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DeepSeek V4 Flash

  • Instruction Following

DeepSeek V4 Flash is an efficiency-optimized Mixture-of-Experts large language model from DeepSeek, featuring a 1M-token context window and fast inference for high-throughput applications.

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Providers Comparison

Speed

Output tokens per second · Higher is better

246
97
92
91
90
80
60
27
LLM API
SiliconFlow (FP8)
GMI
CoreWeave
Novita
DeepSeek
Parasail (FP8)
DeepInfra (FP4)

End-to-End Response Time

Seconds · Lower is better

65.1
8.1
19.8
20.4
20.9
23.1
24.6
30.6
LLM API
SiliconFlow (FP8)
GMI
CoreWeave
Novita
DeepSeek
Parasail (FP8)
DeepInfra (FP4)

Price

USD per 1M tokens (blended) · Lower is better

65.1
8.1
19.8
20.4
20.9
23.1
24.6
30.6
LLM API
SiliconFlow (FP8)
GMI
CoreWeave
Novita
DeepSeek
Parasail (FP8)
DeepInfra (FP4)

About the model

What is DeepSeek V4 Flash?

DeepSeek V4 Flash is a 284B-parameter Mixture-of-Experts language model (with 13B active parameters) released by DeepSeek as the high-efficiency member of its V4 series. It is mainly used for general chat, reasoning, coding assistance, and agent-style workflows that need low latency and high throughput over long contexts. It is also adopted in production APIs and gateways as a cost-efficient default model for large-context applications. DeepSeek V4 Flash belongs to the DeepSeek V4 family, released alongside the more compute-intensive DeepSeek V4 Pro and succeeding earlier DeepSeek V3-generation models.

Model capabilities

5 Core Capabilities

  • Conversational Chat

    Engages in multi-turn, context-aware dialogue, following instructions, answering questions, and adapting tone for various conversational tasks.

  • Image Understanding

    Interprets images to identify objects, scenes, and visual details, supporting vision-language tasks like description and basic reasoning.

  • Text Translation

    Translates text between multiple languages, preserving meaning and style for general-purpose multilingual communication and content localization.

  • Code and Tools

    Helps write, read, and reason about code and APIs, supporting debugging, explanation, and integration with external tools.

  • Text Extraction

    Extracts and structures textual information from visually presented content such as screenshots or documents for downstream processing.

Use cases

6 Most Valuable Use Cases

  • Customer Support Chatbots
  • Invoice Data Extraction
  • Legal Document Review
  • Regulatory Change Monitoring
  • E-commerce Product Search
  • Code Generation Assistance

Transparent pricing

Cost Comparison

LLM API offers the lowest cost and highest performance for DeepSeek V4 Flash–class models.

Provider Region Latency Throughput Uptime Input ($/1M) Output ($/1M) Context
LLM API BEST Global 80ms 120 tps 99.99% $0.05 $0.10 256K
DeepSeek Global ~120ms ~80 tps ~99.9% ~$0.08 ~$0.16 ~128K
OpenRouter Global ~150ms ~60 tps ~99.5% ~$0.09 ~$0.18 ~128K
Together AI US East ~140ms ~70 tps ~99.9% ~$0.10 ~$0.20 ~128K
Fireworks AI US West ~130ms ~75 tps ~99.9% ~$0.11 ~$0.22 ~200K

Performance benchmarks

Technical Specifications

Metric DeepSeek V4 Flash GPT-4.1 mini Claude 3.5 Haiku
Avg Latency ~120ms ~180ms ~150ms
Context Window 128K 128K 200K
Input Price ($/1M) $0.10 $0.15 $0.15
Output Price ($/1M) $0.20 $0.60 $0.60
Max Output Tokens 4K 4K 4K
Throughput ~60 tps ~40 tps ~45 tps
Uptime 99.9% 99.9% 99.9%

30-day usage via LLM API

38.5B
Prompt tokens processed (last 30 days)
12.4B
Completion tokens generated (last 30 days)
21.7M
API requests served (last 30 days)
99.8%
Average uptime (last 30 days)
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Architecture & Integration

Why Build on LLM.API?

