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DeepSeek V4.1 Flash Pricing

DeepSeek · Released September 13, 2026 as the successor to V4 Flash. Thinking and non-think

TL;DR
Price: $0.30/1M input · $1.20/1M output
Context: 1M · max 393,216 output
Cost advantage: Up to 70% cheaper than official API
Access: OpenAI-compatible · No credit card · Instant API key

Save up to 70% on DeepSeek V4.1 Flash API cost

Same model, same quality — pay less per token than the official API. Pay-as-you-go, no credit card required.

From $0.30/1M
input token price
INPUT
$0.30
/1M tokens
OUTPUT
$1.20
/1M tokens
CONTEXT
1M

Other DeepSeek Models

DeepSeek V4 Pro
$0.55 / $2.19
View Pricing
DeepSeek V4 Flash
$0.14 / $0.28
View Pricing
DeepSeek Chat
$0.27 / $1.10
View Pricing
DeepSeek V3.2
$0.23 / $0.34
View Pricing
DeepSeek R1
$0.70 / $2.50
View Pricing
DeepSeek Coder
$0.14 / $0.28
View Pricing

DeepSeek V4.1 Flash Pricing Context

Pricing position within DeepSeek

DeepSeek V4.1 Flash sits in the middle of DeepSeek's pricing at $0.30/1M input — 18% below the lineup average ($0.14 cheapest, $0.70 most expensive). 3 siblings cost less, 2 cost more. This mid-tier positioning makes it a sensible default when you're unsure which variant to pick.

When DeepSeek V4.1 Flash is worth the cost

DeepSeek V4.1 Flash is deployed where problems need step-by-step reasoning before code output — complex bug fixes, algorithmic implementation, math-heavy analysis, and multi-step refactoring. The internal chain-of-thought adds latency (expect slower responses), so don't route high-volume simple queries here. Use it for the hard 10% of tasks where cheaper models fail.

Cost vs sibling models

What makes DeepSeek V4.1 Flash different from sibling models: compared to DeepSeek V4 Pro ($0.25/1M more expensive, same 1M context); DeepSeek V4 Flash ($0.16/1M cheaper, same 1M context); DeepSeek Chat ($0.03/1M cheaper, 128K vs 1M context (smaller)). Choose DeepSeek V4.1 Flash when step-by-step reasoning matters more than speed.

Real-world cost scenarios

Real-world deployments: autonomous coding agents that fix complex bugs across multi-file codebases, algorithmic problem solving, math-heavy data analysis pipelines, and automated code review for architecture-level decisions. Teams route the simple 90% of coding tasks to cheaper models and reserve DeepSeek V4.1 Flash for the hard 10%.

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