DeepSeek V3 vs o1
Pricing, benchmarks, and use case comparison
Quick take
- •DeepSeek V3 is meaningfully stronger at cost efficiency (92 vs 35 on our capability index).
- •o1 is meaningfully stronger at multimodal (60 vs 10).
- •DeepSeek V3 is open-weights (free to self-host); o1 is paid API only.
- •DeepSeek V3 has a 128K tokens context window vs 200,000 tokens (100,000 max output) - better for whole-repo or long-document work.
Specs comparison
| DeepSeek V3 | o1 | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Type | Open source | Closed source |
| Context window | ✓128K tokens | 200,000 tokens (100,000 max output) |
| Input / 1M tokens | ✓Free (self-host) | $15.00 |
| Output / 1M tokens | Free (self-host) | $60.00 |
| Release date | 2024-12 | 2024-12 |
Benchmarks
| Benchmark | DeepSeek V3 | o1 |
|---|---|---|
| Pre-training scale | ~15T tokens | - |
| AIME 2024 | - | 74% |
| GPQA Diamond | - | 77.3% |
| Codeforces | - | ~89th percentile |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose DeepSeek V3 if...
- →You want a proven, stable open model with broad ecosystem support
- →You need to self-host or fine-tune without licensing friction
- →Cost is critical and you don't need V4's 1M context or top scores
- →You want reproducible open-weight behavior pinned to a known version
Choose o1 if...
- →Hard, multi-step math, science, and logic problems that reward deliberate reasoning
- →Competitive programming and algorithmic problem solving
- →Existing o1-based pipelines already validated for reasoning tasks