Table of Contents
Open vs Closed: Why It Matters
DeepSeek R1 is one of the first open-weight models to match GPT-4-class reasoning on key benchmarks. For organisations running inference on dedicated GPU servers, it represents a chance to own the entire stack: no per-token fees, no rate limits, and full data privacy. But does the quality hold up, and when does the economics of self-hosting actually win? This guide answers both questions.
GPT-4o is OpenAI’s flagship model, accessible only through their API. DeepSeek R1 is MIT-licensed and can be deployed on your own hardware. For hosting specifics, see our DeepSeek hosting page.
Model Specifications
| Feature | DeepSeek R1 (Full) | DeepSeek R1 Distill 70B | GPT-4o |
|---|---|---|---|
| Parameters | 671B (37B active) | 70B | Undisclosed |
| Architecture | MoE | Dense | Undisclosed (MoE likely) |
| Context | 128K | 128K | 128K |
| Access | Open weights (MIT) | Open weights (MIT) | API only |
| Self-Hostable | Yes | Yes | No |
The full R1 model requires significant hardware (8x 80 GB GPUs at FP16), but the distilled 70B variant runs on 2x RTX 3090 at 4-bit quantisation. See our DeepSeek VRAM requirements guide for detailed sizing.
Reasoning and Quality Benchmarks
| Benchmark | DeepSeek R1 (Full) | R1 Distill 70B | GPT-4o |
|---|---|---|---|
| MMLU | 90.8 | 79.4 | 88.7 |
| MATH-500 | 97.3 | 85.6 | 94.8 |
| GPQA Diamond | 71.5 | 58.2 | 53.6 |
| HumanEval | 84.1 | 72.3 | 90.2 |
| Codeforces Rating | 2,029 | 1,520 | 1,891 |
The full DeepSeek R1 matches or exceeds GPT-4o on most reasoning benchmarks, particularly on graduate-level science (GPQA). GPT-4o holds an edge on code generation (HumanEval). The distilled 70B version trails both but still outperforms all other open models at that scale. Check our benchmarks hub for GPU-specific throughput data.
Cost Comparison: Self-Hosted vs API
Using our cost-per-million-tokens calculator, here is how the economics compare at typical usage levels.
| Option | Input Cost / 1M Tokens | Output Cost / 1M Tokens | Monthly Fixed Cost |
|---|---|---|---|
| GPT-4o API | $2.50 | $10.00 | $0 |
| R1 Distill 70B (2x RTX 3090) | ~$0.08 | ~$0.08 | ~$300/mo server |
| R1 Distill 8B (1x RTX 3090) | ~$0.02 | ~$0.02 | ~$150/mo server |
Self-hosting breaks even at roughly 30 million tokens per month for the 70B distill. Above that volume, the savings compound rapidly. At 1 billion tokens per month, self-hosting R1 70B costs roughly 95% less than GPT-4o API. Use the LLM cost calculator for your specific volume.
Latency and Throughput
Self-hosted DeepSeek R1 Distill 70B on dual RTX 3090s delivers approximately 28 tokens/second at Q4 quantisation. GPT-4o API latency varies by load but typically starts at 40-60ms time-to-first-token with 60-80 tok/s generation. The API is faster for single requests, but a dedicated server handles concurrent batch workloads without rate limiting or queuing.
When to Self-Host DeepSeek R1
Self-host DeepSeek R1 when you need data privacy (no data leaves your server), predictable costs at high volume, no rate limits, or the ability to fine-tune. The full R1 matches GPT-4o quality and the 70B distill is competitive for most use cases.
Use GPT-4o API for low-volume workloads under 30M tokens/month, when you need the best code generation quality, or when you want zero infrastructure overhead.
For comparisons with other open models, see our LLaMA 3 vs DeepSeek and DeepSeek vs Mistral breakdowns. Browse all comparisons in the GPU comparisons section.
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