Table of Contents
Quick Verdict
Phi-3 Mini has 3.8B parameters. Gemma 2 9B has 9B. Yet Phi-3 generates at 125 tok/s versus Gemma’s 85, scores higher on multi-turn evaluation (8.2 versus 7.6), and uses less than half the VRAM. On a dedicated GPU server, Microsoft’s compact model punches well above its weight class — a testament to the quality-of-data-over-quantity-of-parameters philosophy behind its training.
Gemma 2 9B’s only structural advantage is its larger model capacity, which can help with knowledge-intensive queries. For general chatbot deployment, Phi-3 Mini is the better value.
Full data below. More at the GPU comparisons hub.
Specs Comparison
Phi-3 Mini’s 128K context window versus Gemma’s 8K is a sixteen-fold advantage for conversations that reference long histories or uploaded documents.
| Specification | Phi-3 Mini | Gemma 2 9B |
|---|---|---|
| Parameters | 3.8B | 9B |
| Architecture | Dense Transformer | Dense Transformer |
| Context Length | 128K | 8K |
| VRAM (FP16) | 7.6 GB | 18 GB |
| VRAM (INT4) | 3.2 GB | 7 GB |
| Licence | MIT | Gemma Terms |
Guides: Phi-3 Mini VRAM requirements and Gemma 2 9B VRAM requirements.
Chatbot Performance Benchmark
Tested on an NVIDIA RTX 3090 with vLLM, INT4 quantisation, and continuous batching. See our tokens-per-second benchmark.
| Model (INT4) | TTFT (ms) | Generation tok/s | Multi-turn Score | VRAM Used |
|---|---|---|---|---|
| Phi-3 Mini | 54 | 125 | 8.2 | 3.2 GB |
| Gemma 2 9B | 59 | 85 | 7.6 | 7 GB |
Phi-3 Mini’s 47% higher generation speed means users receive complete responses significantly faster. At 125 tok/s, a 200-token reply streams in 1.6 seconds. At 85 tok/s, the same reply takes 2.4 seconds. See our best GPU for LLM inference guide.
See also: LLaMA 3 8B vs Phi-3 Mini for Chatbot / Conversational AI for a related comparison.
See also: LLaMA 3 8B vs Gemma 2 9B for Text Summarisation for a related comparison.
Cost Analysis
Phi-3 Mini’s 3.2 GB INT4 footprint means you can run multiple instances on a single GPU, or co-locate it with other models for multi-task deployments.
| Cost Factor | Phi-3 Mini | Gemma 2 9B |
|---|---|---|
| GPU Required (INT4) | RTX 3090 (24 GB) | RTX 3090 (24 GB) |
| VRAM Used | 3.2 GB | 7 GB |
| Est. Monthly Server Cost | £141 | £123 |
| Throughput Advantage | 13% faster | 4% cheaper/tok |
See our cost-per-million-tokens calculator.
Recommendation
Choose Phi-3 Mini for most chatbot deployments under 10B parameters. It is faster, higher quality, smaller, and has a more permissive licence. Its 128K context window also enables use cases that Gemma’s 8K limit simply cannot support.
Choose Gemma 2 9B if you need the broader world knowledge that comes with 9B parameters for knowledge-intensive conversations, or if Google’s ecosystem tooling is important for your deployment workflow.
Deploy on dedicated GPU hosting for production chatbot performance.
Deploy the Winner
Run Phi-3 Mini or Gemma 2 9B on bare-metal GPU servers with full root access, no shared resources, and no token limits.
Browse GPU Servers
