DeepSeek-V4.1-Flash
DeepSeekLarge Language ModelOpen SourceDeepSeek's current API workhorse, released September 2026. A 552B-parameter MoE with a novel Causal Encoder-Decoder architecture (8B active params for input, 16B for output), native vision, thinking and non-thinking modes, 1M context, and extreme cost-efficiency with off-peak discounts.
Abilities
Use Cases
Available in Tools
Availability
How to Use
Pros
- Extreme cost-efficiency — $0.30/$1.20 per MTok peak, halved off-peak, and cache hits from $0.003
- 1M token context with 384K max output — the largest output window on the market
- Native vision plus switchable thinking/non-thinking modes in one model
- Open weights under MIT — self-hosting and research use allowed
- Efficient Causal Encoder-Decoder design — KV cache roughly a quarter of the previous V4-Flash
Cons
- Peak/off-peak pricing complicates cost forecasting for latency-bound production traffic
- Below Western frontier flagships on the hardest reasoning benchmarks
- China-hosted API raises data-residency concerns for some enterprises (self-hosting avoids this)
What to Use It For
Perfect For
Among the cheapest capable models per token, with off-peak batches at half price
384K max output dwarfs the 64-128K caps of competing models
Good For
MIT weights with an efficient architecture make large-scale self-hosting viable
Native vision with 1M context handles long, image-heavy documents
Not Recommended
Frontier flagships remain stronger on the most demanding problems
Try instead: Claude Opus 5, GPT-6 Astra
Do Not Use For
Understands images but cannot create them
Try instead: Seedream 4, FLUX.2 Pro