DeepSeek V4 Flash
Overview
DeepSeek-V4-Flash is DeepSeek's high-efficiency open-source language model, released alongside V4-Pro on April 24, 2026 under the MIT License. With 284 billion total parameters and only 13 billion active parameters, it delivers performance within striking distance of V4-Pro at roughly 3.1x lower cost, making it one of the most cost-effective models available.
Key Features
- Ultra-Efficient Architecture: 284B total parameters with just 13B activated per forward pass, resulting in a compact 160GB download that runs on significantly less hardware than frontier models while maintaining strong performance.
- 1M-Token Context Window: Shares the same 1-million-token context and 384K max output as V4-Pro, powered by the same CSA/HCA hybrid attention mechanism for efficient long-context inference.
- Near-Pro Performance at Lower Cost: Scores 79.0% on SWE-bench Verified, only 1.6 percentage points behind V4-Pro's 80.6%, while costing 0.28/0.56 Credits per input/output token.
- Flash-Max Reasoning Mode: When given a larger thinking budget (384K+ context), V4-Flash-Max achieves comparable reasoning performance to V4-Pro, closing the gap on complex tasks.
Best Use Cases
- High-Volume API Workloads: At 0.28 Credits per input token, Flash is ideal for applications that process large volumes of text where cost per query matters more than marginal accuracy gains.
- Self-Hosted Deployments: The 160GB model size and 13B active parameters make it feasible for on-premise or single-node GPU deployments, unlike larger frontier models.
- Agentic Tool-Use Pipelines: Strong tool-calling and coding capabilities paired with low latency make it well-suited for multi-step agent workflows where many LLM calls are chained together.
Capabilities and Limitations
| Capability | Description |
|---|
| Reasoning | Competitive with Claude Sonnet 4.6 level intelligence (47 on Artificial Analysis Index) |
| Coding | 79.0% SWE-bench Verified; 64.4 average across coding benchmarks |
| Multimodal | Text-only; no image, audio, or video support |
| Response Speed | Optimized for high throughput with 13B active parameters and efficient attention |
| Context Window | 1,000,000 tokens |
| Max Output | 384,000 tokens |
| Tool Use | Function calling support; strong agentic task performance |
| Multilingual | Broad multilingual support; strongest in English and Chinese |
Known Limitations
- Text-only, with no multimodal capabilities.
- Falls behind V4-Pro and frontier closed-source models on pure knowledge tasks and the most complex agentic workflows due to smaller parameter scale.
- May require Flash-Max mode (larger thinking budget) to match Pro-level reasoning, increasing latency and cost for complex tasks.
Credits Usage
| Model | Input (Credits/Token) | Cache Write (Credits/Token) | Cache Read (Credits/Token) | Output (Credits/Token) | Web Search (Credits/Use) | Billing Notes |
|---|
| DeepSeek V4 Flash | 0.28 | 0.28 | 0.0056 | 0.56 | - | - |