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.
API Pricing
Cheapest on OpenRouter — 99% below avg| Provider | Input / 1M | Output / 1M | Cached / 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 →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
About DeepSeek V4.1 Flash
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.