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DeepSeek reasonix, DeepSeek native coding agent with high caching and low cost

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Re: DeepSeek reasonix, DeepSeek native coding agent with high caching and low cost

#321

Post by fouric »

gandreani wrote: post #320
fouric wrote: post #67

Earlier quoted context omitted.

I'd generally agree about Deepseek being as good as Sonnet - but I have extreme trouble with prompt compliance with V4 Pro in a way that I've never had with Sonnet. I'll tell it "find the bug, but don't fix it" or "please use this tool I just developed" and it'll ignore me a high fraction of the time. It's bad enough that I'm working on guardrails at the harness level because prompting appears to be useless. Do you h…

I also have this problem! It's the only model where an explicit instruction at the end of my message is sometimes ignored. This doesn't happen with any of the gpts, kimis, glms, qwen, etc. Just a deepseek problem. Hope it improves!

I'm glad I'm not going insane...

I have also noticed this with Sonnet, funnily enough - it's not as strong, but it's still there. But yeah, I haven't seen this with any other model so far (although I mostly use the stronger ones - maybe it's a function of intelligence?).

Re: DeepSeek reasonix, DeepSeek native coding agent with high caching and low cost

#322

Post by johalmed »

stavros wrote: post #189
bobkb wrote: post #141

Earlier quoted context omitted.

That’s impressive! On the sheer performance it’s comparable to Opus ?

Here are my stats (from DeepSeek directly, with a script I wrote). The prices are what equivalent Sonnet usage would have cost, the actual amount I paid was $10. On performance, DeepSeek V4 Pro is comparable to Sonnet for me. ./cost.py amount-2026-5.csv 0.3 3.75 15 input_cache_hit_tokens: 472,971,520 tokens -> $141.8915 input_cache_miss_tokens: 13,299,013 tokens -> $49.8713 output_tokens: 3,334,962 tokens -> $50.0244…

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Re: DeepSeek reasonix, DeepSeek native coding agent with high caching and low cost

#323

Post by wd021 »

0xbadcafebee wrote: post #99
unshavedyak wrote: post #49

It's pretty funny, i'm a $200/m Claude subscriber and i've had little need to use anything else. However the more Claude has been restricting my workflow (notably around the recent IDE/-p usage change) the more i've been wanting to go elsehwere. I'm concerned since i really want SOTA reasoning, but DeepSeek still has me interested.

You should definitely stick to the $200 plan, and not try the $10 coding plans with open weight models and higher limits. Anthropic needs your money to stay solvent, and you'll sleep better knowing you're using SOTA.

[dead]

Re: DeepSeek reasonix, DeepSeek native coding agent with high caching and low cost

#325

Post by estebarb »

ctxc wrote: post #215
estebarb wrote: post #196

Earlier quoted context omitted.

I'm not sure that is really the case, or relevant in practice. I have been using OpenCode with DeepSeek lately (regular coding). For instance, today I got 120 million input tokens hitting cache, vs just 2.59million missing cache.

Reads like a LOT of tokens to me. What does your usage /workflow look like? I'm v curious because although I do use Claude code, my token counts aren't nearly as much I want to know if I'm missing something cool!

Simply Ruby on Rails. I maintain 3 markdown documents with system design, implementation plan and use cases in repo. Then tell it those files exist and go implement X feature (from implementation plan). These documents, plus AGENTS.md, declare completion criteria, which includes full code coverage both with system and controller tests.

Usually I don't tell it to implement something adhoc, I first implement it in the documents first. LLMs are quite good to keep those documents in sync.

A good part of the implementation plan is that it keeps the LLM on track. With it, the LLM can understand why something must not be done yet, so it includes less unsolicited functionality. My workflow surely can be improved, but it has worked well for me.

In not sure about the actual costs, because I started using the same subscription for document parsing. But even then, I used less than $10 in may.

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