DeepSeek Error Codes Explained: Fix 400, 401, 402, 422, 429, 500 & 503

Quick answer: DeepSeek API error codes are easiest to fix when you separate request-side issues from provider-side issues. 400, 401, 402, and 422 usually mean you need to fix the request, API key, balance, or parameters. 429 means you are sending requests too quickly or hitting a dynamic concurrency limit. 500 and 503 usually mean retry after a short wait and check service health. This guide uses the current V4 model IDs for error-code examples.

Independent note: Chat-Deep.ai is an independent DeepSeek guide and browser access site. It is not affiliated with DeepSeek, DeepSeek.com, the official DeepSeek app, or the official DeepSeek developer platform. For API keys, billing, account balance, official support, and production-critical API decisions, use official DeepSeek resources.

Last verified: April 24, 2026.

Current DeepSeek API snapshot for error debugging

• Current API model IDs: deepseek-v4-flash and deepseek-v4-pro
• Current API generation: DeepSeek-V4 Preview
• Base URL for OpenAI-compatible requests: https://api.deepseek.com
• Context length: 1M tokens
• Maximum output: 384K tokens
• Thinking mode and non-thinking mode: supported on both current V4 API models
• JSON Output and Tool Calls: supported on both current V4 API models
• Legacy aliases: deepseek-chat and deepseek-reasoner currently route to deepseek-v4-flash non-thinking and thinking modes
• Legacy alias retirement: DeepSeek says deepseek-chat and deepseek-reasoner will be retired after July 24, 2026, 15:59 UTC

This page is updated to match the current Chat-Deep.ai homepage, DeepSeek API guide, DeepSeek API pricing guide, DeepSeek Thinking Mode guide, DeepSeek Tool Calls guide, and DeepSeek troubleshooting guide.

DeepSeek Error Codes at a Glance

The official DeepSeek API error-code list centers on seven main HTTP responses: 400, 401, 402, 422, 429, 500, and 503.

Code	Official meaning	Fastest next step	Retry or fix?
400	Invalid Format	Fix the request body format and compare it with the official API schema	Fix request
401	Authentication Fails	Check API key, Bearer header, environment variable, and provider endpoint	Fix auth
402	Insufficient Balance	Check account balance and top up on the official DeepSeek platform	Fix account state
422	Invalid Parameters	Remove unsupported fields, fix model ID, schema, mode, or parameter values	Fix parameters
429	Rate Limit Reached	Reduce concurrency, queue requests, and use exponential backoff	Retry with pacing
500	Server Error	Retry after a brief wait and check status if it persists	Retry
503	Server Overloaded	Wait, reduce pressure, retry later, and check status	Retry later

Use this table as your first decision point. Blindly retrying 400, 401, 402, or 422 usually wastes requests. Retrying 429, 500, and 503 can help, but only with pacing, backoff, and retry limits.

How to tell whether the error is on your side or DeepSeek’s side

A simple rule works well: 4xx errors usually start on your side, while 5xx errors usually start on the provider side. The exception is 429, which means the request may be valid but your traffic pattern is too aggressive for current conditions.

Category	Codes	Primary action
Request, auth, or account issue	400, 401, 402, 422	Change request body, credentials, balance, model ID, or parameters before retrying.
Traffic pacing issue	429	Reduce request rate, lower concurrency, queue requests, and retry with backoff.
Provider-side issue or overload	500, 503	Retry after a brief wait, reduce pressure, and check official status if the issue persists.

If a minimal current V4 request succeeds but your production workflow fails, the issue is probably in optional fields, tools, JSON Output, thinking-mode history, streaming parsing, large context, or wrapper logic. If the minimal request also fails, use the returned status code to decide which layer to debug first.

Minimal valid DeepSeek V4 request to compare against

When you are not sure whether the issue is request format, authentication, model naming, or parameters, compare your failing request to this minimal current V4 request.

curl https://api.deepseek.com/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer ${DEEPSEEK_API_KEY}" \
  -d '{
    "model": "deepseek-v4-flash",
    "messages": [
      {"role": "user", "content": "Reply with: DeepSeek API works."}
    ],
    "thinking": {"type": "disabled"},
    "stream": false
  }'

If this request works, your base URL, API key, model ID, and basic message structure are probably valid. Add your original parameters back one at a time until the error returns.

