DeepSeek V4 Pro

SWE-bench leader. Strong math, code, and agentic tool use.

Try in Playground

Input / 1M

$1.32

Cached input / 1M

$0.044

Output / 1M

$3.96

Context

LLMdeepseekFunction callingLoRA tunableServerless

Benchmarks

Published evaluation scores (higher is better). Measured output speed on our fleet, Standard tier.

SWE-bench Verified

74.8%

Real GitHub issues

GPQA Diamond

77.9%

PhD-level science

MMLU Pro

85.2%

Knowledge & reasoning

AIME 2025

94.1%

Competition math

IFEval

90.1%

Instruction following

Output speed

tok/s on runaii

Ways to serve this model

ServerlessPer-token, zero cold starts. From $1.32/M input.Start serverless →Dedicated deploymentReserved GPUs from $40/hr. Full speed control, scale-to-zero, your region.Create deployment →LoRA fine-tuneTrain on your data from $/1M tokens; checkpoints deploy in seconds.Start training →

Live model traffic — last 24h

Requests to runaii/deepseek-v4-pro across the fleet, from the live meter.

Requests

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Tokens

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Spend

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Quickstart

OpenAI SDK (change the base URL) or the Anthropic SDK — both speak runaii.cloud natively.

curl https://api.runaii.cloud/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $RUNAII_API_KEY" \
  -d '{
    "model": "runaii/deepseek-v4-pro",
    "messages": [{"role": "user", "content": "Say hello in Spanish"}]
  }'

live

runaiicloud

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