Qwen_3 GGUF
Collection
Upto Full precision (float32) version
β’
5 items
β’
Updated
β’
1
Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support
File Name | Size | Quantization | Format | Description |
---|---|---|---|---|
Qwen3_0.6B.F32.gguf |
2.39 GB | FP32 | GGUF | Full precision (float32) version |
Qwen3_0.6B.BF16.gguf |
1.2 GB | BF16 | GGUF | BFloat16 precision version |
Qwen3_0.6B.F16.gguf |
1.2 GB | FP16 | GGUF | Float16 precision version |
Qwen3_0.6B.Q3_K_M.gguf |
347 MB | Q3_K_M | GGUF | 3-bit quantized (K M variant) |
Qwen3_0.6B.Q3_K_S.gguf |
323 MB | Q3_K_S | GGUF | 3-bit quantized (K S variant) |
Qwen3_0.6B.Q4_K_M.gguf |
397 MB | Q4_K_M | GGUF | 4-bit quantized (K M variant) |
Qwen3_0.6B.Q4_K_S.gguf |
383 MB | Q4_K_S | GGUF | 4-bit quantized (K S variant) |
Qwen3_0.6B.Q5_K_M.gguf |
444 MB | Q5_K_M | GGUF | 5-bit quantized (K M variant) |
Qwen3_0.6B.Q8_0.gguf |
639 MB | Q8_0 | GGUF | 8-bit quantized |
.gitattributes |
2.04 kB | β | β | Git LFS tracking file |
config.json |
31 B | β | β | Configuration placeholder |
README.md |
3.53 kB | β | β | Model documentation |
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
Link | Type | Size/GB | Notes |
---|---|---|---|
GGUF | Q2_K | 0.4 | |
GGUF | Q3_K_S | 0.5 | |
GGUF | Q3_K_M | 0.5 | lower quality |
GGUF | Q3_K_L | 0.5 | |
GGUF | IQ4_XS | 0.6 | |
GGUF | Q4_K_S | 0.6 | fast, recommended |
GGUF | Q4_K_M | 0.6 | fast, recommended |
GGUF | Q5_K_S | 0.6 | |
GGUF | Q5_K_M | 0.7 | |
GGUF | Q6_K | 0.7 | very good quality |
GGUF | Q8_0 | 0.9 | fast, best quality |
GGUF | f16 | 1.6 | 16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
3-bit
4-bit
5-bit
8-bit
16-bit
32-bit