DeepSeek-R1 vs DeepSeek-V3
DeepSeek vs DeepSeek · Prices checked November 11, 2026
On blended cost DeepSeek-V3 undercuts DeepSeek-R1 by about 2.1×: $0.4910 per million tokens versus $1.04. A single 100K-input, 10K-output job costs $0.0409 on DeepSeek-V3 against $0.0769 on DeepSeek-R1.
Pricing and capacity
RatesUSD per million tokens. Prices checked November 11, 2026.
| Metric | DeepSeek-R1 | DeepSeek-V3 | Difference |
|---|---|---|---|
| Input / 1M tokens | $0.5500 | $0.3200 | 42% |
| Output / 1M tokens | $2.19 | $0.8900 | 2.5× |
| Blended · 70/30calculated | $1.04 | $0.4910 | 2.1× |
| Blended · 50/50calculated | $1.37 | $0.6050 | 2.3× |
| Blended · 80/20calculated | $0.8780 | $0.4340 | 2.0× |
| Blended · 20/80calculated | $1.86 | $0.7760 | 2.4× |
| Job cost · 100K + 10Kcalculated | $0.0769 | $0.0409 | 47% |
| Job cost · 1M + 100Kcalculated | $0.7690 | $0.4090 | 47% |
| Context window | 64,000 | 64,000 | level |
Input and output rates are as published by each provider. Blended and job-cost rows are calculated comparison metrics, not published prices — how they are derived.
Of the 5 shared benchmarks, DeepSeek-R1 takes 5. The widest gap is on LMArena Elo, where DeepSeek-R1 leads by 40 points. Context is level at 64,000 tokens on each side.
Benchmarks
| Benchmark | DeepSeek-R1 | DeepSeek-V3 | Leader |
|---|---|---|---|
| MMLU | 90.8% | 88.5% | DeepSeek-R1 |
| GPQA Diamond | 71.5% | 59.1% | DeepSeek-R1 |
| HumanEval | 90% | 89% | DeepSeek-R1 |
| SWE-bench Verified | 49.2% | 42% | DeepSeek-R1 |
| LMArena Elo | 1398 Elo | 1358 Elo | DeepSeek-R1 |
Only suites both models report are listed, so a missing score is never shown as a loss. Figures are provider-published or from public leaderboards and are not independently re-run.
What each model is for
DeepSeek-R1
DeepSeek · Reasoning
Open-weights reasoning model with chain-of-thought trained via RL. Comparable to o1 on math benchmarks at a fraction of the price.
- Open-weights reasoning
- Visible chain-of-thought
- Math & code
- Cheap
DeepSeek-V3
DeepSeek · Frontier
Open-weights frontier model that matched GPT-4-class quality at a fraction of the inference cost. Sparked the late-2024 cost reset.
- Frontier quality, open weights
- Aggressive pricing
- Strong code & math
- MoE architecture
Frequently asked questions
Which is cheaper, DeepSeek-R1 or DeepSeek-V3?
On blended cost DeepSeek-V3 undercuts DeepSeek-R1 by about 2.1×: $0.4910 per million tokens versus $1.04. A single 100K-input, 10K-output job costs $0.0409 on DeepSeek-V3 against $0.0769 on DeepSeek-R1. Blended cost weights input at 70% and output at 30%; price your own token split for an exact answer, since the cheaper model on a blended basis is not always cheaper for your workload.
Which performs better, DeepSeek-R1 or DeepSeek-V3?
Of the 5 shared benchmarks, DeepSeek-R1 takes 5. The widest gap is on LMArena Elo, where DeepSeek-R1 leads by 40 points. These are the figures each provider or public leaderboard publishes, not results we re-run, and a benchmark average can hide the specific behaviour your workload depends on.
Which has the larger context window, DeepSeek-R1 or DeepSeek-V3?
Context is level at 64,000 tokens on each side. The context window caps everything in a single request: prompt, retrieved documents, conversation history and the model’s own output all share it.
Can I compare DeepSeek-R1 and DeepSeek-V3 on my own numbers?
Yes. Open both in the side-by-side comparison tool to see every field at once, or use the token calculator to price your actual prompt and monthly request volume against each model. Both are free and need no sign-up.
Price it for your own workload
Related matchups
Terms used on this page
Prices and scores are recomputed on every deploy from the catalogue. Prices checked November 11, 2026.