Sulat.com
AI models
$10 off the fastest DeepSeek V4.1 Flash, Kimi K3 and GLM 5.3 from Synthetic
DeepSeek logo

Model details

DeepSeek V4.1 Flash

DeepSeek V4.1 Flash is described as a generational replacement for the prior V4 Flash line rather than a routine refresh, with the older V4 Flash and experimental V4 Flash Vision variants retired while their names temporarily forward to the new model. According to DeepSeek's own framing reported at release, V4.1 Flash surpasses the former V4 Pro on performance, cost, speed, and end-to-end serving time, prompting DeepSeek to route all requests to deepseek-v4-pro to V4.1 Flash and bill them at Flash rates until a dedicated V4.1 Pro arrives. That backdrop positions V4.1 Flash as the de facto default high-throughput, low-cost option in the family, designed to absorb the heaviest traffic from now until a larger sibling reappears.

In practical terms, the model keeps the multimodal text-and-image input surface and open-weight posture that defined its family, while compressing the economics enough to matter for long-context and agentic workloads. The reported gap between the old Pro and the new Flash is significant: cache-miss input cost falls by roughly 77 percent and output cost by roughly 70 percent once V4 Pro traffic moves onto V4.1 Flash, with comparable advantages on agent-style evaluations offset by weaker knowledge recall relative to the larger flagship. That profile makes V4.1 Flash a sensible pick for production pipelines where throughput, tool use, and cost dominate over encyclopedic recall, and a less ideal choice when the task depends on breadth of memorized knowledge.

DeepSeekdeepseek-flashdeepseek-flash

Quick Info

Powered by
Provider
DeepSeek
Model key
deepseek-flash
Release date
Sep 10, 2026
Last updated
Sep 10, 2026
Knowledge cutoff
2025-05
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.15
Output token cost
$0.60

Limits

Output tokens
393,216 tokens
Context window
1,000,000 tokens

Transparent token rates

Compare DeepSeek V4.1 Flash pricing

Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

Browse this family

Latest news about DeepSeek V4.1 Flash

DeepSeek

Official sourceAnnouncement

The DeepSeek API documentation news page confirms DeepSeek-V4.1-Flash is now live on the DeepSeek API under the model id "deepseek-flash" with native multimodal (text and image) support. It restates the 552B-parameter MoE backbone, the asymmetric Causal Encoder–Decoder design with 8B active parameters for input and 16B The page documents the model lifecycle changes developers need to act on: deepseek-v4-flash and deepseek-v4-flash-vision-exp are retired and temporarily route to V4.1-Flash for compatibility, and starting at 04:00 UTC on September 14, 2026 all deepseek-v4-pro requests will route to V4.1-Flash at V4.1-Flash rates until

DeepSeek

Official sourceAnnouncement

DeepSeek officially announced DeepSeek-V4.1-Flash on September 10, 2026, describing it as the smallest model in a new architecture family with native visual understanding. The model uses a 552B-parameter Mixture-of-Experts Causal Encoder–Decoder architecture with 8B active parameters for input and 16B for output. DeepS Compared with the previous generation, V4.1-Flash's KV cache needs just 1/4 the HBM and 1/8 the SSD storage, which DeepSeek highlights as significant savings for cache-hit-heavy agent workloads. V4-Flash and V4-Flash-Vision-Exp are retired, with legacy model names temporarily routing to V4.1-Flash; all `deepseek-v4-pro

DeepSeek

CoverageBenchmark

Eesel's write-up describes DeepSeek V4.1 Flash as a new design rather than an incremental tweak, quoting DeepSeek's framing as "the smallest model in our new architecture family, with native visual understanding." It documents the consolidation of three prior models into V4.1 Flash: deepseek-v4-flash and deepseek-v4-fl The piece covers the architectural rationale for why a bigger model is cheaper and faster, and the practical implications for production teams pinning DeepSeek model IDs, treating the silent substitution risk as a real design constraint. It positions V4.1 Flash against V4 Pro and discusses when pointing the new model a

DeepSeek

CoverageBenchmark

VentureBeat's coverage of the DeepSeek-V4.1-Flash launch details the API pricing structure: during off-peak hours the model is priced at $0.003 per million input tokens on a cache hit, $0.15 per million on a cache miss, and $0.60 per million output tokens, with peak rates double those figures. It defines DeepSeek's pea The piece restates the core model facts: a 552-billion-parameter mixture-of-experts backbone, native vision, a 1-million-token context window, MIT-licensed open weights on Hugging Face, and architecture choices aimed at lowering the cost of repeatedly reading large contexts. It also confirms DeepSeek's plan to retire V

DeepSeek

CoverageBenchmark

Coursiv's breakdown frames V4.1 Flash as a generational replacement rather than a point update, presenting a comparison table against V4 Flash citing DeepSeek's official model card: backbone parameters grew from 284B to 552B while active parameters fell from 13B to 8B for input and 16B for output, the architecture move The article highlights Terminal-Bench 4.0 jumping from 7.0 to 31.2 and Terminal-Bench 2.1 from 82.7 to 90.6, and quantifies the cost shift after the V4 Pro redirect as roughly a 77% drop in cache-miss input cost and a 70% drop in output cost. It situates V4.1 Flash relative to DeepSeek's prior V4 Flash write-up and not

Videos about DeepSeek V4.1 Flash

More models around DeepSeek V4.1 Flash