- Instruction Following
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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.
Providers Comparison
Speed
Output tokens per second · Higher is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
End-to-End Response Time
Seconds · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
DeepInfra (FP4)
Price
USD per 1M tokens (blended) · Lower is better
L
LLM API
S
SiliconFlow (FP8)
G
GMI
C
CoreWeave
N
Novita
D
DeepSeek
P
Parasail (FP8)
D
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)
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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