Qwen / text-generation Open weights updated 2 years ago

Qwen2.5-7B-Instruct-GGUF

Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters. Qwen2.5 brings the following improvements upon Qwen2:

Params
7.0 B
Context
32,768
Downloads 30d
187 K
Likes
200
Commercial use: allowed apache-2.0 Not gated GGUF 1 languages View on Hugging Face ↗

Download history

daily snapshots · 11 days
187 K170 K
Oct 15Oct 18Oct 22Oct 25

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
qwen2.5-7b-instruct-q2_k.gguf Q2_K 3.0 GB 4.9 GB ✅ Runs comfortably
qwen2.5-7b-instruct-q3_k_m.gguf Q3_K_M 3.8 GB 5.7 GB ✅ Runs comfortably
qwen2.5-7b-instruct-fp16-00001-of-00004.gguf GGUF 4.0 GB 5.9 GB ✅ Runs comfortably
qwen2.5-7b-instruct-q4_0-00001-of-00002.gguf Q4_0 4.0 GB 5.9 GB ✅ Runs comfortably
qwen2.5-7b-instruct-q4_k_m-00001-of-00002.gguf Q4_K_M 4.0 GB 5.9 GB ✅ Runs comfortably
qwen2.5-7b-instruct-q5_k_m-00001-of-00002.gguf Q5_K_M 4.0 GB 5.9 GB ✅ Runs comfortably
qwen2.5-7b-instruct-q6_k-00001-of-00002.gguf Q6_K 4.0 GB 5.9 GB ✅ Runs comfortably
qwen2.5-7b-instruct-q5_0-00001-of-00002.gguf Q5_0 4.0 GB 6.0 GB ✅ Runs comfortably
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub
~ · ollama · Q4_0
$ ollama run qwen2-5-7b-instruct-gguf-qwen

# pin the quantization explicitly
$ ollama run qwen2-5-7b-instruct-gguf-qwen-q4_0
est. VRAM 5.9 GBon RTX 4090 · 24 GBJSON API →

Specifications

Parameters
7.0 B
Context length
32,768
Licence
apache-2.0
First seen on the Hub
2024-09-17
Base model
Qwen2.5-7B-Instruct
Training datasets
undisclosed
Added to our catalog
2026-10-15

Family

Base model and the most-downloaded derivatives in the catalog.

Compare with any text-generation model