AI Rankings
DeepSeek-V3: Score, Price and Context Window
Data updated
- DeepSeek
- Open weights
- Released Dec 2024
Its score range overlaps with Qwen2.5-Max, the model just above it, so a small gap in rank is not a meaningful difference.
Best for
- Running it yourself: its weights can be downloaded (read the licence terms first).
These lines are worked out from the numbers on this page, not from hands-on testing.
Key facts
- Price per million tokens
- $0.27 in / $1.10 out
- Blended $0.48. Cached input $0.07. List price from DeepSeek, checked 26 Oct 2026.
Features listed by the price list: Tool use, Prompt caching.
How DeepSeek-V3 stacks up
- Overall capability132.3
Better than 43% of the other 269 models
Epoch Capabilities Index: one score that combines many tests.
- Human preference: chat1358
Better than 27% of the other 165 models
How often people pick its answers over another model's on Arena.
- Human preference: coding1387
Better than 26% of the other 165 models
How often people pick its answers to coding questions on Arena.
- Price$0.48 per 1M
Cheaper than 70% of the other 200 priced modelsUpper half
Blended price per million tokens. Lower is better, so the cheapest models sit on the right.
- Context window66K tokens
Larger context window than 16% of the other 198 models
How much text it can read at once. Bigger suits long documents.
Where DeepSeek-V3 ranks
Test results
Aider Polyglot
225 coding exercises in six programming languages. The AI edits the code files and the exercise's tests decide pass or fail.
48.4%
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.
56.5%
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.
15.8%
Place 134 of 174
SimpleBench
Everyday common-sense and trick questions that most people answer correctly but AI models often get wrong.
18.9%
What it costs in everyday terms
- 100 chats
- $0.08
- 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
- $0.48 per 1M
- Three parts input to one part output. Our own calculation for comparing models.
Assumptions: 100 chats of about 1,000 tokens in and 500 tokens back. a 300-page book of about 100,000 tokens, read once with no reply.
Similar models
Questions about DeepSeek-V3
- How much does DeepSeek-V3 cost?
- DeepSeek-V3 costs $0.27 per million input tokens and $1.10 per million output tokens, using the list price from DeepSeek as of 26 Oct 2026. That is about $0.08 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-V3?
- DeepSeek-V3 has a context window of 66K tokens, roughly 49,000 words of text read at once. A single answer can be up to 8K tokens long.
- Is DeepSeek-V3 open source?
- DeepSeek-V3 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-V3 compared with other AI models?
- On the Epoch Capabilities Index, DeepSeek-V3 scores 132.3 (likely range 128.1 to 135.2), which ranks 154 of 270 models we track. On Arena's human-vote text board it is ranked 121 of 166. Scores close together are a tie in practice.
- How does DeepSeek-V3 compare with Llama 4 Maverick?
- Llama 4 Maverick scores higher on 3 of 5 shared quality measures, DeepSeek-V3 on 1. 1 measure is too close to call. Llama 4 Maverick costs about 24% less than DeepSeek-V3 on a blended price of $0.36 against $0.48 per million tokens. See the full comparison for every measure.
- How current are these numbers for DeepSeek-V3?
- The newest data on this page is dated 26 Oct 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: 26 Oct 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