# DeepSeek V4 Pro 0423 — API, capabilities & pricing | Y-API

> DeepSeek V4 Pro 0423 is the larger text-reasoning model in the original V4 pair. Its publisher describes a 1.6T-parameter MoE model with 49B activated, designed for demanding reasoning and software work rather than native image understanding.

This is the markdown representation of https://y-api.bestvirtualgoods.com/models/deepseek/deepseek-v4-pro. Generated by `scripts/generate-seo-assets.mjs` from the same copy the page renders — do not edit by hand.

Model ID: `deepseek/deepseek-v4-pro`

Sources reviewed: 2026-10-04. Y-API catalog snapshot: 2026-10-04.

## Choosing this model

Selection advice by Y-API. The checks below are suggested evaluations, not published test results.

### Where to start

Consider it for architecture reviews that must reconcile several constraints: database transactions, concurrency, failure recovery and migration order. Supply the relevant code and ask for falsifiable failure cases.

### What to watch for

Parameter count is not an end-to-end quality or speed guarantee. This is the 0423 entry, not every later Pro checkpoint; compare its actual fixes with newer Flash and GLM alternatives before allocating a larger budget.

## Model specifications

These are OpenRouter model-level specifications, not a Y-API compatibility test. A particular route may accept fewer input formats, parameters or tokens. Verify the features you need with a small request; a successful text response does not validate vision or tool calling.

| Field | Value |
| --- | --- |
| Context window | 1,048,576 tokens |
| Input | Text |
| Output | Text |
| Listed on OpenRouter | 2026-04-24 |
| Parameters listed by OpenRouter | `frequency_penalty`, `include_reasoning`, `logit_bias`, `logprobs`, `max_completion_tokens`, `max_tokens`, `min_p`, `presence_penalty`, `reasoning`, `reasoning_effort`, `repetition_penalty`, `response_format`, `seed`, `stop`, `structured_outputs`, `temperature`, `tool_choice`, `tools`, `top_k`, `top_logprobs`, `top_p` |

## Estimate your cost

| Price basis | Input / 1M tokens | Output / 1M tokens |
| --- | --- | --- |
| Account credit | $0.50 | $1.00 |
| Cash equivalent | $0.05 | $0.10 |

$1 paid adds $10 of credit. Cash equivalent = credit consumed ÷ 10; this is not the model publisher’s list price.

Input tokens / request: 1000. Output tokens / request: 500. Number of requests: 1000.

Estimated credit consumed: $1.00. Estimated cash equivalent: $0.10.

Illustrative token budget, not measured usage or a quote. Includes input and output; excludes separate media charges, cache discounts and retries. Include billed reasoning tokens in your output budget where applicable. Actual billing follows usage returned by the service.

### Same token budget, different models

| Model | Estimated credit consumed | Estimated cash equivalent |
| --- | --- | --- |
| [DeepSeek V4 Pro 0423](https://y-api.bestvirtualgoods.com/models/deepseek/deepseek-v4-pro) | $1.00 | $0.10 |
| [DeepSeek V4 Flash 0731](https://y-api.bestvirtualgoods.com/models/deepseek/deepseek-v4-flash-0731) | $0.30 | $0.03 |
| [GLM 5.3](https://y-api.bestvirtualgoods.com/models/z-ai/glm-5.3) | $3.90 | $0.39 |

## Use the API

These minimal, text-only requests use the exact Y-API model ID. They do not demonstrate image, audio, video, file or tool support. The output limit also needs room for reasoning; an empty answer with finish_reason=length can mean the budget was exhausted.

Set the TOKEN environment variable to a key from your console. Run this on your server or locally; never expose a key in browser code or a public repository.

