# This is my OpenCode setup for local models, mainly using a customized llama.cpp configuration. > Source: > Published: 2026-08-18 04:12:42+00:00 This is my OpenCode setup for local models, mainly using a customized llama.cpp configuration. For Qwen 3.8, DeepSeek V4, and Glimmer, the models are already trained to support reasoning effort levels. Depending on the model, these may be exposed as `low` , `medium` , `high` , `xhigh` , or as `low` , `high` , and `max` . For models that support reasoning but were not trained with explicit reasoning-effort levels, such as the Qwen 3.5 and 3.6 variants, I use a token budget to limit the amount of reasoning. Although Qwen 3.8 has built-in reasoning-effort levels, I still apply a maximum reasoning-token cap for each effort level. Although the llama.cpp CLI flags specify `preserve_thinking` and a default reasoning budget, these can still be overridden through the API, so this works fine for my setup. Yes, there is also an `xhigh-no-preserve` variant. In this mode, the model uses its reasoning as a scratchpad without preserving it in the conversation history. I use this when I do not want the reasoning output to unnecessarily consume the context window. Most of the time, I use `low` reasoning. ``` /home/USER/llama.cpp/llama-server \ --model /mnt/d/MODEL_STORE/LLM_SETUP/Qwen3.8-27B/Qwen3.8-27B-UD-Q5_K_XL.gguf \ --alias Qwen3.8-27B \ --host 0.0.0.0 \ --chat-template-file /mnt/d/MODEL_STORE/LLM_SETUP/Qwen3.8-27B/chat_template.jinja \ --no-context-shift \ --metrics \ --kv-unified \ --cache-ram 16384 \ --ctx-size 81920 \ --port 8001 \ --cache-type-k q8_0 \ --cache-type-v q8_0 \ --flash-attn on \ --temp 1.0 \ --top-p 0.95 \ --top-k 20 \ --min-p 0.0 \ --presence-penalty 0.0 \ --repeat-penalty 1.0 \ --jinja \ --chat-template-kwargs '{"preserve_thinking": true}' \ --spec-type draft-mtp \ --spec-draft-n-max 2 \ --reasoning-budget 8192 \ -np 1 \ -ub 256 ``` [https://huggingface.co/froggeric/Qwen-Fixed-Chat-Templates](https://huggingface.co/froggeric/Qwen-Fixed-Chat-Templates) `nvim ~/.config/opencode/opencode.json` ``` { "$schema": "https://opencode.ai/config.json", "plugin": [ "@tarquinen/opencode-dcp@latest" ], "provider": { "openai": { "options": { "headerTimeout": 60000, "timeout": 600000, "chunkTimeout": 60000 } }, "local-vllm": { "npm": "@ai-sdk/openai-compatible", "name": "vLLM (Local)", "options": { "baseURL": "http://localhost:8000/v1" }, "models": { "cyankiwi/Nemotron-Orchestrator-8B-AWQ-4bit": { "name": "cyankiwi/Nemotron-Orchestrator-8B-AWQ-4bit", "max_tokens": 40960 } } }, "local-llamacpp": { "npm": "@ai-sdk/openai-compatible", "name": "llama.cpp (Local)", "options": { "baseURL": "http://localhost:8001/v1" }, "models": { "Qwen3.6-35B": { "name": "Qwen3.6-35B", "max_tokens": 131072, "modalities": { "input": [ "image", "text" ], "output": [ "text" ] }, "variants": { "none": { "chat_template_kwargs": { "enable_thinking": false } }, "low": { "reasoning_budget_tokens": 512 }, "medium": { "reasoning_budget_tokens": 2048 }, "xhigh": { "reasoning_budget_tokens": 8192 }, "xhigh-no-preserve": { "reasoning_budget_tokens": 8192, "chat_template_kwargs": { "preserve_thinking": false } } } }, "Qwen3.8-27B": { "name": "Qwen3.8-27B", "max_tokens": 81920, "modalities": { "input": [ "image", "text" ], "output": [ "text" ] }, "variants": { "none": { "reasoningEffort": "none" }, "low": { "reasoningEffort": "low", "reasoning_budget_tokens": 512 }, "medium": { "reasoningEffort": "medium", "reasoning_budget_tokens": 2048 }, "xhigh": { "reasoningEffort": "xhigh", "reasoning_budget_tokens": 8192 }, "xhigh-no-preserve": { "reasoningEffort": "xhigh", "reasoning_budget_tokens": 8192, "chat_template_kwargs": { "preserve_thinking": false } } } }, "Muse-Glimmer-30B": { "name": "Muse-Glimmer-30B", "max_tokens": 81920, "modalities": { "input": [ "image", "text" ], "output": [ "text" ] }, "variants": { "low": { "reasoningEffort": "low", "reasoning_budget_tokens": 512 }, "medium": { "reasoningEffort": "medium", "reasoning_budget_tokens": 2048 }, "high": { "reasoningEffort": "high", "reasoning_budget_tokens": 4096 }, "xhigh": { "reasoningEffort": "xhigh", "reasoning_budget_tokens": 8192 } } }, "DeepSeek-V4-Flash-0731": { "name": "DeepSeek-V4-Flash-0731", "max_tokens": 81920, "variants": { "low": { "reasoningEffort": "low", "reasoning_budget_tokens": 512 }, "high": { "reasoningEffort": "high", "reasoning_budget_tokens": 4096 }, "max": { "reasoningEffort": "max", "reasoning_budget_tokens": 8192 } } }, "Omnicoder-2-9B": { "name": "Omnicoder-2-9B", "max_tokens": 131072, "modalities": { "input": [ "image", "text" ], "output": [ "text" ] }, "variants": { "none": { "chat_template_kwargs": { "enable_thinking": false } }, "low": { "reasoning_budget_tokens": 512 }, "medium": { "reasoning_budget_tokens": 2048 }, "xhigh": { "reasoning_budget_tokens": 8192 }, "xhigh-no-preserve": { "reasoning_budget_tokens": 8192, "chat_template_kwargs": { "preserve_thinking": false } } } }, "Ornith-9B": { "name": "Ornith-9B", "max_tokens": 131072, "modalities": { "input": [ "image", "text" ], "output": [ "text" ] }, "variants": { "none": { "chat_template_kwargs": { "enable_thinking": false } }, "low": { "reasoning_budget_tokens": 512 }, "medium": { "reasoning_budget_tokens": 2048 }, "xhigh": { "reasoning_budget_tokens": 8192 }, "xhigh-no-preserve": { "reasoning_budget_tokens": 8192, "chat_template_kwargs": { "preserve_thinking": false } } } } } }, "local-ninfer": { "npm": "@ai-sdk/openai-compatible", "name": "Ninfer (Windows)", "options": { "baseURL": "http://localhost:10909/v1" }, "models": { "qwen3.8-27b": { "name": "Qwen3.8-27B", "max_tokens": 81920, "variants": { "none": { "reasoningEffort": "none" }, "low": { "reasoningEffort": "low" }, "medium": { "reasoningEffort": "medium" }, "xhigh": { "reasoningEffort": "xhigh" } } } } } } } ``` - 3090 - WSL2 Ubuntu 24.04 - 6.18.33.2-microsoft-standard-WSL2 - E5 2690v4 - 96G RAM (For WSL2), Total 128G, DDR4 2400 ECC - Qwen 3.8 27B KV Q8:Q8 81920 : 30 tok/s - Qwen 3.6 35B A3B KV Q8:Q8 180224: 75 tok/s - DSv4 Flash KV Q8:Q8 65536: 6 tok/s