DeepSeek V4 Pro 0813

deepseek/deepseek-v4-pro-0813
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ToolsJSONReasoning
by DeepSeek · 2026-08-12

DeepSeek V4 Pro 0813 is the official release of DeepSeek's flagship V4 Pro model, superseding the April preview and rolled out simultaneously across the app, web, and API. It serves a 1M-token context window with up to 384K output tokens, supports thinking and non-thinking modes with selectable low / high / max reasoning effort, plus JSON output and tool calls, and natively speaks the Responses API with a targeted adaptation for Codex-style coding agents. The 0813 revision is a major step up in agent capability, with DeepSeek reporting especially strong gains in production environments on its published agent benchmarks — 87.9 on Terminal Bench 2.1, 83.3 on Cybergym, 74.1 on Toolathlon Verified, 62.7 on DeepSWE, 61.5 on NL2Repo, and 42.7 / 60.0 on HLE without / with tools. On the DeepSeek first-party API this revision is what the deepseek-v4-pro model id now serves; the dated identifier lists the same revision for callers that reference it by date. It is a strong pick for demanding coding agents, terminal and tool-use workloads, and complex agentic pipelines.

ctx1M tokens
Max output384K
Inputtext
Outputtext
p50 TTFT781 ms
INPUT$0.44/ 1M tokens
OUTPUT$0.88/ 1M tokens
p50 TTFT781 ms7d
p95 TTFT1.94 s7d
TRAFFIC3397.0Mtokens / 7d

Code samples

Call from any SDK

OpenAI-compatible — keep the SDK you already use

  • OpenAI SDKhttps://api.orcarouter.ai/v1
  • Anthropic SDKhttps://api.orcarouter.ai
import os

from openai import OpenAI

client = OpenAI(
    base_url="https://api.orcarouter.ai/v1",
    api_key=os.environ["ORCAROUTER_API_KEY"],
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v4-pro-0813",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)

Supported parameters

  • frequency_penalty
  • include_reasoning
  • logit_bias
  • logprobs
  • 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

Pricing

Input / 1M tokens · Off-peak$0.442
Output / 1M tokens · Off-peak$0.884
Cache read / 1M · Off-peak$0.060
Peak hours01:00–04:00, 06:00–10:00 ×2 (UTC)
Input / 1M tokens · ×2$0.884
Output / 1M tokens · ×2$1.768
Cache read / 1M · ×2$0.120
CurrencyUSD

Cost calculator

Tokens / month10MM
Input share70%%
Estimated / month $5.75 · With prompt caching $4.41

Estimate based on list price

Token & cost estimator

Input tokens: 20Cost per request: $0.000451

Estimate only — actual token counts depend on the provider's tokenizer.

Performance

p50 TTFT
781 ms
Output speed
68.2 tok/s
p95 TTFT
1.94 s
Error rate
0.22%

Public benchmarks

68.8
AA Coding
Better than 78% of models compared
#25 of 133
53.2
AA Intelligence
Better than 83% of models compared
#21 of 135
Agent Last Exam
25.7
Automation Bench (Public)
31.8
Cybergym
83.3
DeepSWE
62.7
GPQA Diamond
92.8
HLE (no tools)
42.7
HLE (with tools)
60.0
Humanity's Last Exam
41.0
Long-Context Recall
75.3
NL2Repo
61.5
SciCode
49.2
tau_banking
39.6
Terminal Bench 2.1
87.9
terminalbench_v2_1
78.7
Toolathlon Verified
74.1
Source: artificialanalysis.ai, api-docs.deepseek.com

Community buzz

What developers are saying this week

Hacker News2 mentions · 7ddown 7 vs the previous week

How it compares

DeepSeek V4 Pro 0813DeepSeek V4 ProDeepSeek V4 FlashDeepSeek V4 Flash Vision (Exp)
Input $/M$0.44$0.44$0.15$0.15
Output $/M$0.88$0.88$0.29$0.29
Context1.0M1.0M1.0M1.0M
Quality7/108/107/107/10
Compare side-by-sideCompare side-by-sideCompare side-by-sideCompare side-by-side

FAQ

How much does DeepSeek: DeepSeek V4 Pro 0813 cost on OrcaRouter?
DeepSeek: DeepSeek V4 Pro 0813 is priced at $0.44 per 1M input tokens and $0.88 per 1M output tokens via OrcaRouter. Pricing is pulled live from the routing layer.
What is DeepSeek: DeepSeek V4 Pro 0813's context window?
DeepSeek: DeepSeek V4 Pro 0813 supports a context window of 1M tokens. Use long-context features (RAG, summarisation) up to that limit.
How do I call DeepSeek: DeepSeek V4 Pro 0813 via the OpenAI SDK?
Set OpenAI base_url to https://api.orcarouter.ai/v1, supply your OrcaRouter API key, and pass model="deepseek/deepseek-v4-pro-0813" in the chat.completions.create call.
Does OrcaRouter rate-limit DeepSeek: DeepSeek V4 Pro 0813?
Per-model rate limits follow your OrcaRouter plan. Free tiers ship with conservative caps; paid tiers lift them. Check /pricing for current quotas.

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Model card as data

GET /api/public/models/deepseek/deepseek-v4-pro-0813Open
Machine-readable:/llms.txt/llms-full.txt