How much does DeepSeek V4.1 Flash 1017 cost?

DeepSeek V4.1 Flash 1017 costs $0.30 per million input tokens and $1.20 per million output tokens, using the median price across hosting providers as of 9 Nov 2026. That is about $0.09 for 100 chats of about 1,000 tokens in and 500 tokens back. Confirm on the maker's site before you buy, because prices change.

What is the context window of DeepSeek V4.1 Flash 1017?

DeepSeek V4.1 Flash 1017 has a context window of 1M tokens, roughly 786,000 words of text read at once. A single answer can be up to 1M tokens long.

Is DeepSeek V4.1 Flash 1017 open source?

DeepSeek V4.1 Flash 1017 has open weights: its trained parameters can be downloaded. That is not always the same as open source, because licence terms differ, so read the licence before you use it commercially.

How good is DeepSeek V4.1 Flash 1017 compared with other AI models?

On the Epoch Capabilities Index, DeepSeek V4.1 Flash 1017 scores 159.3 (likely range 157.0 to 161.8), which ranks 19 of 274 models we track. Scores close together are a tie in practice.

How does DeepSeek V4.1 Flash 1017 compare with Gemini 3.8 Flash?

Gemini 3.8 Flash scores higher on 3 of 7 shared quality measures, DeepSeek V4.1 Flash 1017 on 2. 2 measures are too close to call. DeepSeek V4.1 Flash 1017 costs about 65% less than Gemini 3.8 Flash on a blended price of $0.52 against $1.50 per million tokens. See the full comparison for every measure.

How current are these numbers for DeepSeek V4.1 Flash 1017?

The newest data on this page is dated 9 Nov 2026. Scores come from Epoch AI and Arena, prices from the open LiteLLM price list.

AI Rankings

DeepSeek V4.1 Flash 1017: Score, Price and Context Window

Where DeepSeek V4.1 Flash 1017 from DeepSeek ranks, what it costs and how much text it can read, in plain numbers with the sources.

Data updated 9 Nov 2026

DeepSeek
Open weights
Released Oct 2026

Its score range overlaps with Claude Opus 4.8, the model just above it, so a small gap in rank is not a meaningful difference.

Best for

Demanding tasks: its overall Epoch score is in the top 10% of models we track.
Very long documents: its context window is 1M tokens, roughly 786,000 words.
Keeping costs low: it is among the cheapest quarter of models in the top half by score.

These lines are worked out from the numbers on this page, not from hands-on testing.

Key facts

Overall score: 159.3; Rank 19 of 274. Likely range 157.0 to 161.8.
Human preference: web pages: 1664; Rank 13 of 89. 13,449 votes, at the "Max" setting.
Price per million tokens: $0.30 in / $1.20 out; Blended $0.52. Cached input $0.006. Median across hosting providers, checked 9 Nov 2026.
Context window: 1M tokens; About 786,000 words at once. One answer up to 1M tokens.
Weights: Open; The weights can be downloaded. Check the licence before commercial use.

Features listed by the price list: Tool use, Reasoning, Prompt caching, Image input, Structured output.

We do not have an Arena human-vote rating for DeepSeek V4.1 Flash 1017 yet. It is shown as "Not measured" rather than guessed.

Try itDeepSeek in our AI tools directoryAI assistant and model platform for reasoning, coding, writing, and conversational work, with separately billed APIs.

How DeepSeek V4.1 Flash 1017 stacks up

Each strip shows every model we track as faint bars. The dot is this model. Better is always to the right, even for price.

DeepSeek V4.1 Flash 1017 compared with all models we trackOverall capability: 159.3. Better than 93% of the other 273 models. Human preference: web pages: 1664. Better than 86% of the other 88 models. Price: $0.52 per 1M. Cheaper than 66% of the other 206 priced models. Context window: 1M tokens. Larger context window than 83% of the other 204 models.

Overall capability159.3
Better than 93% of the other 273 modelsTop 10%
Epoch Capabilities Index: one score that combines many tests.
Human preference: web pages1664
Better than 86% of the other 88 modelsTop 25%
How often people pick the web pages and small apps it builds on Arena.
Price$0.52 per 1M
Cheaper than 66% of the other 206 priced modelsUpper half
Blended price per million tokens. Lower is better, so the cheapest models sit on the right.
Context window1M tokens
Larger context window than 83% of the other 204 modelsTop 25%
How much text it can read at once. Bigger suits long documents.

