iapp/ openthai2.0-qwen3.8-27b:latest

26 6 days ago

OpenThai2.0 - Best All-in-One Opensource Thai Knowledge, Document, and Agentic AI

vision tools thinking 
ollama run iapp/openthai2.0-qwen3.8-27b

Details

6 days ago

b30f4bdc1c58 · 18GB

model
qwen35
·
27.3B
·
Q4_K_M
projector
clip
·
461M
·
BF16
params
{ "num_ctx": 32768, "repeat_penalty": 1.05, "temperature": 0.7, "top_k": 20, "to
template
{{- $lastUserIdx := -1 -}} {{- range $idx, $msg := .Messages -}} {{- if eq $msg.Role "user" }}{{ $la

Readme

OpenThai2.0 - Opensource Thai Knowledge, Document, and Agentic AI (GGUF)

ollama run iapp/openthai2.0-qwen3.8-27b

GGUF quantizations of openthai2.0-qwen3.8-27b (v9) for llama.cpp. Includes the MTP head (exported as nextn layers) and the vision projector.

file size use
openthai2.0-qwen3.8-27b-Q4_K_M.gguf ~17 GB recommended balance
openthai2.0-qwen3.8-27b-IQ2_M.gguf ~9.8 GB recommended 2-bit — imatrix-calibrated (Thai+EN); passes factual sanity checks that plain Q2_K fails
openthai2.0-qwen3.8-27b-Q2_K.gguf ~11 GB plain 2-bit — ⚠️ factual slips observed; prefer IQ2_M
openthai2.0-qwen3.8-27b-Q8_0.gguf ~29 GB near-lossless
mmproj-openthai2.0-qwen3.8-27b-F16.gguf — vision projector (documents/images)

Run

llama-server -m openthai2.0-qwen3.8-27b-Q4_K_M.gguf       --mmproj mmproj-openthai2.0-qwen3.8-27b-F16.gguf -c 32768

⚠️ The model reasons before it answers. Use a large context (32k) and leave max_tokens unset or >= 8192, or replies may come back empty.

Sanity-verified: Q4_K_M (CPU) and IQ2_M (GPU) answer Thai factual prompts correctly; imatrix-a80.dat is included for community re-quants. Full benchmarks and model card: see the main bf16 repo.