DeepSeek-R1 vs DeepSeek-V3 0324
Comparing DeepSeek-R1 and DeepSeek-V3 0324 across benchmarks, pricing, and capabilities.
DeepSeek · DeepSeek · Updated for 2026
Which is better?
DeepSeek-R1 and DeepSeek-V3 0324 trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-V3 0324 is roughly 2.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3 0324 also accepts a larger context window (163,840 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-R1
- you want predictable pricing at $0.55/M input and $2.19/M output
Choose DeepSeek-V3 0324
- cost matters — it's about 2.4x cheaper per token
- you process long inputs — it offers a 163,840 token context window
- you want the most recent training data — it shipped Mar 2025
At a glance
The differences that matter most.
Individual benchmarks
0 reported for DeepSeek-R1 · 5 for DeepSeek-V3 0324
DeepSeek-R1 and DeepSeek-V3 0324don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 2.3x more expensive than DeepSeek-V3 0324 ($0.24/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 2.4x more expensive than DeepSeek-V3 0324 ($0.90/1M tokens).
In conclusion, DeepSeek-R1 is more expensive than DeepSeek-V3 0324.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3 0324 has 0.0B more parameters than DeepSeek-R1, making it 0.0% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3 0324 accepts 163,840 input tokens compared to DeepSeek-R1's 131,072 tokens. DeepSeek-V3 0324 can generate longer responses up to 163,840 tokens, while DeepSeek-R1 is limited to 131,072 tokens.
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while DeepSeek-V3 0324 uses MIT + Model License (Commercial use allowed).
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
MIT + Model License (Commercial use allowed)
Open weights
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while DeepSeek-V3 0324 was released on 2025-03-25.
DeepSeek-V3 0324 is 2 months newer than DeepSeek-R1.
Jan 20, 2025
1.6 years ago
Mar 25, 2025
1.5 years ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. DeepSeek-V3 0324 is available from DeepInfra, Novita.
DeepSeek-R1
DeepSeek-V3 0324
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1 and DeepSeek-V3 0324 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1 vs DeepSeek-V3 0324.