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Show HN: Claude Code's $200 plan is a 17× subsidy on the raw API

9 points by Hiteshjain118 4mo ago

Hiteshjain118 4mo ago
[flagged]
divyvasal 4mo ago
A 17x subsidy is crazy. It really highlights the hidden cost of context window re-evaluation in agent loops.
sibidharan 4mo ago
You mean if I use 2x $200 Max fully every week, I actually consume ~$5000 worth of API usage ?? Wow!!!
- Hiteshjain118 4mo ago
  My guess is you can push to $5k/month token usage with just a single Max subscription. During my 30 days analysis window, I consumed $3371 of token and didn't hit rate limits even once. I plan to keep pushing my token usage higher until I hit rate limits at least 5-10 times in a month.
  - sibidharan 4mo ago
    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
  - nbbaier 4mo ago
    It's hard for me to figure out what to use all those tokens for
- wd021 4mo ago
  [dead]
dnnddidiej 4mo ago
Subsidy? Sound more like raw API is just expensive.
- l2s0 4mo ago
  I agree with this, until we have actual info about how much is the API going to cost for the big lab, I wouldn't call it subsidy
  - Hiteshjain118 4mo ago
    I think we would know the costs when they go public. Before that may have infer costs through various signals.
kpratik16 4mo ago
Interesting analysis that most token cost is due to re-reading the same context.
- shanewei 4mo ago
  [flagged]
photonair 4mo ago
Does this mean Claude Code $200 plan is really costing them more to run it especially for power users or they are just ripping off people with API usage? If they are just subsidizing for the $200 plan, is it just a land grab for now? and then raise prices later?
- Lionga 4mo ago
  Clearly land grab, they reported billions of losses every quater. To be break even it needs to cost about 1000$ month, but then they would lose at lot of customers. Problem is they have no moat and will just burn billions of VC money to lose customers later.
  - photonair 4mo ago
    If I don't need something powerful like GPT 5.5 or Claude, I could just use Deepseek, Qwen or the cheaper chinese models. I think everyone is getting smart about routing their workload to models that are cheap but good enough to fulfill the request/task and then reserving the pricier like Claude for tasks needing higher intelligence.
    - Hiteshjain118 4mo ago
      Yup, I have been testing Qwen and Kimi lately. Seeing comparable accuracy of Qwen-Instruct (not thinking) to closed source models. Here's a blog we published on that https://www.coralbricks.ai/blog/alphacumen-finance-benchmarks https://www.coralbricks.ai/blog/alphacumen-finance-benchmark...
      - deleted 4mo ago
        [deleted]
    - mrkn1 4mo ago
      A lot of my queries are summarize/explain/fact check, and these are covered 100% on my CPU locally [0], reducing frontier model reliance [0] https://news.ycombinator.com/item?id=48301003 https://news.ycombinator.com/item?id=48301003
kevinsmith51 4mo ago
[flagged]
Alex_toani 4mo ago
I've been read reports which suggesting that the major AI model companies aren't particularly profitable. The ones actually making money are those selling servers and providing power infrastructure. The bulk of these companies' revenue flows straight to those costs, leaving slim profit margins. That's to say nothing of services like Claude and ChatGPT with their subscription tiers — unless, of course, they happen to land a customer who pays $200 a month and barely touches the product.
vagrantJin 4mo ago
Dubious at best. When you remember that there are open models with performance just as good as Sonnet that cost $2.50/M - $5/M output tokens. They don't have magically cheaper energy or compute costs. Anthropic premium pricing the API is just vibes. Like Starbucks. Like Lululemon. Like Apple.

9 points by Hiteshjain118 4mo ago

Hiteshjain118 4mo ago

[flagged]

divyvasal 4mo ago

A 17x subsidy is crazy. It really highlights the hidden cost of context window re-evaluation in agent loops.

sibidharan 4mo ago

You mean if I use 2x $200 Max fully every week, I actually consume ~$5000 worth of API usage ?? Wow!!!

Hiteshjain118 4mo ago
My guess is you can push to $5k/month token usage with just a single Max subscription. During my 30 days analysis window, I consumed $3371 of token and didn't hit rate limits even once. I plan to keep pushing my token usage higher until I hit rate limits at least 5-10 times in a month.
- sibidharan 4mo ago
  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
- nbbaier 4mo ago
  It's hard for me to figure out what to use all those tokens for
wd021 4mo ago
[dead]

dnnddidiej 4mo ago

Subsidy? Sound more like raw API is just expensive.

l2s0 4mo ago
I agree with this, until we have actual info about how much is the API going to cost for the big lab, I wouldn't call it subsidy
- Hiteshjain118 4mo ago
  I think we would know the costs when they go public. Before that may have infer costs through various signals.

kpratik16 4mo ago

Interesting analysis that most token cost is due to re-reading the same context.

shanewei 4mo ago
[flagged]

photonair 4mo ago

Does this mean Claude Code $200 plan is really costing them more to run it especially for power users or they are just ripping off people with API usage? If they are just subsidizing for the $200 plan, is it just a land grab for now? and then raise prices later?

Lionga 4mo ago
Clearly land grab, they reported billions of losses every quater. To be break even it needs to cost about 1000$ month, but then they would lose at lot of customers. Problem is they have no moat and will just burn billions of VC money to lose customers later.
- photonair 4mo ago
  If I don't need something powerful like GPT 5.5 or Claude, I could just use Deepseek, Qwen or the cheaper chinese models. I think everyone is getting smart about routing their workload to models that are cheap but good enough to fulfill the request/task and then reserving the pricier like Claude for tasks needing higher intelligence.
  - Hiteshjain118 4mo ago
    Yup, I have been testing Qwen and Kimi lately. Seeing comparable accuracy of Qwen-Instruct (not thinking) to closed source models. Here's a blog we published on that https://www.coralbricks.ai/blog/alphacumen-finance-benchmarks https://www.coralbricks.ai/blog/alphacumen-finance-benchmark...
    - deleted 4mo ago
      [deleted]
  - mrkn1 4mo ago
    A lot of my queries are summarize/explain/fact check, and these are covered 100% on my CPU locally [0], reducing frontier model reliance [0] https://news.ycombinator.com/item?id=48301003 https://news.ycombinator.com/item?id=48301003

kevinsmith51 4mo ago

[flagged]

Alex_toani 4mo ago

I've been read reports which suggesting that the major AI model companies aren't particularly profitable. The ones actually making money are those selling servers and providing power infrastructure. The bulk of these companies' revenue flows straight to those costs, leaving slim profit margins. That's to say nothing of services like Claude and ChatGPT with their subscription tiers — unless, of course, they happen to land a customer who pays $200 a month and barely touches the product.

vagrantJin 4mo ago

Dubious at best. When you remember that there are open models with performance just as good as Sonnet that cost $2.50/M - $5/M output tokens. They don't have magically cheaper energy or compute costs. Anthropic premium pricing the API is just vibes. Like Starbucks. Like Lululemon. Like Apple.