### A task to try

Worker A locks account 1 then account 2. Worker B locks account 2 then account 1. Explain the failure and propose a consistent locking rule.

```bash
curl --fail-with-body --silent --show-error --max-time 120 \
  'https://api.y-api.bestvirtualgoods.com/v1/chat/completions' \
  -H "Authorization: Bearer ${TOKEN:?Set TOKEN first}" \
  -H 'Content-Type: application/json' \
  --data-binary @- <<'JSON'
{
  "model": "deepseek/deepseek-v4-pro",
  "messages": [
    {
      "role": "user",
      "content": "Worker A locks account 1 then account 2. Worker B locks account 2 then account 1. Explain the failure and propose a consistent locking rule."
    }
  ],
  "max_tokens": 4096
}
JSON
```

```python
import json
import os
import sys
import urllib.error
import urllib.request

payload = {
  "model": "deepseek/deepseek-v4-pro",
  "messages": [
    {
      "role": "user",
      "content": "Worker A locks account 1 then account 2. Worker B locks account 2 then account 1. Explain the failure and propose a consistent locking rule."
    }
  ],
  "max_tokens": 4096
}

request = urllib.request.Request(
    "https://api.y-api.bestvirtualgoods.com/v1/chat/completions",
    data=json.dumps(payload).encode("utf-8"),
    headers={
        "Authorization": "Bearer " + os.environ["TOKEN"],
        "Content-Type": "application/json",
    },
    method="POST",
)
try:
    with urllib.request.urlopen(request, timeout=120) as response:
        result = json.load(response)
    print(json.dumps(result, ensure_ascii=False, indent=2))
except urllib.error.HTTPError as error:
    print(error.read().decode("utf-8"), file=sys.stderr)
    raise SystemExit(1)
```

### How to evaluate the result

Require a concrete deadlock interleaving and a globally consistent lock order. Reject answers that merely add retries without addressing the cause.

## Before you choose

### Does Pro necessarily beat newer Flash revisions?

No. The tier name and parameter count do not establish that ranking. Use the same repository task, tool permissions and token budget, then compare test results and total cost.

## Sources & scope

Technical facts come from the cited model page and, where available, its linked publisher card. A card describes that checkpoint; it is not proof of the weights a gateway serves. Prices come only from the Y-API catalog. We do not claim measured latency, uptime or benchmark scores for this endpoint.

- [OpenRouter model page & specifications](https://openrouter.ai/deepseek/deepseek-v4-pro)
- [Publisher model card linked by OpenRouter](https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro)
- [Y-API catalog & prices (JSON)](https://y-api.bestvirtualgoods.com/models.json)

## Models to compare

Compare these alternatives on the same inputs. Their descriptions explain different roles; a lower price does not establish equivalent quality.

### [DeepSeek V4 Flash 0731](https://y-api.bestvirtualgoods.com/models/deepseek/deepseek-v4-flash-0731)

DeepSeek V4 Flash 0731 is the publisher’s official V4 Flash release, following the earlier preview. It remains a text-only model; its post-training revision focuses on coding, reasoning and agent tasks.

### [GLM 5.3](https://y-api.bestvirtualgoods.com/models/z-ai/glm-5.3)

GLM 5.3 builds on the GLM 5.2 base model with revised post-training for complex coding and long-running tasks. OpenRouter documents always-on reasoning for this entry, a meaningful distinction when budgeting output.

## Links

- HTML version of this page: https://y-api.bestvirtualgoods.com/models/deepseek/deepseek-v4-pro
- Site index for agents: https://y-api.bestvirtualgoods.com/llms.txt
- Full reference (single file): https://y-api.bestvirtualgoods.com/llms-full.txt
- OpenAPI 3.1 spec: https://y-api.bestvirtualgoods.com/openapi.json
- Model catalog (JSON, no key needed): https://y-api.bestvirtualgoods.com/models.json
- API base URL: `https://api.y-api.bestvirtualgoods.com/v1`
- Contact: support@bestvirtualgoods.com
- Model catalog: https://y-api.bestvirtualgoods.com/models
- Integration guide: https://y-api.bestvirtualgoods.com/docs