> ## Documentation Index
> Fetch the complete documentation index at: https://docs.ruapi.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# DeepSeek Flash: review and tests from Russia

> DeepSeek Flash after the 1017 update (17 October 2026): DeepSeek's benchmarks and independent tests, prices on RuAPI, speed from Moscow without a VPN, and a comparison with GPT-5.4 mini, Claude Haiku 5.5, Gemini 2.5 Flash and DeepSeek V4 Pro.

By number of requests, `deepseek-flash` is the most-used model on RuAPI. On 17 October 2026 DeepSeek updated it to version 1017 without changing the name: if you already call `deepseek-flash`, there's nothing to change. Below: what changed, what DeepSeek's own benchmarks and independent tests show, what it costs next to similar models, and how fast it answers from Russia.

**In short**

* **What it is.** DeepSeek's fast, low-cost model: a 1M-token context, image input, function calling, and it thinks before answering by default.
* **Quality.** By DeepSeek's numbers, version 1017 beats Claude Opus 5 and GPT-5.6 Sol on fixing bugs in real code (DeepSWE). Opus 5 is still ahead on terminal work and on building a whole project. Independent ranking Artificial Analysis gives it 45 points, more than DeepSeek V4 Pro (36).
* **Price on RuAPI.** Per 1M tokens: \$0.168 input, \$0.012 cache read, \$1.44 output.
* **Speed.** By our stats the first token arrives in 1.5 s on average. From Moscow without a VPN the first data came in 0.5 s.
* **Try it free.** New users usually get \$0.05 right away — enough for roughly 50 short questions (at 1,000 tokens per question and 600 per answer).

## What changed on 17 October

DeepSeek released version 1017 and pointed the `deepseek-flash` name in its API to it right away; DeepSeek's price did not change. According to DeepSeek, the new version:

* scores higher on benchmarks;
* finishes tasks faster;
* gives shorter answers — so you pay for fewer output tokens for the same result.

In DeepSeek's table, the biggest gains are on agent tasks: Terminal-Bench 4.0 went from 31.2 to 42.3, ProgramBench from 20.3 to 29.1, DeepSWE from 74.2 to 77.0. DeepSeek also says it trained the model further on building whole projects "from start to finish" — games, for example. The weights of the new version are open, as before (MIT license). Details are in DeepSeek's [announcement](https://api-docs.deepseek.com/news/news261017) of 17 October.

> [!NOTE]
>
> One name, two versions. Reviews and tests published before 17 October describe the September version of Flash — their numbers don't apply to version 1017.

## Specs

| | `deepseek-flash` |
| - | - |
| Context | 1M tokens |
| Max answer length | up to 384K tokens |
| Image input | yes |
| Function calling, JSON output | yes |
| Thinking mode | on by default; the reasoning comes in the `reasoning_content` field |
| Weights | open, MIT license |

Sources: [DeepSeek models and pricing page](https://api-docs.deepseek.com/quick_start/pricing), [model card on Hugging Face](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017). Data as of 20 October 2026.

## DeepSeek's benchmark results

The numbers come from the official model card on Hugging Face. DeepSeek measured them itself, with its own setup (for example, Terminal-Bench was run in Claude Code), so treat them as a guide, not a guarantee.

| Benchmark | Flash 1017 | Flash (September) | Claude Opus 5 | GPT-5.6 Sol |
| - | - | - | - | - |
| DeepSWE v1.1 (fixing real bugs in code) | **77.0** | 74.2 | 74.0 | 73.0 |
| Automation-Bench (task automation) | **60.5** | 54.8 | 50.3 | 45.8 |
| Terminal-Bench 4.0 (working in a terminal) | 42.3 | 31.2 | **51.8** | 39.9 |
| ProgramBench (writing programs) | 29.1 | 20.3 | **37.0** | 23.0 |
| NL2Repo-Bench (a whole project from a description) | 68.2 | 65.4 | **75.3** | 56.8 |
| HLE without tools (hard expert questions) | 42.6 | 36.8 | **56.3** | 44.5 |
| BabyVision with tools (understanding images) | 92.5 | 89.6 | **94.1** | 88.9 |

Bottom line: on fixing bugs and automating tasks, version 1017 is ahead of the flagships by DeepSeek's numbers, and it beats GPT-5.6 Sol on every row of the table except HLE. Where a model has to work on its own for a long time — in a terminal, on a whole project — Claude Opus 5 is still clearly stronger.

## What independent tests show

* **[Artificial Analysis](https://artificialanalysis.ai/models/deepseek-v4-1-flash-1017)** — an independent ranking that runs models through its own test suite. Version 1017 (at maximum reasoning) scores 45; [DeepSeek V4 Pro 0813](https://artificialanalysis.ai/providers/deepseek) scores 36. Through DeepSeek's API, Flash outputs about 210 tokens per second, and the first chunk of the answer arrives in about 1.1 s. The same page shows that the model thinks a lot: it used 210M output tokens on their tests, against a median of 140M for comparable models.
* **[Video review on Bilibili](https://www.bilibili.com/video/BV1txJB6BEqL/)** (17 October, 11 tasks of the author's own). Code and complex engineering tasks are clearly better than in the previous version, and it uses about a third fewer tokens. But creative writing in Chinese and basic image recognition got worse, and SVG graphics and knowledge of the 3D world remain weak spots. The author's verdict: the new version is stronger at code, but not better than the old one at everything.

Bottom line: the gains in code and agent tasks hold up from the outside too. But the model likes to think at length, and you pay for that thinking as well (see the note below). Before you move a workflow to Flash, run 5–10 of your typical tasks on it.

