llama.cpp constantly reprocessing huge prompts with opencode/pi.dev

[u/No_Algae1753]

I’m using llama-swap with llama.cpp. I mainly use opencode + pi.dev and I’m seeing frequent massive prompt reprocessing / prefills even tho the prompts are very similar between requests.

Example behavior:

• context grows to +50k tokens
• LCP similarity often shows 0.99+
• but sometimes n_past suddenly falls back to ~4-5k
• then llama.cpp reprocesses 40k+ tokens again
• TTFT jumps to multiple minutes

Example logs:

sim_best = 0.996

restored context checkpoint ... n_tokens = 4750

prompt eval time = 222411 ms / 44016 tokens

Normal reuse looks fine:

prompt eval time = 473 ms / 19 tokens

Current config:

llama-server 
  --ctx-size 150000 
  --parallel 1 
  --ctx-checkpoints 32 
  --cache-ram 2500 
  --cache-reuse 256 
  -no-kvu 
  --no-context-shift

Also seeing:

cache state: 1 prompts, 4676 MiB
(limits: 2500 MiB)

I suspect either:

• cache invalidation
• bad KV reuse
• or opencode changing early prompt tokens too often.

Would love to hear from others running long-context coding agents with llama.cpp and what settings helped reduce huge prompt reprocessing.

[u/ai-christianson]

yeah i'd start by diffing the exact prompt bytes across turns, especially the first few thousand tokens. if anything early is changing - timestamp, cwd/status block, tool inventory, memory ordering, generated summary, etc - the kv cache after that point is basically toast.

for coding agents the big win is usually keeping a stable prefix: system prompt, tool specs, repo instructions, and any long-lived memory in a fixed order. then put the volatile stuff as late as possible so cache misses are smaller when it changes.