Compared with the other published models that have each measure. Data updated 9 Nov 2026.

Where DeepSeek V4.1 Flash 1017 ranks

Leaderboards it appears on, best placing first.

See all leaderboards

Test results

Each test checks one kind of skill. Place shows where it stands among the models that took that test.

OTIS Mock AIME
Maths competition problems in the style of the US AIME exam, from the 2024 and 2025 sets. Every answer is a whole number.
99.4%
Place 15 of 178
tied with 2 others
GPQA Diamond
Very hard multiple-choice science questions in biology, physics and chemistry, written by experts and designed so a quick web search does not give the answer.
93.2%
Place 20 of 186
ARC-AGI-2
Visual puzzles where the AI must work out a new rule from a few examples and apply it. They test picking up a new idea quickly, not recalling facts.
78.1%
Place 17 of 91
FrontierMath (Tiers 1-3)
Original, very hard maths problems written by mathematicians. Each has an exact answer and the problems are kept private so models cannot have memorised them. This is the Tiers 1 to 3 set, version 2.
71.2%
Place 27 of 90
SimpleQA Verified
Short factual questions that each have one correct answer. It measures how often a model gets facts right.
42.5%
Place 45 of 85

What it costs in everyday terms

List prices turned into amounts you can picture. Real bills depend on how you use it.

100 chats: $0.09; Cost of 100 chats assumes each chat sends 1,000 tokens (about 750 words) and gets 500 tokens (about 375 words) back.
A 300-page book: $0.03; Cost to read a 300-page book assumes about 100,000 input tokens and no reply. A real book varies with page size and language.
Blended price: $0.52 per 1M; Three parts input to one part output. Our own calculation for comparing models.

Compare DeepSeek V4.1 Flash 1017

Side-by-side pages for the closest rivals.

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Questions about DeepSeek V4.1 Flash 1017

How much does DeepSeek V4.1 Flash 1017 cost?: DeepSeek V4.1 Flash 1017 costs $0.30 per million input tokens and $1.20 per million output tokens, using the median price across hosting providers as of 9 Nov 2026. That is about $0.09 for 100 chats of about 1,000 tokens in and 500 tokens back. Confirm on the maker's site before you buy, because prices change.
What is the context window of DeepSeek V4.1 Flash 1017?: DeepSeek V4.1 Flash 1017 has a context window of 1M tokens, roughly 786,000 words of text read at once. A single answer can be up to 1M tokens long.
Is DeepSeek V4.1 Flash 1017 open source?: DeepSeek V4.1 Flash 1017 has open weights: its trained parameters can be downloaded. That is not always the same as open source, because licence terms differ, so read the licence before you use it commercially.
How good is DeepSeek V4.1 Flash 1017 compared with other AI models?: On the Epoch Capabilities Index, DeepSeek V4.1 Flash 1017 scores 159.3 (likely range 157.0 to 161.8), which ranks 19 of 274 models we track. Scores close together are a tie in practice.
How does DeepSeek V4.1 Flash 1017 compare with Gemini 3.8 Flash?: Gemini 3.8 Flash scores higher on 3 of 7 shared quality measures, DeepSeek V4.1 Flash 1017 on 2. 2 measures are too close to call. DeepSeek V4.1 Flash 1017 costs about 65% less than Gemini 3.8 Flash on a blended price of $0.52 against $1.50 per million tokens. See the full comparison for every measure.
How current are these numbers for DeepSeek V4.1 Flash 1017?: The newest data on this page is dated 9 Nov 2026. Scores come from Epoch AI and Arena, prices from the open LiteLLM price list.

Where this data comes from

Epoch AI: Benchmark data: Epoch AI, 'Capabilities & benchmarking', epoch.ai/benchmarks (CC BY 4.0). We match models across sources, rank them and show them in charts. Scores are not changed. Epoch AI does not endorse this site.
Arena (formerly LMArena): Human-preference ratings: Arena (arena.ai) leaderboard dataset, CC BY 4.0. We keep the latest published ratings, match them to models from other sources and rank them. Ratings are not changed. Arena does not endorse this site.
LiteLLM model price list: Prices and context windows: LiteLLM model price list (github.com/BerriAI/litellm, MIT licence). We use the model maker's own price entry when there is one. Prices change often, so always confirm on the maker's site before you buy.

Newest data on this page: 9 Nov 2026. Prices are list prices and change often, so confirm on the maker's site before you buy. Sponsors never change a score or an order. How we calculate this · Report a mistake