AI Cockpit
AI Cockpit v…
by Ruggi Software —
Where Intelligence Compiles.
CLAUDE
CLAUDEArch
tune
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GEMINI
Auto
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OLLAMA
qwen2.5-coder:3b
qwen2.5-coder:3b
★ Tier 1 — Best for CRUD & Context
qwen2.5-coder:3b Fast coder, fits VRAM fully, best speed/quality ratio ★ default
qwen2.5-coder:7b Best all-rounder, strong instruction & code tasks ★ quality
deepseek-r1-tool-calling:7b Fine-tuned for structured tool/function calls ★ tools
glm4-cockpit GLM-4 9B tuned for your GPU (split + 8K ctx). Strong CRUD/context/agentic. Manual/scheduled use (>4B). Create via Model Manager → "Create tuned GLM-4". ★ context
Tier 2 — Good General Assistants
gemma3:12b Strong reasoning, runs on RAM, good context understanding
gemma3:4b Google model, good reasoning, fits VRAM
llama3.2:1b Lightweight Meta model, decent instruction following
llama3.2:3b Solid Meta model, good instruction following, VRAM-friendly
mistral:7b Strong instruction following, great context retention
qwen2.5-coder:1.5b Very fast coder, minimal VRAM, decent format compliance
qwen2.5:1.5b General Qwen, fast, modest context retention
qwen2.5:3b General Qwen assistant, use coder variant for file tasks
Tier 3 — Reasoning / Slow / Specialized
deepseek-r1:1.5b Reasoning model, wastes tokens on think-blocks for CRUD slow
deepseek-r1-tool-calling:14b Best tool-call quality but runs on RAM, slow interactive slow
gemma2:2b Older Google model, outclassed by gemma3 variants
gemma3:1b Too small for reliable instruction following tiny
gemma4:e2b Multimodal variant, runs on RAM, no text-CRUD advantage RAM
gemma4:e4b Multimodal variant, runs on RAM, no text-CRUD advantage RAM
olmo-3:7b Allen AI, decent chat but inconsistent format compliance
phi Older Microsoft model, mostly a demo, limited reliability
phi3.5 Microsoft model, reasonable but inconsistent on strict output
qwen3:0.6b Thinking model, too small for structured command syntax tiny
qwen3:1.7b Thinking model, better for reasoning than file operations
smollm2:135m Embedded/benchmark use only, not suitable for chat tasks tiny
smollm2:1.7b On-device model, too small for reliable format compliance tiny
smollm2:360m Embedded/benchmark use only, not suitable for chat tasks tiny
stablelm-zephyr:3b Decent chat but weak on structured output formats
starcoder2:3b Code completion model — not instruction/chat, wrong tool
starcoder2:7b Code completion model — not instruction/chat, wrong tool
tinyllama:1.1b Benchmark/toy size, not suitable for real tasks tiny
Tier 4 — Embedding Only — No Chat
mxbai-embed-large Text-to-vector embedding for RAG pipelines, not a chat model embed
nomic-embed-text Text-to-vector embedding for RAG pipelines, not a chat model embed
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WORKERS
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TOOLS
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Project: · Chat: Default ·
i5-10600K · 32GB · 12.5TB · RX6500XT 4GB
⇄ —
left_panel_open
Claude...
Gemini...
Ollama...
monitoring S — C — P — speed
folder_open /default/chat_default.json
right_panel_open
search keyboard_arrow_up keyboard_arrow_down
Msg#
System
Cockpit initializing — checking agent status...