pnnbao-ump
VieNeu-TTS-0.3B-q4
Speech / audio
- Parameters
- 0.3B
- Max context length
- 4,096
- Architecture
- qwen3
- License
- Commercial OK
- Base model
- pnnbao-ump/VieNeu-TTS-0.3B
- License
- cc-by-nc-4.0
- llama.cpp
- b5092+
About VieNeu-TTS-0.3B-q4
VieNeu-TTS-0.3B-q4 is a GGUF model based on pnnbao-ump/VieNeu-TTS-0.3B on Hugging Face. GGUF files are published by pnnbao-ump/VieNeu-TTS-0.3B-q4-gguf. It has about 294M parameters, the qwen3 architecture, a maximum context length of 4,096 tokens (values written in the GGUF).
There is one quantization, Q4_0, with a file size of 0.20 GB (actual size on Hugging Face).
The original model is licensed under Apache License 2.0, which allows commercial use (keep the license text and copyright notice when redistributing). Check the original license for the terms of use.
File size and estimated memory per quantization
- Up to 8 GB
- Up to 16 GB
- Up to 24 GB
- Up to 48 GB
- Up to 128 GB
- More
File sizes are the actual values on Hugging Face. Memory is estimated for each context length (KV cache f16). The formula is in How memory is calculated.
All memory figures are Estimated (KV cache f16). It should run on a setup with at least this much VRAM (or Mac unified memory). Click a value to see the devices and models that fit that amount (Find by GPU / Mac).
About the "quality guide" (how far a quantization drifts from the original)
For each quantization type, how far the output drifts from the original model, grouped into six levels from values llama.cpp measured on Llama-3-8B.
The value is mean KLD (the difference between the original and quantized model in next-token probabilities); smaller means closer to the original. Quantizations made with an imatrix (importance data) come out slightly smaller. Levels use the value without an imatrix (or with one, for types that only have that).
These values were not measured on this model. Larger models and MoE models tend to drift less with the same type. Distributor-specific mixed types (such as UD-Q4_K_XL) cannot be matched by type name alone, so they show "-".
| Quantization | Quality guide | KLD (no imatrix) | KLD (imatrix) | Size (Llama-3-8B) |
|---|---|---|---|---|
| Q8_0 | Nearly identical | 0.0014 | - | 7.96 GiB |
| Q6_K | Very small | 0.0055 | - | 6.14 GiB |
| Q5_K_M | Very small | 0.0108 | - | 5.33 GiB |
| Q5_K_S | Small | 0.0166 | - | 5.21 GiB |
| Q5_1 | Small | 0.0180 | - | 5.65 GiB |
| Q5_0 | Small | 0.0222 | - | 5.21 GiB |
| Q4_K_M | Small | 0.0313 | 0.0282 | 4.58 GiB |
| Q4_K_S | Medium | 0.0431 | 0.0320 | 4.37 GiB |
| IQ4_NL | Small | - | 0.0357 | 4.35 GiB |
| IQ4_XS | Small | - | 0.0363 | 4.14 GiB |
| Q4_1 | Medium | 0.0717 | - | 4.78 GiB |
| Q4_0 | Medium | 0.0719 | - | 4.34 GiB |
| Q3_K_L | Medium | 0.0872 | 0.0731 | 4.03 GiB |
| Q3_K_M | Medium | 0.1019 | 0.0844 | 3.74 GiB |
| IQ3_M | Medium | - | 0.1025 | 3.53 GiB |
| IQ3_S | Medium | - | 0.1113 | 3.42 GiB |
| IQ3_XS | Large | - | 0.1387 | 3.28 GiB |
| IQ3_XXS | Large | - | 0.1836 | 3.05 GiB |
| Q3_K_S | Large | 0.2282 | 0.1998 | 3.41 GiB |
| IQ2_M | Large | - | 0.3260 | 2.74 GiB |
| Q2_K | Very large | 0.4451 | 0.3322 | 2.96 GiB |
| Q2_K_S | Very large | - | 0.4034 | 2.96 GiB |
| IQ2_S | Very large | - | 0.4392 | 2.56 GiB |
| IQ2_XS | Very large | - | 0.5463 | 2.43 GiB |
| IQ2_XXS | Very large | - | 0.8120 | 2.24 GiB |
| IQ1_M | Very large | - | 1.3931 | 2.01 GiB |
| IQ1_S | Very large | - | 2.2546 | 1.88 GiB |
Source: llama.cpp (MIT), measured on Llama-3-8B against FP16, Wikitext-2, revision f364eb6f. Original table · Reading and choosing quantizations
Last checked: Nov 11, 2026
- Architecture
- qwen3
- llama.cpp b5092 and later
- Parameters
- 0.3B
- Max context length
- 4,096
- License
- apache-2.0 Commercial OK
| Quantization | File size Measured | Quality guide | 4,096 max |
|---|---|---|---|
| Q4_0 | 0.20 GB | Medium | 0.99 GB |
Ollama ollama run hf.co/pnnbao-ump/VieNeu-TTS-0.3B-q4-gguf:Q4_0
llama.cpp llama-server -hf pnnbao-ump/VieNeu-TTS-0.3B-q4-gguf:Q4_0
License and commercial use
Apache License 2.0 Commercial OK
Allows commercial use, modification and redistribution. When redistributing, keep the license text and copyright notice, and note changes in modified files.
Based on the license on the original model's Hugging Face page. This differs from the GGUF repository's label (cc-by-nc-4.0). Quantized files are made from the original model, so check the original model's license terms as well. Original license text (checked Oct 18, 2026)
The summary states facts this site read from the original text and is not legal advice. Always check the original license and its latest terms before use. All licenses
How to run
Mainline llama.cpp can load this model's format (qwen3) from b5092 (Apr 9, 2025) onward. Ollama and LM Studio bundle llama.cpp internally, so an older app fails to load it with errors such as "unknown model architecture". If that happens, update the app.
Example commands using Q4_0. To use another quantization, replace the name with one from the table above. How to run local LLMs
Ollama
Run it by pointing directly at the GGUF on Hugging Face.
ollama run hf.co/pnnbao-ump/VieNeu-TTS-0.3B-q4-gguf:Q4_0
llama.cpp
Pass the repository and quantization name to llama-server (or llama-cli) with -hf.
llama-server -hf pnnbao-ump/VieNeu-TTS-0.3B-q4-gguf:Q4_0
LM Studio
Paste pnnbao-ump/VieNeu-TTS-0.3B-q4-gguf into the search box, download it, and choose the quantization from the file list.
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Frequently asked questions
- How much memory do I need to run VieNeu-TTS-0.3B-q4 (Q4_0)?
- The file size is 0.20 GB (measured). With a 4,096-token context, the estimated memory including the KV cache is 0.99 GB. The formula is published at https://localllm.az-arte.com/en/guide/memory-calculation.
- Can VieNeu-TTS-0.3B-q4 be used commercially?
- The original model's license is Apache License 2.0 (Commercial use allowed).Allows commercial use, modification and redistribution. When redistributing, keep the license text and copyright notice, and note changes in modified files. Check the original license text before deciding.
- What is the command to run VieNeu-TTS-0.3B-q4 with Ollama?
- Run "ollama run hf.co/pnnbao-ump/VieNeu-TTS-0.3B-q4-gguf:Q4_0" to use the GGUF on Hugging Face directly. To use another quantization, replace the name at the end.