Local AI Advisor

Can Desktop PC · Ryzen 9 9950X (no GPU) · 64 GB DDR5 run Kolibri-1 (78B-A3.5B)?

64 GB RAM, no GPU · Kolibri-1 (78B-A3.5B) has 78.1B parameters (3.46B active per token).

Short answer

Yes, comfortable for chat; borderline for agentic coding.

Best quantization for chat: Q4_K_M (45 GB of weights) on llama.cpp (llama-server). Generation: 13–20 tok/s, leaving about 7.0 GB free for your other apps.

How it rates for each workload

Same model and machine, different jobs. Agents and long documents send far bigger prompts than chat, so they need much more speed and memory.

WorkloadVerdictQuantGenerationFirst replyContext
Chatwith Open WebUIComfortableQ4_K_M13–20 tok/s≈3 s8KDetails
Coding questionswith ContinueAcceptableQ4_K_M12–20 tok/s≈20 s16KDetails
Coding in a repositorywith AiderAcceptableQ4_K_M11–19 tok/s≈55 s32KDetails
Agentic codingwith OpenCodeBorderlineQ4_K_M11–18 tok/s≈75 s32KDetails
Long documents (64K)with Open WebUIAcceptableQ4_K_M9–14 tok/s≈4 min64KDetails

Speeds are bandwidth-based estimates; no direct benchmark exists for this pair. “First reply” is the time to read the workload’s opening prompt. How we calculate

Different tool, context size or workload?

These pages use typical settings. The full check models your exact setup.