DeepSeek V4 Flash

API Model ID:deepseek-v4-flash

Blazing fast Mixture-of-Experts engine optimized for latency-critical microservices.

#Ultra Fast#Sub-Cent#Microservices#JSON#Low Latency

Deploy with Gruvo All Models

Context Window128K tokens128,000 tokens

Max Output16K tokens16,000 tokens

Input Price$0.080per 1M input tokens

Output Price$0.20per 1M output tokens

Latency / Speed~70ms240 tokens/sec

Overview & Architecture

DeepSeek V4 Flash is tuned for instantaneous responses and high concurrency. With lightweight token routing and low memory overhead, V4 Flash is the preferred choice for microservices requiring prompt categorization, moderation, and low-latency JSON transformation.

ArchitectureCompact MoE with Low-Rank Latent Projections

Knowledge IndexCurrent (Continuously Indexed)

Benchmark Highlights

MMLU84.2%

Standard knowledge evaluation

HumanEval82.5%

Function synthesis speed & correctness

MT-Bench8.65

Conversational speed & coherence

Supported Capabilities

Function Calling / Tools

Supported

Vision & Image Inputs

Audio & Voice Inputs

Structured JSON Mode

Supported

System Prompts

Supported

Streaming Completions

Supported

Prompt Caching

Supported

Engineering Strengths

Extremely economical: $0.08 per 1M input tokens
Sub-70ms time-to-first-token with up to 240 tokens/sec output
Solid adherence to JSON mode and single-step function calls
Minimal infrastructure footprint and reliable uptime

Recommended Production Workloads

Real-time content moderation, classification, and toxicity filtering
Fast API gateway semantic caching verification and request rewrites
Embedding reranking verification and fast relevance scoring

Execute via Gruvo

Unified Endpoint

Connect through Gruvo with OpenAI-compatible client libraries. Gruvo translates requests, manages provider streaming, and applies caching automatically.

import OpenAI from "openai";

// Configure client with Gruvo's unified AI gateway
const gruvo = new OpenAI({
  baseURL: "https://api.gruvo.ai/v1",
  apiKey: process.env.GRUVO_API_KEY,
  defaultHeaders: {
    "X-Gruvo-Provider": "deepseek",
  },
});

const completion = await gruvo.chat.completions.create({
  model: "deepseek-v4-flash",
  messages: [
    { role: "system", content: "You are a production reasoning assistant." },
    { role: "user", content: "Analyze the architecture of our service." },
  ],
  temperature: 0.2,
});

console.log(completion.choices[0].message.content);