Minimal Python smoke test

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["DEEPSEEK_API_KEY"],
    base_url="https://api.deepseek.com",
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[
        {"role": "user", "content": "Reply with: DeepSeek API works."}
    ],
    extra_body={"thinking": {"type": "disabled"}},
    stream=False,
)

print(response.choices[0].message.content)

Use deepseek-v4-flash in non-thinking mode for the first smoke test because it is the simplest current V4 path for fast, lower-cost debugging.

400 Invalid Format

What it means: DeepSeek could not accept the request body in the format it expected. This is usually a structural request-body problem, not a model-quality problem.

Most common causes:

• Malformed JSON
• Missing required model or messages field
• Wrong message role or malformed messages array
• Tool result sent without the matching tool_call_id
• Assistant/tool message order broken in a Tool Calls loop
• Thinking-mode tool loop where the assistant message history was rebuilt incorrectly
• Using a request shape copied from an unsupported endpoint

Fastest fix: strip the request down to the minimal V4 smoke test above. If that succeeds, add optional fields back one by one.

Retry or change something? Change the request first. Retrying the same malformed body rarely helps.

Common 400 fixes

• Validate JSON before sending.
• Confirm messages is a non-empty array.
• Use only valid message roles: system, user, assistant, and tool.
• When returning a tool result, include the exact tool_call_id.
• During thinking + tool-call loops, preserve the full assistant message while the active loop continues.
• Do not send arbitrary old reasoning_content into a fresh normal user turn.

401 Authentication Fails

What it means: the API could not authenticate your request because the API key is missing, wrong, expired, revoked, malformed, or sent to the wrong provider endpoint.

Most common causes:

• Missing Authorization header
• Missing Bearer prefix
• Wrong API key
• API key not loaded from environment variables
• Using an OpenAI API key with the DeepSeek base URL
• Using a DeepSeek API key with the default OpenAI endpoint
• Copied key includes extra spaces, quotes, or hidden characters

Correct authorization format:

Authorization: Bearer YOUR_DEEPSEEK_API_KEY

Fastest fix: confirm that your request is going to https://api.deepseek.com, that the key was created on the official DeepSeek platform, and that your runtime can actually read DEEPSEEK_API_KEY.

Retry or change something? Fix authentication first. A 401 error is not solved by waiting.

Python key check

import os

api_key = os.environ.get("DEEPSEEK_API_KEY")

if not api_key:
    raise RuntimeError("Missing DEEPSEEK_API_KEY")

if not api_key.startswith("sk-"):
    print("Warning: key format may be unexpected. Verify it on the official DeepSeek platform.")

402 Insufficient Balance

What it means: your request reached DeepSeek and authentication passed, but the account does not have enough balance to process the request.

Most common causes:

• Prepaid balance is depleted
• Granted balance is exhausted
• Application scaled faster than expected
• Long prompts, long outputs, retries, tools, or agent loops increased usage
• Assuming the official web/app experience and the developer API share the same pricing model

Fastest fix: check your balance on the official DeepSeek platform and top up if needed.

Retry or change something? Retrying will not fix 402 until the balance issue is resolved.

How to prevent it: log token usage and model ID for every request, monitor daily spend, and use the DeepSeek API pricing guide.

422 Invalid Parameters

What it means: your request body reached the correct API surface, but one or more parameters are invalid, unsupported, malformed, or incompatible with the selected model or mode.

Most common causes:

• Wrong model ID
• Using old V3.2-era model names as if they were current primary models
• Unsupported request parameter
• Wrong parameter type
• Invalid response_format
• Invalid tool schema
• Strict-mode schema does not match DeepSeek’s supported subset
• Beta-only feature used on the normal base URL
• Using an OpenAI-only endpoint or parameter that DeepSeek does not document

Fastest fix: reduce the payload to a minimal working request, confirm it works, then add parameters back one by one.