One unified API. Every major model. Built-in reliability, cost control, and observability.

  • Unified AI Routing

    Dynamically route each request to the best model across providers based on latency, price, and quality—no client changes required.

    One endpoint, every model

  • Cost-Aware Orchestration

    Control spend with per-route pricing policies, smart downshifts to cheaper models, and detailed cost breakdowns per project, user, and feature.

    Optimize every token

  • Resilient Fallback Flows

    Define provider-agnostic fallback chains so failed or slow calls automatically retry on alternative models without breaking your application.

    Stay up under failure

  • Deep LLM Observability

    Get full traces, logs, and metrics for every call—latency, tokens, costs, and errors—wired into your existing monitoring stack.

    See every token hop

  • Task-Level Abstractions

    Call high-level tasks like chat, tools, or RAG through one stable interface while LLM.API handles provider quirks and prompt wiring.

    Code to tasks, not models

  • High-Throughput Batch

    Process large workloads with parallel, rate-limit-aware batching, automatic retries, and consolidated results to keep pipelines fast and reliable.

    Scale jobs, not stress

Decision guide

When to Use — When NOT to Use

Use it if...

  • You need a low-cost model for high-volume chatbots and customer support automation.
  • You need fast, lightweight inference for simple classification, routing, or tagging tasks.
  • Your use case involves rapid prototyping where model cost and latency dominate accuracy.
  • You need a compact model to embed into resource-constrained backends or services.
  • Your use case involves short-context prompts with straightforward, non-nuanced generation needs.
  • You need a backup or fallthrough model for handling overflow traffic cheaply.

Avoid if...

  • You need frontier-level reasoning quality for complex multi-step planning or code synthesis.
  • Your workload requires best-in-class performance on safety-critical medical, legal, or financial tasks.
  • You need very long-context understanding across large documents, codebases, or research corpora.
  • Your workload requires strong multilingual performance across many low-resource or niche languages.
  • You need highly reliable adherence to strict policies, compliance constraints, or safety guarantees.
  • Your workload requires top-tier creative writing, stylistic control, and subtle narrative coherence.

FAQ

Frequently Asked Questions

  • What is DeepSeek V4 Flash?

    DeepSeek V4 Flash is a fast, cost-efficient large language model by DeepSeek designed for high-throughput text generation and reasoning workloads.

  • What is the context window of DeepSeek V4 Flash?

    DeepSeek V4 Flash supports a context window of up to 32K tokens for prompts and conversation history.

  • What modalities does DeepSeek V4 Flash support via LLM.API?

    Through LLM.API, DeepSeek V4 Flash currently supports text-in, text-out interactions for chat, reasoning, and tool-augmented workflows.

  • How fast is DeepSeek V4 Flash in terms of latency?

    DeepSeek V4 Flash is optimized for low-latency streaming responses, making it suitable for real-time applications like chatbots and interactive tools.

  • How is DeepSeek V4 Flash priced on LLM.API?

    DeepSeek V4 Flash is billed on a pay-as-you-go basis on LLM.API, with separate per-token rates for input and output tokens.

  • How does DeepSeek V4 Flash compare to heavier DeepSeek models?

    Compared with larger DeepSeek models, DeepSeek V4 Flash trades some peak capability for significantly lower latency and cost-per-token.

  • What are the main strengths of DeepSeek V4 Flash?

    DeepSeek V4 Flash excels at high-volume chat, support automation, code assistance, and lightweight reasoning where low cost and responsiveness are critical.

  • What are known limitations of DeepSeek V4 Flash?

    DeepSeek V4 Flash may underperform frontier models on complex long-horizon reasoning, highly specialized domains, or tasks requiring exhaustive multi-step analysis.

  • How do I call DeepSeek V4 Flash through the LLM.API gateway?

    You can invoke DeepSeek V4 Flash by selecting the DeepSeek provider and specifying the model name "deepseek-v4-flash" in your LLM.API requests.

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