u/Aromatic_Pumpkin8856

What happened

I've been a heavy Claude Code user for months. I instrument everything through SigNoz so I have actual data, not vibes. For a long time, Anthropic was excellent — I consistently struggled to hit my token limits. That's the good problem.

Then something changed on Anthropic's side. I don't know exactly what, maybe extended thinking changes, maybe rate limit policy, maybe something else. But around April 17–18, a single /review-pr command started eating through more than half my 5-hour token window. My workflow didn't change. I run the same commands I've run for months. The model behavior did.

The result: Mon Apr 20 and Tue Apr 21, I was getting throttled repeatedly mid-session. Same work — implementation, code review, multi-agent orchestration. Just constantly hitting walls.

At 9:51am PDT today I switched Claude Code to deepseek-v4-pro:cloud via Ollama Cloud's $20/mo Pro plan. Here's what happened.


The data

Two metrics that matter: lines of code changed per hour (real output) and lines per million tokens (efficiency — how much code gets produced per unit of compute).

Session Avg tok/hr Lines/hr Lines/M-tok
Thu Apr 16 — Anthropic at its best 29,555,000 1,688 41.5
Sat Apr 18 — something starting to shift 14,640,000 717 35.0
Mon Apr 20 — throttled, cutting out 10,475,000 289 18.4
Tue Apr 21 — throttled again 12,860,000 431 22.3
Today Apr 29 — Ollama Cloud / DeepSeek 21,466,000 1,174 54.7

Mon and Tue weren't a different type of work. It was the same implementation and review work I've done for months. The throttling is what cut the output.


The part that floored me

DeepSeek on Ollama Pro is slower than Claude. My plan caps me at 3 concurrent cloud models. I regularly run 14+ parallel agents — church review swarms, dual-repo implementations, blog agents, the works. Today all of that had to queue.

And I still produced 1,174 lines/hr — nearly 70% of my best-ever Anthropic session, which had no concurrency limits and a faster model.

Compared to what Anthropic has been delivering this week: 2.7–4× more productive, with more constraints, on a plan that costs 10× less.


My honest takeaway

DeepSeek is better. Not "competitive." Not "surprisingly good for the price." Better. At least for the way I work — heavy parallelism, large codebases, long multi-agent sessions.

Anthropic's Claude used to be the clear answer for me. Thursday's session proves it can still hit those peaks. But whatever changed in the past week has made it unusable for my workflow at the rate limits they're enforcing. DeepSeek through Ollama Cloud doesn't have that problem.

$200/mo → $20/mo. More productive. Less friction.

I'll keep tracking the data and post a follow-up after a full week.

reddit.com
u/Aromatic_Pumpkin8856 — 15 days ago

The 5h bar in the strip above is red despite being only half-full. The bar colors by pace, so 50% used with only 49 minutes elapsed in a 5-hour window puts me ~34 percentage points ahead, which trips red. If I'd used 85% of my weekly budget by day 6, that would be fine. 85% by day 3 would mean I'm on track to blow through the window before it resets.

Computed as used% - elapsed%:

  • ≤ 0 → green (on or under pace)
  • up to 15 percentage points ahead → yellow
  • more than 15 → red

So: 5h bar at 50% used and ~16% elapsed = ~34 points ahead → red. 7d bar at 9% used and ~3.5% elapsed = ~5 points ahead → yellow. The ctx bar is fill-based; context isn't a time window.

Anthropic's official usage panel and ccusage both report how much I've used. Neither tells me whether I'm using it too fast. Without a color signal, you can't tell from a 50% reading whether you're on pace or about to crash through the limit early. The pace bars answer that question: am I about to get rate-limited mid-task?

Full writeup with the bash and the thresholds here

u/Aromatic_Pumpkin8856 — 18 days ago

Welcome to r/PracticalAIDev

This community is for developers, makers, and technical builders using AI to create real things.

There are plenty of places online to argue about models, complain about rate limits, or recycle hot takes. This is not one of them.

r/PracticalAIDev is for practical, useful discussion around AI in software development:

* Projects you’ve built with AI help

* Coding workflows that genuinely save time

* Tool reviews (Claude Code, Cursor, Copilot, etc.)

* Prompting techniques that improve results

* Architecture and engineering tradeoffs

* Useful AI news for developers

* Questions from people trying to get better

What We Value

* Building over complaining

* Signal over noise

* Helpful feedback over ego

* Real examples over vague claims

* Curiosity over gatekeeping

What to Do First

  1. Introduce yourself in the comments
  2. Share what you’re building or learning
  3. Ask a practical question
  4. Post something useful for other developers

Founding Members Matter

You’re here early, which means you help shape what this place becomes.

Let’s build a community worth checking every day.

reddit.com
u/Aromatic_Pumpkin8856 — 25 days ago