DeepSeek V3
DeepSeek V3 — the most cost-efficient frontier-quality model available.
| Type | Price / 1M tokens | Notes |
|---|---|---|
| Input | $0.27 | Per 1M input tokens |
| Output | $1.10 | Per 1M output tokens |
| Cache read | $0.070 | Cached prefix read-back |
At $0.27/M input and $1.10/M output, DeepSeek V3 delivers near-GPT-4o quality at GPT-5 mini prices.
Best for
- Cost-sensitive production at scale
- Code generation
- Chinese-English multilingual tasks
- Teams evaluating open-weight alternatives
Not ideal for
- Real-time latency-sensitive applications (higher TTFT)
- EU data residency requirements
Real cost scenarios
| Scenario | Est. monthly cost | Breakdown |
|---|---|---|
| 10M requests/month — 1k in, 300 out | $6,000 | Extremely cost-efficient at scale |
Estimates with typical token distributions. Use the Prompt Cost Calculator for your exact workload.
How to cut costs on DeepSeek V3
- DeepSeek V3 is already 5-10× cheaper than equivalent Western models. Self-hosting the open-weight version eliminates API costs entirely for teams with GPU infrastructure.
Calculate your DeepSeek V3 costs
Other DeepSeek models
Compare DeepSeek V3
Frequently Asked Questions
Is DeepSeek V3 as good as GPT-5.4?
On coding benchmarks and general reasoning, DeepSeek V3 scores within 5-10% of GPT-5.4 at roughly 10% of the cost. For pure performance-per-dollar, it is currently the best model available. The main trade-offs are latency (higher TTFT), data privacy considerations, and lack of enterprise SLAs.
Can I self-host DeepSeek V3?
Yes — DeepSeek V3 is fully open-weight (MIT license). At 685B parameters, running it requires substantial GPU infrastructure: approximately 8× A100 80GB GPUs for FP16, or 4× for Q4 quantization. For teams with GPU infrastructure, this eliminates per-token API costs entirely.
Pricing verified 2026-08-19 from DeepSeek official pricing. All prices in USD per 1M tokens. See methodology and price changelog.