Retry or change something? Change the payload. Repeating the same invalid parameters is wasted traffic.

422 model-name checklist

• Use deepseek-v4-flash for fast, economical requests.
• Use deepseek-v4-pro for hard reasoning, coding, long-context, and agentic workflows.
• Keep deepseek-chat and deepseek-reasoner only as legacy compatibility notes.
• Do not describe V3.2, 128K, or old pricing as the current hosted API state.

422 JSON Output checklist

• Use response_format={"type":"json_object"}.
• Explicitly ask the model to return JSON in the prompt.
• Provide the target JSON shape.
• Set enough max_tokens so JSON is not cut off.
• Validate the parsed JSON in your app.

422 Tool Calls checklist

• Use tools as an array.
• Use only function tools.
• Keep function names within the allowed character and length limits.
• Validate the JSON Schema.
• For strict mode, use https://api.deepseek.com/beta and strict: true.
• Do not execute tool arguments before validating them.

429 Rate Limit Reached

What it means: you are sending requests too quickly for current server conditions or you reached a dynamic concurrency limit.

Most common causes:

• Too many parallel workers
• Retry loop without delay
• Traffic burst after queue drain
• Agent or RAG workflow making many model calls per user request
• Streaming jobs held open while new jobs continue to start

Fastest fix: reduce concurrency, queue work, and add exponential backoff with jitter.

Retry or change something? Retry with pacing. Do not retry instantly.

Retry and backoff pattern

import random
import time

RETRYABLE_STATUS_CODES = {429, 500, 503}
MAX_RETRIES = 5

for attempt in range(MAX_RETRIES):
    response = call_deepseek()

    if response.status_code < 400:
        break

    if response.status_code not in RETRYABLE_STATUS_CODES:
        raise RuntimeError(
            f"Do not blindly retry this error: {response.status_code} {response.text}"
        )

    sleep_seconds = min(30, (2 ** attempt) + random.random())
    time.sleep(sleep_seconds)
else:
    raise RuntimeError("DeepSeek is still unavailable after multiple retries.")

Keep-alive behavior under load

During high traffic, the official rate-limit guidance says non-streaming requests may continuously return empty lines while waiting, and streaming requests may return SSE keep-alive comments such as : keep-alive. If you parse raw HTTP responses yourself, ignore these keep-alive signals and wait for the real JSON body or final stream event.

If a request has not started inference after 10 minutes, the server may close the connection. Your application should set timeouts and handle closed connections gracefully.

500 Server Error

What it means: DeepSeek’s server encountered an internal issue.

Most common causes:

• Temporary backend issue
• Partial service instability
• Provider-side processing problem
• Short-lived infrastructure fault

Fastest fix: retry after a brief wait. If the issue persists across minimal requests and multiple users, check the official DeepSeek status page.

Retry or change something? Retry first. If a minimal request works but one special payload still fails, then inspect that payload for format or parameter problems.

503 Server Overloaded

What it means: the server is overloaded due to high traffic.

Most common causes:

• Heavy platform demand
• Temporary provider overload
• Your app is sending too many concurrent requests
• Large requests are waiting for scheduling

Fastest fix: wait, reduce concurrency, retry later, and use graceful fallback.

Retry or change something? Retry later with backoff. A 503 should also trigger queueing, load shedding, and user-facing fallback messages in production apps.

DeepSeek V4 model troubleshooting

Many old errors come from copying outdated examples. For current DeepSeek API debugging, start with V4 model names and only mention old aliases as migration notes.

Model or alias	Current role	Use in error debugging
deepseek-v4-flash	Current V4 model	Best first model for minimal smoke tests, low-latency debugging, JSON Output, and routine tool calls.
deepseek-v4-pro	Current V4 model	Use for hard reasoning, complex coding, long-context, and agentic workflows.
deepseek-chat	Legacy compatibility alias	Migration only. Currently routes to deepseek-v4-flash non-thinking mode.
deepseek-reasoner	Legacy compatibility alias	Migration only. Currently routes to deepseek-v4-flash thinking mode.

