Qwen1.5 14B Chat on UDOO BOLT V8 (16 GB)
Can the UDOO BOLT V8 (16 GB) run Qwen1.5 14B Chat?
No, it doesn’t fit
No. Qwen1.5 14B Chat needs about 13.6 GB even at Q2_K; the UDOO BOLT V8 (16 GB) has 8.0 GB usable.
Download Qwen1.5 14B Chat
Recommended: Q2_K. Every other quantization has its own download link in the table below.
Quickest · Ollama
One command downloads a ready-to-run version and starts a chat.
ollama run qwen:14b-chat-v1.5-q2_KQuantized files · GGUF
Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.
Download the Q2_K file (opens in a new tab)
huggingface.co/Qwen/Qwen1.5-14B-Chat-GGUF (opens in a new tab)
ollama run hf.co/Qwen/Qwen1.5-14B-Chat-GGUF:Q2_KOriginal weights · Hugging Face
Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers.
How it’s rated
Match score
To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.
| Model quality | 3.2 / 45 | |
|---|---|---|
| Memory fit | 0.0 / 25 | |
| Speed | 0.0 / 15 | |
| Memory use | 0.0 / 15 | |
| Match score | 3.2 / 100 |
Every quantization on the UDOO BOLT V8 (16 GB)
| Quant | Memory needed | Available | Speed | Runs | Quality | Download |
|---|---|---|---|---|---|---|
Q2_K | 13.6 GB | 8.0 GB | — | Won't run | 23Basic quality (D) · 23 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 3/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q3_K_M | 14.9 GB | 8.0 GB | — | Won't run | 28Basic quality (D) · 28 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 3/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q4_K_M | 16.6 GB | 8.0 GB | — | Won't run | 32Basic quality (D) · 32 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q5_K_M | 18.0 GB | 8.0 GB | — | Won't run | 32Basic quality (D) · 32 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q6_K | 19.6 GB | 8.0 GB | — | Won't run | 33Basic quality (D) · 33 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
Q8_0 | 23.0 GB | 8.0 GB | — | Won't run | 34Basic quality (D) · 34 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking. | GGUF (opens in a new tab) |
F16 | 36.3 GB | 8.0 GB | — | Won't run | 34Basic quality (D) · 34 of 100: how capable the model is at F16, whatever it runs on. Match score 4/100 (quality, fit, speed and memory use) sets the ranking. | Original weights (opens in a new tab) |
Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.
Hardware that can run it
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34Basic quality (D) · 34 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 5090
-
33Basic quality (D) · 33 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 7900 XTX
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33Basic quality (D) · 33 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 3090
-
33Basic quality (D) · 33 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4090
-
28Basic quality (D) · 28 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking.
AMD Radeon RX 9070 XT
-
28Basic quality (D) · 28 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking.
NVIDIA GeForce RTX 4070 Ti SUPER
Models that do run on the UDOO BOLT V8 (16 GB)
- 57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. Ling 3.0 Tiny (8B-A1.3B)
- 76Great quality (A) · 76 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. K2 Horizon 7B
- 74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. MiMo V2.6 Distill Qwen 9B
- 74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. SenseNova Loop 9B Preview
- 73Great quality (A) · 73 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 9B
Quick answers
How much memory does Qwen1.5 14B Chat need on the UDOO BOLT V8 16GB?
Even at Q2_K it needs about 13.6 GB; the UDOO BOLT V8 16GB has 8.0 GB usable.
What can the UDOO BOLT V8 16GB run instead?
Ling 3.0 Tiny (8B-A1.3B), K2 Horizon 7B and MiMo V2.6 Distill Qwen 9B run best on it; the page lists more, each with its speed.
What hardware can run Qwen1.5 14B Chat?
RTX 5090 32GB, RX 7900 XTX 24GB and RTX 3090 24GB run it; the page lists more, each with its speed.
Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.