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Open SourceDeepSeek

DeepSeek V4.1 Flash

DeepSeek V4.1 Flash is a chat model from DeepSeek positioned as a speed-oriented variant in the company's V4.1 line, measured at roughly 267 output tokens per second.

License Open Source
Input from
$0.0030 / 1M tokens
across 15 providers

API Pricing

Cheapest on OpenRouter — 99% below avg
ProviderInput / 1MOutput / 1MCached / 1M
$0.0030$2.40$0.0030
$0.112$0.336$0.0034
$0.150$0.600-
$0.180$0.720$0.0036
$0.200$0.600$0.0060
$0.294$1.19$0.147
$0.300$1.20$0.0070
$0.300$1.20-
$0.300$1.20$0.0060
$0.300$1.20$0.300
$0.300$1.20-
$0.300$1.20-
$0.300$1.20$0.0060
$0.300$1.10-
$0.300$1.20$0.0060
$0.500$1.50$0.130

Prices updated daily. Last check: Oct 6, 2026

DeepSeek V4.1 Flash pricing by provider

Input, output, and batch rates, plus alternatives, for one provider at a time.

Performance & Benchmarks

Source: Artificial Analysis →
Intelligence
39.5 / 100
Output Speed
212 t/s
Latency (TTFT)
838ms

Reasoning & Knowledge

  • Humanity's Last Exam39.2%

Coding

  • SciCode51.9%

Instruction & Long Context

  • Long-Context Reasoning84.0%

Benchmarks measured Oct 2026. Scores are independent evaluations, not vendor-reported.

Model Details

General

Creator
DeepSeek
Modalities
Text

Capabilities

Tool Calling
No
Open Source
Yes

Strengths & Limitations

Strengths

  • Measured output speed of roughly 267 tokens per second, which supports responsive streaming in interactive chat interfaces
  • Time to first token of about 896 ms keeps perceived latency under a second for typical prompts
  • Flash tier within the DeepSeek V4.1 line is positioned for cost-sensitive, high-volume text workloads
  • DeepSeek models are typically available from several inference providers, allowing price and region comparison
  • Throughput profile suits batch jobs such as summarization, classification, and data extraction at scale
  • Independent third-party performance measurement (Artificial Analysis) is available rather than vendor-reported numbers alone

Limitations

  • We do not have a confirmed context window length for this entry — verify with your provider before relying on long inputs
  • Modality support (image or audio input) is not tracked in our data for this model
  • Flash-tier models are generally tuned for speed over maximum reasoning depth, so complex multi-step problems may favor a larger sibling
  • No standardized quality benchmark scores (MMLU, coding, math) are recorded for this model in our database
  • Serving quality, quantization, and rate limits can differ substantially between the providers hosting DeepSeek models

Key Features

•Text chat completion API interface
•Speed-oriented Flash tier within the DeepSeek V4.1 family
•Measured ~267 output tokens/second generation throughput
•Measured ~896 ms time to first token
•Streaming token output suitable for interactive UIs
•Available through multiple third-party inference providers
•Benchmarked by Artificial Analysis for independent latency and throughput figures

About DeepSeek V4.1 Flash

DeepSeek V4.1 Flash is a text chat model released by DeepSeek, the Chinese AI lab whose DeepSeek-named model series has been widely served through third-party inference providers. The "Flash" designation marks it as the latency- and throughput-oriented member of the V4.1 generation, intended for workloads where response speed and per-request cost matter more than squeezing out the last few points of benchmark accuracy. Independent measurements collected by Artificial Analysis put DeepSeek V4.1 Flash at approximately 267 output tokens per second with a time to first token of about 896 milliseconds. Those two numbers describe the model's practical behavior fairly well: generation is fast once it starts, while initial latency sits in the sub-second range typical of hosted API models rather than the tens of milliseconds achievable on specialized inference hardware. We do not currently track a confirmed context window, modality list, or tool-calling specification for this entry, so check your provider's model card for those details before building against them. In practice, a Flash-tier model like this is chosen for high-request-volume applications — chat front ends, summarization pipelines, retrieval-augmented answering, and bulk text transformation — where sustained token throughput determines how many concurrent users a deployment can serve. Compared with larger siblings in the same family, the trade-off is the usual one: faster and cheaper per token, with less headroom on long multi-step reasoning. Because DeepSeek models are commonly offered by multiple hosts, serving characteristics and pricing for this model vary meaningfully between providers; see the pricing table on this page for current options.

Common Use Cases

DeepSeek V4.1 Flash fits workloads defined by request volume rather than problem difficulty: customer-facing chat assistants where streaming responsiveness shapes the user experience, document and transcript summarization pipelines, content rewriting and translation batches, retrieval-augmented question answering over indexed corpora, and routing or classification steps inside a larger agent system. Its measured throughput of roughly 267 tokens per second means long generations complete in a few seconds, which matters for drafting and summarization jobs, while sub-second time to first token keeps interactive sessions feeling immediate. For work requiring extended chain-of-thought reasoning, competition-level mathematics, or long autonomous coding sessions, a larger reasoning-oriented model — including heavier members of the DeepSeek lineup — is usually the better match, with Flash reserved for the high-frequency, lower-complexity calls in the same application.

Frequently Asked Questions

How much does DeepSeek V4.1 Flash cost?

Pricing depends on which provider hosts the model and on the pricing type — input tokens, output tokens, cached input, and any batch or committed-throughput discounts are billed separately. Rates also change as providers compete. Check the pricing table on this page for the current figures across the providers we track.

What is DeepSeek V4.1 Flash best used for?

High-volume text workloads where speed and per-request cost dominate: chat assistants, summarization, translation, classification, extraction, and retrieval-augmented answering. Its measured ~267 tokens/second output rate and ~896 ms time to first token make it a reasonable fit for interactive and batch pipelines alike.

How does the Flash variant differ from other DeepSeek V4.1 models?

The Flash designation indicates the speed- and cost-oriented tier of the V4.1 generation. Non-Flash siblings are generally positioned for harder reasoning and longer-horizon tasks, while Flash targets fast responses across many requests. If your workload mixes both, a common pattern is routing simple calls to Flash and escalating difficult ones to a larger model.

What context window does DeepSeek V4.1 Flash support?

We do not have a confirmed context window recorded for this model. Providers sometimes serve the same DeepSeek model with different maximum context settings, so consult the model card of the specific provider you plan to use.

Is DeepSeek V4.1 Flash fast enough for real-time chat?

Independent measurement puts time to first token at roughly 896 ms and sustained output at about 267 tokens per second. That is fast enough for streaming chat interfaces, where the first token arrives in under a second and text renders faster than most people read, though it is slower to start than latency-specialized inference stacks.