Qwen2.5-14B-Instruct
7 workload results across 3 hardware configurations.
Fastest community-submitted config (not measured by llm-speed)
133.3 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, Qwen2.5-14B-Instruct is fastest on the M3 Ultra (60-core GPU) at 70.85 tok/s, 392% faster than the M3 Pro (18-core GPU) (14.41 tok/s).
| Card | Decode tok/s | TTFT (131-token prompt) | Run | Source |
|---|---|---|---|---|
| M3 Ultra (60-core GPU) | 70.85 (single run) | 434 ms | r_v4bq1sviz4o | community-submitted |
| M3 Pro (18-core GPU) | 14.41 (single run) | 1111 ms | r_ia73dzeue0b | community-submitted |
Qwen2.5-14B-Instruct, 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 (7 workload results)
All 4 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 | - | 130.3tok/s | no data | 48.6ms | r_xr4qdv1hgf2 | Community-submitted |
| chat-long | llama.cpp | - | 122.7tok/s | no data | 489ms | r_xr4qdv1hgf2 | Community-submitted |
| concurrent-decode | llama.cpp | - | 131.4tok/s | no data | no data | r_xr4qdv1hgf2 | Community-submitted |
| agent-trace | llama.cpp | - | 122.8tok/s | 20,315.4tok/s | 111ms | r_xr4qdv1hgf2 | Community-submitted |
| chat-short | llama.cpp | - | 133.3tok/s | no data | 55.9ms | r_tj9bu7gvnvh | 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 | 14.41tok/s | 117.9tok/s | 1,111ms | r_ia73dzeue0b | 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 | 70.85tok/s | 301.7tok/s | 434ms | r_v4bq1sviz4o | Community-submitted |
Can Qwen2.5-14B-Instruct 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.
Qwen2.5-14B-Instruct on hardware
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