Running DeepSeek 7B on the RTX 5090 is a bit like putting a sports engine in a family car — it works brilliantly, but you have more power than the model strictly needs. At 95 tokens per second with 17.3 GB of spare VRAM, this is less about squeezing performance and more about building a platform that can grow with your workload. We measured everything on GigaGPU dedicated servers.
Near-Instant Generation
| Metric | Value |
|---|---|
| Tokens/sec (single stream) | 95.0 tok/s |
| Tokens/sec (batched, bs=8) | 152.0 tok/s |
| Per-token latency | 10.5 ms |
| Precision | FP16 |
| Quantisation | FP16 |
| Max context length | 16K |
| Performance rating | Excellent |
Benchmark conditions: single-stream generation, 512-token prompt, 256-token completion, llama.cpp or vLLM backend. GGUF Q4_K_M via llama.cpp or vLLM FP16.
At 10.5 ms per token, DeepSeek 7B on the 5090 generates text faster than most rendering engines can display it. The 152 tok/s batched throughput means this single GPU can realistically serve a team of 8-10 users simultaneously while keeping per-user latency well under a second. These numbers approach what you would expect from a dedicated inference cluster, not a single consumer GPU.
Massive Headroom
| Component | VRAM |
|---|---|
| Model weights (FP16) | 14.7 GB |
| KV cache + runtime | ~2.2 GB |
| Total RTX 5090 VRAM | 32 GB |
| Free headroom | ~17.3 GB |
Seventeen gigabytes of spare VRAM opens up possibilities beyond running a single model. You could load a second 7B model for A/B testing, run speculative decoding to push throughput even higher, or dedicate that memory to enormous KV caches supporting 16K context with many concurrent users. This is infrastructure-grade flexibility from a single card.
The Premium Tax
| Cost Metric | Value |
|---|---|
| Server cost | £1.50/hr (£299/mo) |
| Cost per 1M tokens | £4.386 |
| Tokens per £1 | 227998 |
| Break-even vs API | ~1 req/day |
At £4.39 per million tokens, the 5090 is not the most cost-efficient way to run DeepSeek 7B — the RTX 5080 at £3.88 and even the RTX 4060 at £4.42 offer comparable or better per-token economics. Where the 5090 justifies its £299/month is in scenarios requiring high concurrency, long context, or future-proofing for larger models. Batched, it delivers about £2.74 per million tokens. Check our benchmark comparisons for the full picture.
Building for Scale
The RTX 5090 is the right choice for DeepSeek 7B when you are building infrastructure rather than just running a model. If you need guaranteed low-latency serving for multiple users, plan to upgrade to larger models soon, or want the flexibility to run multi-model setups, this is the foundation to build on. For simpler single-user or development work, the 5080 or 3090 deliver more value per pound.
Quick deploy:
docker run --gpus all -p 8080:8080 ghcr.io/ggerganov/llama.cpp:server -m /models/deepseek-7b.Q4_K_M.gguf --host 0.0.0.0 --port 8080 -ngl 99Explore our DeepSeek hosting guide and GPU comparison for DeepSeek. See the LLaMA 3 8B on RTX 5090 or browse all benchmarks.
Scale-Ready DeepSeek 7B
95 tok/s, 17 GB headroom, 16K context. The GPU that grows with your ambitions.
Order RTX 5090 Server
