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I hit rate-limit every other day... 5 hour... Week... I consume my 20x weekly in 3 days! So having 2x 20x! If I could harness $10000 worth of API usage... this

I hit rate-limit every other day... 5 hour... Week... I consume my 20x weekly in 3 days! So having 2x 20x! If I could harness $10000 worth of API usage... this is the best time, no idea how long we will get this subsidy! I wont pay $10000 out of my pockets to do the same work!

Hiteshjain118 4mo ago
I'm curious what your token/$ usage looks like, if you'd be willing to share :)
- sibidharan 4mo ago
  TL;DR = ~$22,720 total compute @ Opus 4.7 if no caching = $113,418 (5.9x more) - this is just one month on one server... I have 3 more servers like this where I work all time! // Generated wit Claude Ran this on my own ~/.claude/projects/ (933 sessions, 93,842 model calls, mix of main thread + spawned subagents). Numbers came out very close to yours in shape, different in scale. cost.py (Opus 4.7 list rates, main thread only): cache reads (re-reading context) 21.69B tok $10,843 56% cache writes (1h) 678M tok $6,781 35% output (incl. reasoning) 63.5M tok $1,589 8% fresh uncached input 1.6M tok $8 0% TOTAL 22.43B tok $19,221 if no caching: $113,418 (5.9x more) input:output ratio: 353:1 cache hit rate: 97.0% token_time_breakdown.py (179M unique tokens, 166h wall clock): reasoning (hidden thinking) 29% of tokens, 102h (61%) of time bash 1.4% 23h (14%) writing tool calls 4% 14h (8%) summaries 2.5% 9h (5%) reading/searching/web 1.6% 7h (4%) subagents 0.2% 6h (4%) editing 0.1% 5h (3%) pasted attachments 25.3% - typed prompt 34.4% - system+tools 1.4% - reread_breakdown.py (per-activity share of billed input): reasoning 59.5% (~$11.4k of the bill is re-sending old hidden thinking back to the model) attachments 22.6% tool calls 7.8% bash 3.0% reading/web 2.4% my prompt 1.6% summaries 1.5% system+tools 0.8% subagents 0.4% main_vs_sidecar.py: main sidecar combined sessions/agents 449 484 933 assistant calls 63,820 30,022 93,842 cache hit 97.0% 94.4% 96.6% turns/agent 142 (median 20, max 11,058 in one session) 62 (median 44) reasoning % of out 82% 51% 77% cost @ Opus 4.7 $19,225 $3,495 $22,720 sidecar = 32% of calls but only 15% of cost. Subagents are doing their job (cheap, focused, short context). Same shape as yours: re-read dominates, reasoning is the biggest re-read line, caching is the only thing keeping it sane. The one that surprised me was a single 11,058-turn main session - some autonomous loop I forgot to kill. Going to grep for that. Repo: github.com/Coral-Bricks-AI/coral-ai/tree/main/claude-code-token-xray
  - Hiteshjain118 4mo ago
    Thanks for sharing your workload. Impressive! And this one person(you) steering all this token usage across the month? I want to double click on -- if the prices were to go high, you wouldn't be spending these many tokens. Would you just delay all those projects?
    - sibidharan 4mo ago
      Its just me steering all tokens... Multiple projects for my bootstrapped Academy, running parallel researches on things I wouldn't do myself, and deriving the right patterns for the future. Using different Max on same machine. I have similar ~$22K on another machine, where I am working in parallel with the same 2xMax subscriptions! So if the prices were to go high, I honestly have no idea at the moment. I might need a rehabilitation centre!!! But I am mentally prepared that someday this will be gone... So make hay while the sun shines! I am doing the most complex of all works I want to do... And pushing the limits. Knowing how much it costs in actual tokens, I give me some kind of seriousness, like an invisible funding that I must use to grow!! Considering this like a launchpad... If any of the projects hit and scale and I get some funding in future, then I might not need to worry when prices go high. So either this or rehab lol !
      - Hiteshjain118 4mo ago
        More power to you!

Hiteshjain118 4mo ago

I'm curious what your token/$ usage looks like, if you'd be willing to share :)

sibidharan 4mo ago
TL;DR = ~$22,720 total compute @ Opus 4.7 if no caching = $113,418 (5.9x more) - this is just one month on one server... I have 3 more servers like this where I work all time! // Generated wit Claude Ran this on my own ~/.claude/projects/ (933 sessions, 93,842 model calls, mix of main thread + spawned subagents). Numbers came out very close to yours in shape, different in scale. cost.py (Opus 4.7 list rates, main thread only): cache reads (re-reading context) 21.69B tok $10,843 56% cache writes (1h) 678M tok $6,781 35% output (incl. reasoning) 63.5M tok $1,589 8% fresh uncached input 1.6M tok $8 0% TOTAL 22.43B tok $19,221 if no caching: $113,418 (5.9x more) input:output ratio: 353:1 cache hit rate: 97.0% token_time_breakdown.py (179M unique tokens, 166h wall clock): reasoning (hidden thinking) 29% of tokens, 102h (61%) of time bash 1.4% 23h (14%) writing tool calls 4% 14h (8%) summaries 2.5% 9h (5%) reading/searching/web 1.6% 7h (4%) subagents 0.2% 6h (4%) editing 0.1% 5h (3%) pasted attachments 25.3% - typed prompt 34.4% - system+tools 1.4% - reread_breakdown.py (per-activity share of billed input): reasoning 59.5% (~$11.4k of the bill is re-sending old hidden thinking back to the model) attachments 22.6% tool calls 7.8% bash 3.0% reading/web 2.4% my prompt 1.6% summaries 1.5% system+tools 0.8% subagents 0.4% main_vs_sidecar.py: main sidecar combined sessions/agents 449 484 933 assistant calls 63,820 30,022 93,842 cache hit 97.0% 94.4% 96.6% turns/agent 142 (median 20, max 11,058 in one session) 62 (median 44) reasoning % of out 82% 51% 77% cost @ Opus 4.7 $19,225 $3,495 $22,720 sidecar = 32% of calls but only 15% of cost. Subagents are doing their job (cheap, focused, short context). Same shape as yours: re-read dominates, reasoning is the biggest re-read line, caching is the only thing keeping it sane. The one that surprised me was a single 11,058-turn main session - some autonomous loop I forgot to kill. Going to grep for that. Repo: github.com/Coral-Bricks-AI/coral-ai/tree/main/claude-code-token-xray
- Hiteshjain118 4mo ago
  Thanks for sharing your workload. Impressive! And this one person(you) steering all this token usage across the month? I want to double click on -- if the prices were to go high, you wouldn't be spending these many tokens. Would you just delay all those projects?
  - sibidharan 4mo ago
    Its just me steering all tokens... Multiple projects for my bootstrapped Academy, running parallel researches on things I wouldn't do myself, and deriving the right patterns for the future. Using different Max on same machine. I have similar ~$22K on another machine, where I am working in parallel with the same 2xMax subscriptions! So if the prices were to go high, I honestly have no idea at the moment. I might need a rehabilitation centre!!! But I am mentally prepared that someday this will be gone... So make hay while the sun shines! I am doing the most complex of all works I want to do... And pushing the limits. Knowing how much it costs in actual tokens, I give me some kind of seriousness, like an invisible funding that I must use to grow!! Considering this like a launchpad... If any of the projects hit and scale and I get some funding in future, then I might not need to worry when prices go high. So either this or rehab lol !
    - Hiteshjain118 4mo ago
      More power to you!