DeepSeek V4 Flash or V4.1 Flash: which cheap model to pick

If you are looking for a DeepSeek V4 Flash API for bulk tasks, the catalog holds a surprise: two models with almost identical names, deepseek-v4-flash and deepseek-v4.1-flash, sit side by side. It is natural to assume the newer one costs more. Here it is the other way round: V4.1 Flash is cheaper, and its intelligence index is higher. We go through the numbers as of October 18, 2026, cost the same job on both and show how to check the choice on your own data. Current prices are always at GET https://api.zukko.pro/v1/models and on the Models page in the dashboard.

The comparison in one table

Zukko prices, $ per 1M tokens. Strength is the Intelligence Index (Artificial Analysis).

What stands out immediately:

1. The newer version is cheaper on every line, both input and output.
2. Its intelligence index is 4 points higher (39 versus 35).
3. Both have a 1M-token context and neither accepts image input: for screenshots and scans you need another model (for example deepseek-v4-pro, which takes images, or gpt-6.1-sol).
4. For both models, the cache read price equals the input price, and cache writes are not billed separately. So DeepSeek has no separate cache discount in our tariff: a repeated prefix costs the same as regular input. This differs from Claude, where a cache read is noticeably cheaper than input.

Why a newer version can be both cheaper and stronger

The intuition "newer means more expensive" comes from subscriptions and premium lines. API prices work differently: the price per token depends on what serving the model costs the provider and how it is positioned, while the intelligence index measures quality separately. The two axes are not rigidly linked, so within one family a newer model can easily be both stronger and cheaper. Why exactly the provider set these prices, we do not know and will not guess. The practical conclusion matters: do not choose by version number. Look at price, context and index, then test on your own data.

Costing one job

Take a bulk task: classifying 1,000 support tickets. Assumptions (replace with your own): each request has 1,500 input tokens (instruction plus text) and 300 output tokens.

• Input: 1,000 × 1,500 = 1,500,000 tokens = 1.5M.
• Output: 1,000 × 300 = 300,000 tokens = 0.3M.

Formula: input × input price + output × output price.

• V4 Flash: 1.5 × 0.025 + 0.3 × 0.063 = 0.0375 + 0.0189 = $0.0564.
• V4.1 Flash: 1.5 × 0.013 + 0.3 × 0.038 = 0.0195 + 0.0114 = $0.0309.

The difference is $0.0255 per thousand requests. At a million requests it becomes $25.5, so the choice only matters at large volumes. On $1 of balance, these assumptions give about 32 such batches on V4.1 Flash (1 / 0.0309 ≈ 32.4).

For reference, the same calculation on neighboring cheap models at the same volumes:

• glm-5.3-flash (0.04 / 0.04, index 42, 128K context): 1.5 × 0.04 + 0.3 × 0.04 = 0.06 + 0.012 = $0.072.
• qwen3.8-flash (0.038 / 0.075, index 40, 1M context): 1.5 × 0.038 + 0.3 × 0.075 = 0.057 + 0.0225 = $0.0795.

The calculation ignores reasoning tokens if the model spends them: they count as output and can shift the total. Take real numbers from the usage field of the response.

A free DeepSeek V4 Flash API: what you can actually get

Many people look for free access to the DeepSeek V4 Flash API, but the honest answer is: Zukko has no free tier. Payment is per token from a shared dollar balance, top-up from $1. Running V4.1 Flash costs fractions of a cent per request, as the calculation above shows, but that is not free. Stay away from "free keys" on third-party sites: behind them there is usually someone else's account or a leak. Payment is available via SBP (the payment page adds an 8.5% fee on top), cryptocurrency and MasterCard cards (a fee of about 13%).

How to connect and switch

The model is called like any other: only the model string changes. Access from Russia goes through the gateway, and the request format stays OpenAI-compatible.

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.zukko.pro/v1",
    api_key=os.environ["ZUKKO_API_KEY"],
)

resp = client.chat.completions.create(
    model="deepseek-v4.1-flash",
    messages=[
        {"role": "system", "content": "Classify the ticket: billing, bug, other. Answer with one word."},
        {"role": "user", "content": "I can't top up my balance, the payment page won't open"},
    ],
    max_tokens=20,
)
print(resp.choices[0].message.content)
print(resp.usage.prompt_tokens, resp.usage.completion_tokens)

Note max_tokens: for short classifications set a small ceiling so accidental verbosity does not cost money.

Testing on your own data

The intelligence index is general, and your texts may behave differently. Collect 50-100 examples with a known correct answer and run both models:

import os
from openai import OpenAI

client = OpenAI(base_url="https://api.zukko.pro/v1", api_key=os.environ["ZUKKO_API_KEY"])
PRICES = {  # $ per 1M tokens as of Oct 18, 2026: (input, output)
    "deepseek-v4-flash": (0.025, 0.063),
    "deepseek-v4.1-flash": (0.013, 0.038),
}

def run(model, samples):
    ok, cost = 0, 0.0
    for text, expected in samples:
        r = client.chat.completions.create(
            model=model,

Look at two numbers: the share of correct answers and the cost. If V4.1 Flash scores at least as well as V4 Flash, switch. If V4 Flash does better on your task, stay on it while it remains in the catalog.

What to consider when switching

• A model can disappear. Providers switch models off; a request to a disabled one returns 503 with the code model_disabled. Keep a fallback model in your code and try it on this error (handling 503 and a fallback model↗).
• Picking a model too cheap for the task. If answers come out weak, move up the index: glm-5.3-flash (42), gpt-6.1-sol (52). Cost goes up, and you should recompute it with the formula above; more on choosing in the cheapest model for a task↗.
• Do not change both variables at once. First change only the model, run the examples, and only then change the prompt.

A description of all models is in the models documentation↗. You can connect the model with one key from the dashboard↗: create a key, set a daily limit and send your first request.

FAQ

Is DeepSeek V4.1 Flash definitely better than V4 Flash?

We do not claim quality. According to the table, V4.1 Flash is cheaper and its intelligence index is higher (39 versus 35). For your task this has to be tested on your own examples, for instance with the script above.

Do both models accept images?

No, the catalog marks both as "image input: no". For images pick a model with image support, such as deepseek-v4-pro or gpt-6.1-sol.

Does DeepSeek get a cache discount?

In our tariff the cache read price on both models equals the input price: 0.025 for V4 Flash and 0.013 for V4.1 Flash. There is no separate discount, so do not build optimization around the cache.

Where do I find current prices?

Call GET https://api.zukko.pro/v1/models or open the Models page in the dashboard. Provider prices change, so treat the table in this article as the state on October 18, 2026.