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Long Story Video Skill
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deepseek 4.1 flash 1017
DeepSeek 4.1 Flash 1017 builds full games and 3D scenes from a single written wish — faster replies, leaner output and lower cost per run. Try it free.
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Built for Whole Projects, Not One-Off Edits
Instead of squeezing quality and price against each other, this release lifts both at once: benchmark numbers rise, tasks wrap up in less time and replies arrive shorter. It is aimed at end-to-end builds rather than quick single-shot tweaks.
- Better Scores at a Lower PriceQuality and cost move in the same direction here. Benchmark results improve while each job finishes sooner and returns tighter output, so teams no longer choose between speed and spend.
- From Wish to Working BuildReinforcement learning with self-feedback keeps the model on track across an entire project — a racing game, a palace model, a 3D timeline of dynasties — rather than producing isolated fragments.
- Weights You Can Host YourselfThe release is published openly on Hugging Face and ModelScope, giving teams the option to download the weights and run the model on their own infrastructure.
Three Routes Into the Flash Release
You can reach the model through the hosted surfaces, by upgrading DeepSeek Harness, or through the Search and Fetch endpoints.
Search, Fetch and Vision in One Model
Live web access, image understanding and pay-per-result pricing — the parts that let agents pull current pages and read screenshots.
Search API, Built In-House
A query comes back as structured page results from DeepSeek's own crawler and engine, which already handles hundreds of millions of calls every day worldwide.
Fetch That Returns Markdown
Fetch grabs a single page and hands it back as clean Markdown, so RAG pipelines and agents get readable live text without extra parsing work.
Image Understanding
The deepseek-flash model reads pictures alongside text — captioning a photo, lifting wording from a screenshot or interpreting a chart — across JPEG, PNG, GIF and WebP.
Three Ways to Send Images
Pass images as base64 data URLs, public http(s) links or Files API file_ids; inline payloads share a 48 MiB body cap while uploaded files can go up to 64 MiB.
Pay Only for Results
Each 1,000 calls costs $0.75, and billing applies only when a request returns something — failed calls, empty searches and timeouts are never charged.
Tuned for Popular Agent Tools
DeepSeek Harness, Tencent CodeBuddy and WorkBuddy are already optimized for the model, and server-side Search and Fetch stay free for API users until billing begins.
DeepSeek 4.1 Flash 1017: Common Questions
Answers on the release itself, its Search and Fetch APIs, image inputs and where to find the open weights.
What exactly is DeepSeek-V4.1-Flash-1017?
It is the newest Flash model from DeepSeek. Benchmark scores are higher, tasks finish in less time and replies come back shorter — and it is already handling traffic across the website, the app and the API.
How is it different from the earlier version?
Quality and cost both improve rather than one being traded for the other: scores climb while jobs complete faster and output gets more compact. That combination is what the Pareto framing refers to.
Which tools already support it?
DeepSeek Harness v0.2.1-rc.1 and later, Tencent CodeBuddy, WorkBuddy and other optimized integrations are ready to use with the model today.
Do Search and Fetch cost anything?
Server-side Search and Fetch calls inside Harness, Claude Code and Codex stay free for DeepSeek API users for now. Billing is scheduled to begin on Oct 31, 2026, at 16:00 UTC.
Where do I get the open-source weights?
They are published on Hugging Face and ModelScope under the DeepSeek-V4.1-Flash-1017 repository names, ready to download and self-host.
Which image formats can the vision model read?
JPEG, PNG, GIF and WebP all work. The model inspects the bytes directly, so a wrong file extension or a mismatched declared MIME type will not throw it off.
Start Building With the Flash Release
Head to the website, the app or the API to build with DeepSeek 4.1 Flash 1017, upgrade DeepSeek Harness to v0.2.1-rc.1 or newer, or pull the open weights from Hugging Face and ModelScope.