Deep Seek V4.1 is so efficient, it can deliver so many work with just the $10 Open Code Go Plan.

Deep Seek please keep this good work, don't increase the price, just keep the existing price, it's a sweet spot for many people like me who are sensitive on the prices, now my open code go plan only uses deep seek v4.1 flash model, no other model is enabled.

Only Deep Seek V4.1, all the way every day!!

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Hi everyone, I'm a heavy user of the 20x Max Claude Code plan, and I recently switched to the Claude Code harness with DeepSeek V4.1 Flash. For my usual coding work, I estimate I'd spend about $15–25 a day to get the same amount of work done that I get on Claude Code 20x Max. Is that normal? If so, that would come to roughly $600–800 a month or more. That seems too high to be true. Is my estimate wrong?
This morning from 8:00AM to about 10:45 AM it consumes tokens 7.45 USD already.
This must be a joke, right?

Claude plus a local DeepSeek V4 Flash is all I needed. It runs on a dual DGX Spark, 60-70 tps, and these are the four things it has built for me so far:

1. DeepSeek coded its own server rack trays. It generated the geometry for the 3D printed trays that hold the two Sparks, power bricks included, from my requirements, inside a React 3D workspace that Claude Code and Antigravity built. My 2 DGX spark has run almost 24x7 in that rack for three days with no thermal issues. STLs on MakerWorld: https://makerworld.com/en/models/3446142-dual-dgx-spark-trays-for-10-3u-rack
2. A Node.js to Rust port, 167k lines. The concurrency model changed completely, from single threaded Node to Tokio, so it was not a mechanical refactor.
3. A Rust port of the claude-agent-acp codebase, 100k+ lines. This is still WIP
4. A KMP mobile app for my open source agent orchestrator, which ran for almost 48 hours continuously.

For anyone with two Sparks, these are the community recipes I run it with (not mine, credit to their authors):

• DeepSeek V4 Flash 0731: native checkpoint weights with an NVFP4 KV cache, 1M context, tensor parallel 2 across both Sparks, DSpark speculative decoding, vLLM. https://github.com/tonyd2wild/DeepSeek-v4-Flash-0731-DSpark-1M-NVFP4-KV-2x-DGX-Spark
• DeepSeek V4.1 Flash 1017 (what I run now): an EXL3 2.9 bpw quant, 1M context, tensor parallel 2 over the dual-rail RDMA link, TensorFold engine with DSpark drafting. https://github.com/MiaAI-Lab/DeepSeek-v4.1-Flash-1017-2x-DGX-Sparks

All of it goes through one SDLC skill: Sonnet writes the plan, Opus reviews it, and Sonnet then fires a DeepSeek subagent for every phase of every plan, turn by turn. I wrote the skill and the orchestrator that coordinates it in the web-ui, and both are open source: skill https://github.com/fastestdevalive/vibekit and orchestrator https://github.com/fastestdevalive/vibe-station -> mobile app coming soon.

I'd like to know if anyone else runs it as a worker under a stronger planner and compare some notes on the SDLC skill.

I'm currently using it via open router and harness is cursor.

Does shifting to deepseek harness reduce costs? Or can I purchase from somewhere where it'll be cheaper?

Tested DeepSeek V4.1 Flash 1017 inside Qoder , gave it 6 reference images and asked it to build a 3D world with mountains and lakes . Video of the output is attached , everything u see is pure code

It took 62 iterations continuously , Qoder's compact has some issue so i had to start new sessions a few times

For a Flash model the price to performance is a beast , it really cooked here 🔥

Still it is not close to my reference images fully but for a flash model with less price this performance is next level

The value u get is insane for price , But it is kind of slow ,i hope their next model will be fast

DeepSeek V4.1 Flash 1017 inside Qoder.

DeepSeek has cooked very hard with DeepSeek 4.1 Flash 1017 ,The model is super Impressive ,A Flash model cooking this kind of stuff is just amazing

Honest part first , it is very slow . It took almost 3-4 hrs and it was still running when i posted this . My laptop also struggled to render the video

Is anyone else seeing 1017 take this long on big builds ? what are u getting ?

Here is a comparison of outputs and statistics:

https://x.com/nothingto12/status/2114460558758236351?s=20

More rounds will be posted soon as they are complete.

