flash in the cloud.