DeepSeek: DeepSeek V4.1 Flash
DeepSeek • LLM#39 of 616 in intelligence
DeepSeek: DeepSeek V4.1 Flash by DeepSeek
Specifications
Context Window
1.0M tokens
Input Price/1M
$0.30
#380 of 744
Output Price/1M
$1.20
Parameters
—
Speed
199 tok/s
#41 of 602
Latency (TTFT)
1.1s
Max Output
384K tokens
Cost per Task
75.2
AA Score / US$ · higher = better
Benchmarks
DeepSeek: DeepSeek V4.1 Flash results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 39.5 | 100.0 | Artificial Analysis official API |
Information
- Release date
- September 10, 2026
- Tool Calling
- ❌ Not supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: DeepSeek: DeepSeek V4.1 Flash
What is DeepSeek: DeepSeek V4.1 Flash?
DeepSeek: DeepSeek V4.1 Flash is an AI model developed by DeepSeek, classified as a large language model (LLM). It is a multimodal model, capable of processing text, images, and potentially other media types. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 1.0M tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
DeepSeek: DeepSeek V4.1 Flash is usage-based, priced at $0.3/1M input tokens and $1.2/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
DeepSeek: DeepSeek V4.1 Flash was evaluated on 1 different benchmarks, covering categories like overall. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
DeepSeek: DeepSeek V4.1 Flash is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), multimodal processing combining text and images, high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, DeepSeek: DeepSeek V4.1 Flash competes directly with similarly capable models. DeepSeek competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is DeepSeek: DeepSeek V4.1 Flash?
DeepSeek: DeepSeek V4.1 Flash is an AI model developed by DeepSeek. It is a language model (LLM), with multimodal support (text, image and more), open source.
How much does DeepSeek: DeepSeek V4.1 Flash cost?
DeepSeek: DeepSeek V4.1 Flash costs $0.3/1M input tokens and $1.2/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does DeepSeek: DeepSeek V4.1 Flash compare with other models?
In available benchmarks, DeepSeek: DeepSeek V4.1 Flash scored: AA Intelligence Index: 39.5/100. See the full table above for a detailed comparison.
Is DeepSeek: DeepSeek V4.1 Flash open source?
Yes, DeepSeek: DeepSeek V4.1 Flash is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
What is DeepSeek: DeepSeek V4.1 Flash best for?
DeepSeek: DeepSeek V4.1 Flash excels at general-purpose language tasks. With its large context window, it handles long documents, codebases, and extended conversations.
Last updated: September 12, 2026 • View methodology →