Common model-related error fixes

• Replace old model="deepseek-chat" examples with model="deepseek-v4-flash".
• Replace old model="deepseek-reasoner" examples with model="deepseek-v4-pro" plus thinking enabled where needed.
• Use thinking: {"type":"disabled"} for simple smoke tests.
• Use thinking: {"type":"enabled"} and reasoning_effort for reasoning-heavy tests.
• Do not debug a complex agent before a minimal V4 request works.

Python error handling with the OpenAI SDK

If you use the OpenAI Python SDK with DeepSeek, the SDK may surface DeepSeek provider errors through SDK error classes. Treat the HTTP status code as the source of the debugging decision.

import os
import openai
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["DEEPSEEK_API_KEY"],
    base_url="https://api.deepseek.com",
    timeout=30.0,
    max_retries=2,
)

try:
    response = client.with_options(timeout=60.0).chat.completions.create(
        model="deepseek-v4-flash",
        messages=[
            {"role": "user", "content": "Return one short API reliability tip."}
        ],
        extra_body={"thinking": {"type": "disabled"}},
        stream=False,
    )

    print(response.choices[0].message.content)

except openai.APIConnectionError as exc:
    print("Connection problem or timeout while reaching the API.")
    print(str(exc.__cause__) if exc.__cause__ else "No low-level cause available.")

except openai.RateLimitError as exc:
    print("429 rate limit or traffic-related throttling. Back off and retry later.")
    print("request_id:", getattr(exc, "request_id", None))

except openai.APIStatusError as exc:
    print(f"API returned status code: {exc.status_code}")
    print("request_id:", getattr(exc, "request_id", None))
    print("Response body:")
    print(exc.response)

Node.js and TypeScript error handling

In Node.js and TypeScript, use baseURL with a capital URL. Do not use Python’s base_url spelling in JavaScript.

import "dotenv/config";
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.DEEPSEEK_API_KEY,
  baseURL: "https://api.deepseek.com",
  timeout: 30_000,
  maxRetries: 2,
});

type DeepSeekChatBody =
  Parameters<typeof client.chat.completions.create>[0] & {
    thinking?: { type: "enabled" | "disabled" };
  };

async function main(): Promise<void> {
  try {
    const completion = await client.chat.completions.create({
      model: "deepseek-v4-flash",
      messages: [
        { role: "user", content: "Return one TypeScript API reliability tip." },
      ],
      stream: false,
      thinking: { type: "disabled" },
    } as DeepSeekChatBody);

    console.log(completion.choices[0]?.message?.content ?? "");
  } catch (error) {
    if (error instanceof OpenAI.AuthenticationError) {
      console.error("401 authentication failed. Check your DeepSeek API key.");
      return;
    }

    if (error instanceof OpenAI.RateLimitError) {
      console.error("429 rate limit or traffic-related throttling. Retry with backoff.");
      return;
    }

    if (error instanceof OpenAI.InternalServerError) {
      console.error("DeepSeek server error or overload. Retry after a brief wait.");
      return;
    }

    if (error instanceof OpenAI.APIConnectionTimeoutError) {
      console.error("Connection timed out while waiting for the API.");
      return;
    }

    if (error instanceof OpenAI.APIConnectionError) {
      console.error("Network or connection problem while reaching the API.");
      console.error(error.message);
      return;
    }

    if (error instanceof OpenAI.APIError) {
      console.error("API returned an error.");
      console.error("status:", error.status);
      console.error("message:", error.message);
      return;
    }

    throw error;
  }
}

main().catch((error) => {
  console.error(error);
  process.exit(1);
});

JSON Output, Tool Calls, and Thinking Mode errors

Many DeepSeek errors happen only after you add advanced features. Debug them one feature at a time.

