DeepSeek 7B vs Mistral 7B for API Serving (Throughput): GPU Benchmark

When your product depends on an LLM-backed API, every millisecond of p99 latency and every extra request per second directly impacts user experience and infrastructure spend. We benchmarked DeepSeek 7B against Mistral 7B under realistic API traffic patterns to help you pick the right model for dedicated GPU serving.

Bottom Line

DeepSeek 7B doubles Mistral’s request throughput (24.4 vs 12.4 req/s) while maintaining comparable tail latency. If your API SLA centres on handling volume spikes without horizontal scaling, DeepSeek is the stronger choice. Browse more head-to-head tests in our GPU comparisons hub.

Model Specifications

Both architectures support 32K context, but the way they handle concurrent requests differs. DeepSeek’s vanilla dense attention is surprisingly efficient under continuous batching because vLLM can pack more sequences into memory when the KV-cache per sequence is predictable. Mistral’s SWA, while faster per-token, introduces variable memory patterns that slightly reduce batch density. Details: DeepSeek VRAM | Mistral VRAM.

API Throughput Under Load

Test setup: RTX 3090, vLLM with INT4 quantisation, 128-token average output, 64 concurrent clients ramping over 10 minutes. See real-time speed data on our tokens-per-second benchmark.

DeepSeek nearly doubles Mistral’s throughput. Mistral holds a slim 2 ms edge on median latency and a tighter p99, making it the better pick for latency-sensitive endpoints that never see high concurrency. But for any workload above ~15 requests per second on a single GPU, DeepSeek is the only option that avoids queuing.

Related: DeepSeek vs Mistral for Chatbots | LLaMA 3 vs DeepSeek for API Serving

Infrastructure Costs

Mistral is 10% cheaper per token if you are not saturating the GPU. Once you hit capacity and would need a second Mistral server, a single DeepSeek instance at £108/month beats two Mistral instances at £186/month. Run your numbers with our cost-per-million-tokens calculator.

Choosing Your API Model

DeepSeek 7B is the throughput king. Pick it when your API serves a product with unpredictable traffic spikes — think a public-facing chatbot widget or an internal tool used by hundreds of employees simultaneously.

Mistral 7B shines for low-concurrency, latency-critical APIs where p99 under 225 ms is non-negotiable and daily request volume stays below 1 million. Its SWA architecture keeps tail latency predictable.

Deploy either behind vLLM on a dedicated GPU server with continuous batching enabled. For hardware guidance, see our best GPU for LLM inference guide.