DeepSeek V3 vs o1
2026 - Pricing, benchmarks, and use case comparison
Quick take
- •DeepSeek V3 is 98% cheaper on input tokens - better for high-volume workloads.
- •o1 has a 200K context window - 2x larger than DeepSeek V3's 128K. Better for long documents and large codebases.
- •DeepSeek V3 is open-source: fine-tune it, self-host it, or use any inference provider. o1 is closed-source.
Specs comparison
| DeepSeek V3 | o1 | |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Type | Open source | Closed source |
| Context window | 128K | ✓200K |
| Input / 1M tokens | ✓$0.27 | $15.00 |
| Output / 1M tokens | $1.10 | $60.00 |
| Release date | 2024-12 | 2024-09 |
Benchmarks
| Benchmark | DeepSeek V3 | o1 |
|---|---|---|
| HumanEval | 90.2% | 92.4% |
| MMLU | 88.5% | - |
| Aider Polyglot | 55.0% | - |
| GPQA Diamond | - | 78.3% |
| SWE-bench Verified | - | 48.9% |
Scores sourced from official provider release posts.
Strengths
DeepSeek V3
- ✓Near-GPT-4o quality at a fraction of the price
- ✓Open weights - self-host or fine-tune freely
- ✓Efficient MoE architecture reduces inference cost
- ✓Strong coding (Aider polyglot, HumanEval)
- ✓Good instruction following and structured output
o1
- ✓Best-in-class math and physics
- ✓Strong competitive coding (Codeforces, HumanEval)
- ✓Scientific reasoning (GPQA top performer)
- ✓Multi-step logic and planning
- ✓200K context for long technical documents
Which should you choose?
Choose DeepSeek V3 if you need...
- →Cost-sensitive high-volume inference
- →Self-hosted deployments
- →Fine-tuning for specialized domains
- →Coding assistants
Choose o1 if you need...
- →Math and science problems
- →Competitive programming
- →Complex multi-step reasoning
- →Research assistance