## What it costs on RuAPI

Prices per 1M tokens, as on the [pricing page](https://www.ruapi.ai/pricing?lng=en\&utm_source=docs\&utm_campaign=en-deepseek-flash-review):

| Model | Input | Cache read | Output |
| - | - | - | - |
| **`deepseek-flash`** | **\$0.168** | **\$0.012** | **\$1.44** |
| `claude-haiku-5-5`, request up to 100,000 tokens | \$0.12 | \$0.012 | \$0.60 |
| `claude-haiku-5-5`, request over 100,000 tokens | \$0.60 | \$0.06 | \$3 |
| `gemini-2.5-flash` | \$0.36 | \$0.09 | \$3 |
| `gpt-5.4-mini` | \$0.90 | \$0.09 | \$5.40 |
| `deepseek-v4-pro` | \$1.584 | \$0.06 | \$4.752 |
| `claude-sonnet-5-5` | \$2.40 | \$0.12 | \$12 |

* **Versus `gpt-5.4-mini`**, Flash is 5 times cheaper on input and almost 4 times cheaper on output.
* **Versus `gemini-2.5-flash`** — roughly half the price on both input and output.
* **Versus `claude-haiku-5-5`** it depends on request length. On short requests Haiku is cheaper. Once a request with its context goes over 100,000 tokens — and with agents like Cline and Claude Code it almost always does — Flash is 3.5 times cheaper than Haiku on input, and its cache read is 5 times cheaper.
* **Versus `deepseek-v4-pro`** — about 9 times cheaper on input and about 3 times cheaper on output.
* **Versus `claude-sonnet-5-5`** — 14 times cheaper on input and about 8 times cheaper on output. What that adds up to over a full day of agent work is in [“DeepSeek or Claude”](/en/deepseek-vs-claude).

> [!NOTE]
>
> The model's thinking is billed as output tokens too, and Flash thinks readily. If a task doesn't need reasoning, short answers cost less: ask the model to be brief.

## How fast it answers

We looked at two numbers.

* **Real requests over a week** (our server's stats, 14–20 October): the first meaningful token of the answer arrives in **1.5 s** on average. Only about 2.6% of requests waited longer than 3 s.
* **From Moscow without a VPN** (20 October, a test server in a Moscow data center): the streamed answer started arriving in **0.5 s**; an answer of up to 1,000 tokens, reasoning included, arrived in full in 6.8 s.

For comparison: connecting to DeepSeek directly, Artificial Analysis gets the first chunk of the answer in about 1.1 s — so the delay through RuAPI is of the same order. Home or mobile internet may give different numbers, but you won't wait several seconds for an answer to start.

## When to pick Flash and when another model

* **Flash** — nearly everything day to day: chat, translation, classification, extracting data from text, reading screenshots, coding agents with a long context.
* **`deepseek-v4-pro`** — only if it is clearly better on your own tasks. In the Artificial Analysis ranking, version 1017 beats V4 Pro (45 vs 36) and answers about twice as fast, while costing 3–9 times less. Pro also doesn't understand images.
* **Claude Sonnet or Opus** — when a model has to work on its own for a long time: long chains of actions in a terminal, a whole project. That's where Flash shows the biggest gap in the benchmarks.
* **`claude-haiku-5-5`** — very short requests where every fraction of a cent matters.

## How to connect

Flash uses the OpenAI-compatible protocol: any OpenAI SDK works, you only change the address and the model.

```python theme={null}
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_RUAPI_KEY",
    base_url="https://www.ruapi.ai/v1",
)

resp = client.chat.completions.create(
    model="deepseek-flash",
    messages=[{"role": "user", "content": "Explain what this function does and suggest tests"}],
)
print(resp.choices[0].message.content)
```

Ready-made settings for tools: [Cline](/en/integrations/cline), [Claude Code on DeepSeek](/en/integrations/claude-code-deepseek), [Cherry Studio](/en/integrations/cherry-studio). Step by step, from the key to the first request — in the [Quick Start](/en/quickstart). An overview of the whole family is on the [DeepSeek API](/en/deepseek-api) page.

## Try it free

New users usually get \$0.05 right away to try `deepseek-flash` for free. Other models open after a top-up from \$5 — in USDT or with a foreign-issued card. No USDT? [Buy it with rubles](/en/buy-usdt).

> **[Start for free](https://www.ruapi.ai/register?lng=en\&utm_source=docs\&utm_campaign=en-deepseek-flash-review)**
>
> Sign-up takes a minute, no VPN needed.

## Sources

* DeepSeek, [API changelog](https://api-docs.deepseek.com/updates/) and [update announcement](https://api-docs.deepseek.com/news/news261017), 17 October 2026 — version 1017, the `deepseek-flash` name, unchanged price.
* DeepSeek, [model card on Hugging Face](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017) — benchmark table, license.
* DeepSeek, [models and pricing](https://api-docs.deepseek.com/quick_start/pricing) — context, max answer length, features.
* Artificial Analysis, [model page](https://artificialanalysis.ai/models/deepseek-v4-1-flash-1017) and [DeepSeek models](https://artificialanalysis.ai/providers/deepseek) — rating, speed, token use; as of 20 October 2026.
* [Video review on Bilibili](https://www.bilibili.com/video/BV1txJB6BEqL/), 17 October 2026 — 11 hands-on tasks.
* RuAPI prices — [pricing page](https://www.ruapi.ai/pricing?lng=en\&utm_source=docs\&utm_campaign=en-deepseek-flash-review), as of 20 October 2026.


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