Feature	Common error	Likely cause	Fix
JSON Output	400, 422, long-running response, truncated JSON	Missing JSON instruction, wrong response_format, low max_tokens, or invalid parser assumption	Set response_format, include the word JSON in the prompt, provide a JSON example, and validate output.
Tool Calls	400 or 422	Bad tool schema, missing tool_call_id, wrong message order, or invalid tool arguments	Validate tool schema and follow the model-proposes / app-executes / tool-result loop.
Strict Tool Mode	422	Using normal base URL, missing strict: true, unsupported schema keywords, or missing additionalProperties:false	Use beta base URL and DeepSeek’s supported strict-mode schema subset.
Thinking Mode	400, unexpected output, high usage	Mishandled reasoning_content, wrong tool-loop history, or too much output	Keep reasoning fields separate, preserve full assistant messages in active tool loops, and set output limits intentionally.
Streaming	Parser looks stuck or misses usage	Parser assumes every chunk has visible text, ignores keep-alives, or misses final usage chunk	Handle empty chunks and request stream_options.include_usage when usage is needed.

How to prevent DeepSeek API errors in production

• Keep one minimal known-good V4 request for smoke testing.
• Use deepseek-v4-flash or deepseek-v4-pro in new code.
• Keep legacy aliases only in migration notes.
• Validate JSON shape, required fields, tool schemas, and parameter types before sending.
• Store API keys in a secrets manager or server-side environment variables.
• Never expose API keys in browser JavaScript, mobile bundles, screenshots, logs, or public repositories.
• Monitor 4xx and 5xx separately.
• Track status code, model ID, endpoint, feature, request size, finish reason, and token usage.
• Add pacing, queueing, and exponential backoff for 429 and 503.
• Use retry budgets; never create infinite retry loops.
• Check balance before production workloads to avoid 402.
• Use DeepSeek Pricing to monitor costs.
• Check the official DeepSeek status page when 5xx errors persist.

DeepSeek API debugging decision tree

Symptom	First check	Next action
No HTTP response	Network, DNS, firewall, proxy	Test from another network or run a minimal curl request.
401	API key and Bearer header	Confirm the key is valid and the request targets https://api.deepseek.com.
402	Account balance	Top up or reduce usage before retrying.
400	Request body shape	Remove optional fields and compare with the Chat Completion schema.
422	Model ID and parameters	Use current V4 IDs and remove unsupported fields.
429	Concurrency and retry loops	Queue, back off, and reduce parallel requests.
500	Temporary provider-side issue	Retry briefly and check status if repeated.
503	Overload	Retry later, lower traffic, and provide graceful fallback.

Related DeepSeek guides

• DeepSeek API Guide — current V4 model IDs, base URL, setup, and migration notes
• DeepSeek Not Working Troubleshooting — web, app, API, network, login, and status checks
• OpenAI SDK with DeepSeek — Python and Node.js migration examples
• DeepSeek Python SDK Guide — Python examples, streaming, JSON, tools, and errors
• DeepSeek Node.js TypeScript Guide — TypeScript examples and SDK error handling
• DeepSeek Tool Calls — function calling, strict mode, and tool-loop debugging
• DeepSeek Thinking Mode — reasoning output and thinking-mode tool loops
• DeepSeek JSON Output — structured output and JSON troubleshooting
• DeepSeek API Pricing — current V4 rates and billing explanation
• DeepSeek Status Guide — official status links and outage troubleshooting

DeepSeek Error Codes FAQ

Conclusion

DeepSeek API errors become much easier to solve when you treat each status code as a routing signal. Fix request format for 400, authentication for 401, balance for 402, parameters for 422, pacing for 429, and retry/status handling for 500 and 503.

For current API debugging, start with a minimal request using deepseek-v4-flash. Once the basic request works, add streaming, JSON Output, Tool Calls, thinking mode, long context, RAG, agents, and retry logic one layer at a time. This keeps V4 model naming, error handling.

Official sources and last verified

Last verified: April 24, 2026. DeepSeek model names, pricing, error codes, request schema, rate behavior, status, and deprecation dates can change. Use the official sources below when making production decisions.

• DeepSeek Error Codes
• DeepSeek Models & Pricing
• DeepSeek-V4 Preview Release
• DeepSeek Create Chat Completion API Reference
• DeepSeek Rate Limit
• DeepSeek JSON Output
• DeepSeek Tool Calls
• DeepSeek Thinking Mode
• DeepSeek official status page