Pricing updated 2026-08-19: AIWave V4 Flash is $0.638 input, $1.914 output, and $0.0203 cache hit; V4 Pro is $1.914 input, $5.742 output, and $0.0638 cache hit per 1M tokens.
With multiple DeepSeek model variants available — V3, V3.1, V3.2, V4 Pro, V4 Flash, and R1 — choosing the right model for your project can be confusing. Here is what actually differs between them: architecture, price per million tokens, measured performance and the workloads each one suits.
| Model | Generation | Context | Best For | Status |
|---|---|---|---|---|
| DeepSeek V4 Pro | 4th gen (latest) | 128K | Best all-round performance | ✅ Recommended |
| DeepSeek V4 Flash | 4th gen | 128K | Fast, affordable inference | ✅ Recommended |
| DeepSeek R1 (Reasoner) | 4th gen | 128K | Chain-of-thought reasoning | ✅ Recommended |
| DeepSeek V3 | 3rd gen | 64K | Legacy applications | ⚠️ Being phased out |
| DeepSeek V3.1 | 3rd gen (refined) | 64K | Incremental V3 update | ⚠️ Legacy |
| DeepSeek V3.2 | 3rd gen (refined) | 64K | Minor V3 improvement | ⚠️ Legacy |
| ERNIE 4.0 (Baidu) | $0.55 | $0.55 | 128K |
| Model | Input (per 1M tokens) | Output (per 1M tokens) | Cost vs V4 Pro |
|---|---|---|---|
| DeepSeek V4 Pro | $1.914 | $5.742 | — (baseline) |
| DeepSeek V4 Flash | $0.638 | $1.914 | Lower AIWave list rate |
| DeepSeek R1 | $0.55 | $1.10 | 3.9x more |
| DeepSeek V3 | $0.27 | $1.10 | 1.9x more |
| GPT-4o (for reference) | $2.50 | $10.00 | 17.9x more |
| ERNIE 4.0 (Baidu) | $0.55 | $0.55 | 128K |
💡 Key finding: DeepSeek V4 Pro is nearly half the price of DeepSeek V3 ($1.914 vs $5.742/1M input) while delivering significantly better performance. There is no cost advantage to staying on V3.
DeepSeek V3 uses a Mixture-of-Experts (MoE) architecture with 671B total parameters and 37B activated per token. It features a 64K context window, Multi-head Latent Attention (MLA), and was trained on 14.8T tokens. V3.1 and V3.2 are incremental refinements with minor alignment and safety improvements but share the same core architecture.
DeepSeek V4 represents a major architectural leap. Built on an improved MoE design with enhanced attention mechanisms, V4 Pro achieves significant gains in reasoning, coding, and multilingual performance while reducing inference costs. The 128K context window doubles V3's capacity.
| Benchmark | DeepSeek V4 Pro | DeepSeek V3 | Improvement |
|---|---|---|---|
| MMLU (knowledge) | 90.2% | 86.8% | +3.4% |
| HumanEval (coding) | 92.5% | 85.4% | +7.1% |
| MATH (reasoning) | 88.7% | 79.2% | +9.5% |
| Context Length | 128K | 64K | +100% |
| Inference Speed | ~40% faster | Baseline | +40% |
| ERNIE 4.0 (Baidu) | $0.55 | $0.55 | 128K |
DeepSeek V3.1 and V3.2 are minor updates to the V3 base model with alignment improvements, better instruction following, and safety updates. They do not introduce architectural changes and their performance is broadly similar to V3. For most users, upgrading directly from V3/V3.1/V3.2 to V4 Pro offers the best return on investment.
DeepSeek R1 (DeepSeek Reasoner) is a chain-of-thought reasoning model designed for complex multi-step problems. While V4 Pro handles most tasks efficiently, R1 excels at:
At $0.55/1M input tokens, R1 is more expensive than V4 Pro but justified for tasks that require deep reasoning.
| Use Case | Recommended Model | Rationale | |
|---|---|---|---|
| General chatbot / assistant | DeepSeek V4 Pro | Best balance of quality and cost | |
| High-volume production API | DeepSeek V4 Flash | most cost-effective option at $0.07/M | |
| Complex math / logic problems | DeepSeek R1 | Chain-of-thought reasoning | |
| Code generation & review | DeepSeek V4 Pro | Top coding performance (+7.1%) | |
| Long document processing | DeepSeek V4 Pro or Kimi K2.5 | 128K or 200K context window | |
| Legacy V3 migration | DeepSeek V4 Pro | Drop-in upgrade, lower price | |
| ERNIE 4.0 (Baidu) | $0.55 | $0.55 | 128K |
One API key for all DeepSeek models — V4 Pro, V4 Flash, R1, and V3.
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Yes. DeepSeek V4 Pro outperforms V3 across all benchmarks — especially coding, reasoning, and knowledge benchmarks — with a 128K context window and faster inference. The upgraded architecture also supports 128K context (up from 64K) and delivers ~40% faster inference.
Not always. Compare the current dated AIWave rate card, model quality, cache behavior, and workload before choosing a default.
V3.1 and V3.2 were minor refinements of the V3 base with alignment and safety improvements. They don't change the architecture or core performance. Users on any V3 variant should upgrade to V4 Pro.
V4 Pro is the full flagship model with maximum performance. V4 Flash is a distilled variant optimized for speed and cost — a lower AIWave input rate than Pro ($0.638 vs $1.914, updated 2026-08-19) with slightly lower but still strong quality.
R1 (Reasoner) excels at chain-of-thought reasoning but is a separate reasoning route with different pricing and workload behavior. Use V4 Pro for general tasks and R1 specifically when you need step-by-step logical reasoning for complex problems.
DeepSeek V4 Pro and V4 Flash support 128K tokens. DeepSeek R1 supports 128K tokens. DeepSeek V3 and all its variants (V3.1, V3.2) support 64K tokens.
Related: DeepSeek API pricing · DeepSeek V4 Pro
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