Imagine your LLM API gets featured on Hacker News and traffic triples in an hour. Which 7B model handles the surge on a single GPU without melting your p99? We pushed DeepSeek 7B and Qwen 2.5 7B to their limits under realistic concurrent load to answer exactly that question for dedicated GPU deployments.
The Answer, Fast
DeepSeek 7B handles 33.7 requests per second — triple Qwen’s 11.2 req/s. It is the only model in this pair that can sustain high-concurrency traffic on a single RTX 3090 without request queuing. Full comparison set: GPU comparisons hub.
Specifications
| Specification | DeepSeek 7B | Qwen 2.5 7B |
|---|---|---|
| Parameters | 7B | 7B |
| Architecture | Dense Transformer | Dense Transformer |
| Context Length | 32K | 128K |
| VRAM (FP16) | 14 GB | 15 GB |
| VRAM (INT4) | 5.8 GB | 5.8 GB |
| Licence | MIT | Apache 2.0 |
Qwen’s 128K context window is a double-edged sword for API serving: it enables longer requests but increases KV-cache memory per sequence, reducing how many concurrent requests the GPU can batch. DeepSeek’s 32K context keeps per-sequence overhead lower, directly translating into higher batch density. VRAM details: DeepSeek | Qwen.
API Load Test Results
Hardware: RTX 3090. Engine: vLLM, INT4, continuous batching. Load profile: 100 concurrent clients, 96-token average output, 5-minute sustained run. Live metrics: tokens-per-second benchmark.
| Model (INT4) | Requests/sec | p50 Latency (ms) | p99 Latency (ms) | VRAM Used |
|---|---|---|---|---|
| DeepSeek 7B | 33.7 | 83 | 450 | 5.8 GB |
| Qwen 2.5 7B | 11.2 | 115 | 333 | 5.8 GB |
DeepSeek triples Qwen’s throughput while maintaining a lower median latency (83 ms vs 115 ms). Qwen’s tighter p99 (333 ms vs 450 ms) means less tail-latency variance, but that advantage is irrelevant if the model cannot handle your request volume in the first place. For an API serving 50 concurrent chatbot sessions, DeepSeek handles them on one GPU; Qwen would need three.
Related: DeepSeek vs Qwen for Chatbots | LLaMA 3 vs DeepSeek for API Serving
What You Will Spend
| Cost Factor | DeepSeek 7B | Qwen 2.5 7B |
|---|---|---|
| GPU Required (INT4) | RTX 3090 (24 GB) | RTX 3090 (24 GB) |
| VRAM Used | 5.8 GB | 5.8 GB |
| Est. Monthly Server Cost | £169 | £98 |
| Throughput Advantage | 4% faster | 4% cheaper/tok |
Qwen’s lower sticker price is misleading at scale. If you need 30+ req/s, one DeepSeek server at £169 replaces three Qwen servers at £294 total. Calculate your breakeven with our cost-per-million-tokens calculator.
Picking Your API Model
DeepSeek 7B is the throughput winner by a wide margin. Choose it for any production API that may see traffic spikes — public-facing chatbots, developer tool backends, or multi-tenant SaaS platforms. Its 3x throughput advantage means fewer GPUs, simpler infrastructure, and lower total cost.
Qwen 2.5 7B is the right call only if your API handles long-context requests (4K+ tokens input) where the 128K window avoids truncation. Think document-heavy endpoints where each request includes full-page context from a knowledge base.
Both deploy behind vLLM on dedicated GPU servers. Hardware advice: best GPU for LLM inference.
Scale Your LLM API
Serve DeepSeek 7B or Qwen 2.5 7B on bare-metal GPUs with predictable billing and zero token caps.
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