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OpenMythos-GGUF
educatedlucifer12/OpenMythos-GGUF
OpenMythos-GGUF is a machine learning model from educatedlucifer12. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
GGUF quantisation of build-small-hackathon/OpenMythos, a fine-tune of Qwen3.6-27B.
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jun 22, 2026
- Updated
- Jun 22, 2026
- SHA
- 58e33b12
Base models
Model card
From the Hugging Face model README
OpenMythos 27B - GGUF
GGUF quantisation of build-small-hackathon/OpenMythos, a fine-tune of Qwen3.6-27B.
Converted with convert_hf_to_gguf.py --no-mtp from llama.cpp build 9658.
The fine-tune does not include MTP head weights (dropped during training), so MTP
is not available in this GGUF.
Available Quantisations
| File | Size | Type |
|---|---|---|
| OpenMythos-27B-F16.gguf | 53.8 GB | F16 |
| OpenMythos-27B-Q5_K.gguf | 18.3 GB | Q5_K_M |
| OpenMythos-27B-Q4_K.gguf | 15.4 GB | Q4_K_M |
| OpenMythos-27B-Q6_K.gguf | 21.2 GB | Q6_K |
Benchmark
Evaluated with SecEval (commit 7aef317) on 2189
multiple-choice security questions. Backend: llama.cpp OpenAI-compatible server, fully
offloaded to GPU. No chain-of-thought / reasoning enabled (enable_thinking=false).
Prompt formatted with a system prompt requesting letter-only answers (no explanation).
| Set | Model | Score |
|---|---|---|
| A | OpenMythos-27B-Q5_K | 1703 / 2189 (77.8%) |
| B | VulnLLM-R-7B | 1315 / 2189 (60.1%) |
OpenMythos-27B-Q5_K test parameters
- model:
OpenMythos-27B-Q5_K.gguf - inference:
temp=0.2,top_p=0.8,top_k=20,min_p=0.05,repeat_penalty=1.02 - benchmark script:
/mnt/storage/SecEval-tmp/run_bench.py - output:
seceval-1781809723.json - prompt speed: 282 tok/s | generation speed: 68 tok/s
Per-topic scores
| Topic | Score |
|---|---|
| PenTest | 84.2% |
| MemorySafety | 83.3% |
| WebSecurity | 82.7% |
| Vulnerability | 77.8% |
| NetworkSecurity | 77.4% |
| SoftwareSecurity | 75.0% |
| ApplicationSecurity | 74.8% |
| SystemSecurity | 73.6% |
| Cryptography | 71.4% |
VulnLLM-R-7B test parameters
- model:
VulnLLM-R-7B.Q6_K.gguf - inference: same settings as above
- output:
seceval-1781811525.json - prompt speed: 148 tok/s | generation speed: 39 tok/s
Per-topic scores
| Topic | Score |
|---|---|
| PenTest | 70.9% |
| WebSecurity | 66.4% |
| Vulnerability | 58.7% |
| NetworkSecurity | 58.3% |
| SystemSecurity | 56.4% |
| SoftwareSecurity | 54.7% |
| ApplicationSecurity | 54.7% |
| MemorySafety | 54.2% |
| Cryptography | 28.6% |
Full detailed results are included in this repo: seceval-1781809723.json and
seceval-1781811525.json.
Usage
llama-server (recommended)
[OpenMythos-27B]
model = /mnt/storage/models/OpenMythos/OpenMythos-27B-Q5_K.gguf
chat-template-file = /mnt/storage/llama-server/chat_template-v15.jinja
ctx-size = 65536
cache-type-k = q8_0
cache-type-v = q8_0
cache-prompt = on
cache-reuse = 2048
batch-size = 4096
ubatch-size = 4096
kv-unified = on
parallel = 1
gpu-layers = all
temp = 0.2
top-p = 0.8
top-k = 20
min-p = 0.05
presence-penalty = 0.2
repeat-penalty = 1.02
spec-type = ngram-mod
spec-draft-n-max = 5
reasoning-format = deepseek
swa-checkpoints = 5
llama-cli
/mnt/storage/llama.cpp/build/bin/llama-cli \
-m /mnt/storage/models/OpenMythos/OpenMythos-27B-Q5_K.gguf \
--chat-template-file /mnt/storage/llama-server/chat_template-v15.jinja \
-c 65536 -b 4096 --ubatch-size 4096 \
--cache-type-k q8_0 --cache-type-v q8_0 \
--kv-unified -t 8 -fa \
--temp 0.2 --top-p 0.8 --top-k 20 --min-p 0.05 \
--presence-penalty 0.2 --repeat-penalty 1.02 \
-ngl all \
-p "Your prompt here"
- License
- apache-2.0
- Created
- Jun 22, 2026
- Updated
- Jun 22, 2026