gemma-2-9b-it
3 workload results across 3 hardware configurations.
Fastest community-submitted config (not measured by llm-speed)
152.7 decode tok/s
on RTX 5090 (32GB) via llama.cpp. see full run
For a standard 4-bit quantization using MLX, here are measured results for short-chat generation.
On MLX 4-bit, gemma-2-9b-it is fastest on the M3 Ultra (60-core GPU) at 89.45 tok/s, 307% faster than the M3 Pro (18-core GPU) (21.97 tok/s).
| Card | Decode tok/s | TTFT (118-token prompt) | Run | Source |
|---|---|---|---|---|
| M3 Ultra (60-core GPU) | 89.45 (single run) | 691 ms | r_iz137eqvuzy | community-submitted |
| M3 Pro (18-core GPU) | 21.97 (single run) | 1151 ms | r_q7t7b7dcuz5 | community-submitted |
gemma-2-9b-it, 4-bit, MLX, chat-short, batch 1. Only cards with their standard memory are listed; CPU-only hosts are excluded. Community-submitted runs are signed on the submitter's own machine and are not measured by llm-speed; llm-speed verdicts use only its own runs.
Signed runs (3 workload results)
All 3 runs are community-submitted (signed on the submitter's own machine, not measured by llm-speed, and not used for llm-speed verdicts).
RTX 5090 (32GB)
| Workload | Backend | Quant | decode tok/s | prefill tok/s | TTFT | Run | Source |
|---|---|---|---|---|---|---|---|
| chat-short | llama.cpp | - | 152.7tok/s | no data | 58.9ms | r__b_bzmmab_8 | Community-submitted |
M3 Pro (18-core GPU) + 36GB unified
| Workload | Backend | Quant | decode tok/s | prefill tok/s | TTFT | Run | Source |
|---|---|---|---|---|---|---|---|
| chat-short | mlx@0.31.3 | 4BIT | 21.97tok/s | 102.5tok/s | 1,151ms | r_q7t7b7dcuz5 | Community-submitted |
M3 Ultra (60-core GPU) + 96GB unified
| Workload | Backend | Quant | decode tok/s | prefill tok/s | TTFT | Run | Source |
|---|---|---|---|---|---|---|---|
| chat-short | mlx@0.31.3 | 4BIT | 89.45tok/s | 170.7tok/s | 691ms | r_iz137eqvuzy | Community-submitted |
Can gemma-2-9b-it run on your hardware?
Fastest decode speed on each GPU or Mac, from llm-speed's own runs and community-submitted runs. Each page lists every quant and runtime and labels which runs llm-speed measured.
gemma-2-9b-it on hardware
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