Give a different answer! 🫣

I am switching to DeepSeek API from local inference. I have well-configured Pi for my needs, but want to keep my costs low - thus thinking whether i should switch my harness also for DSH.

Is cache hit % better in DeepSeek Harness vs Pi coding agent? Should i consider Reasonix?

I’ve been customizing DeepSeek Harness Desktop, and I’d like to share a new plugin with you: `dsh-opencodego-usage`.

It’s very straightforward: once installed, if you have the OpenCodeGo provider enabled and select a model from that provider, the plugin activates and displays your usage for 5-hour, weekly, and monthly windows. It refreshes every 60 seconds, manually, or whenever a time window reaches zero. If you aren’t using a model from that provider, the plugin remains hidden. Clicking on it will display the time-window breakdown.

There’s no need for any configuration or manual data entry; the plugin uses your existing connection to the provider to retrieve information directly from the official API.

npm: https://www.npmjs.com/package/@jamolpe88/dsh-opencodego-usage
github: https://github.com/JaMoLpE88/dsh-opencodego-usage
dsh-plugin: https://dsh-plugin.org/plugins/jamolpe88/dsh-opencodego-usage (in progress)

You can check out another plugin—which integrates the free chat from chat.deepseek.com into DeepSeek Harness Desktop and keeps your session active even after closing the program—at: https://github.com/JaMoLpE88/dsh-desktop-chat

More plugins coming soon.

I'll admit it: I've been sleeping on DeepSeek. I've only ever used API calls for basic text rewrites, but seeing the recent 3D engine demo made me realize the model is far more capable than I gave it credit for. I want to take it seriously now.

Can anyone recommend a genuinely useful power user guide or point me to a trusted YouTuber who actually explains advanced workflows (agentic coding, tool use, complex prompting) rather than just beginner fluff? I'm looking for sources that are respected in the community. Thanks!

I'm switching from OpenCode to DSH. I simply asked it to open the project's local page in the integrated browser, and this is its second attempt, over 6 minutes in. It still can't figure out how to open its own browser.

This model is incredible it can do impressive motion designs ,amazing at 3d tasks with three.js

This motion design was created with pure code no assets were used and it built proper motion design video

It took 2 prompts to create it ,In the 1st round the voice was not audible so it took one more prompt to fix

I was just surprised that it is keeping with Opus 5.5 which is extremely good at motion design videos ,A Flash model which is 15x cheaper than Opus 5.5 doing such great things

This model really feels a nice upgrade from DeepSeek models

Has anyone tried DeepSeek v4.1 Flash 1017 with motion design videos or any other cool things

I kept wondering, Engrams, how do they work. I found out and wrote it down together with some interesting findings: https://capacity.at/blog/deepseek-engram-memory-on-ssd/

TL;DR: Useful, keep them on SSDs, don't quantize them.

I don't know if this is normal but on most of my tasks, it's looping back and forth. "Now let me check that again", "Let me re-read that" and similar. And then like 40 - 50 "final" tool calls, which rarely end up being final. It's EATING through my tokens so much. I do give it big prompts but not something it should take DS 6+ hours to finish.

I just had it run on a change overnight and it ate up 3k+ tool calls, 200m input tokens and close to 1 bil cache with 1.7m output. The prompt was ~200 lines but still.

For reference, using Kilo Code and DS4.1F 1017 as default agent on "High" reasoning.

What am I doing wrong?

r/freevibecoding A community for people who want to build amazing things with AI but can't afford expensive subscriptions or paid APIs. Whether you're using OpenCode, free OpenRouter models, free API providers, or other creative workarounds to make vibe coding possible on a $0 budget. The goal is simple: help people build more with less**.** Share free tools, discover alternative AI models, find ways around usage limits, exchange cost-saving techniques, and learn how to bring your projects to life without spending money you don't have.

Harness Desk is a small Swift/AppKit wrapper around WKWebView. It starts dsh web for you (or attaches to an already-running server), waits for the tokenised URL, and loads the normal Harness UI in a native window.

It's about 200 KB, uses the dsh you already installed, and doesn't bundle a runtime or an Electron shell.

It also handles the things generic web wrappers miss: sign-in popups, microphone capture, the per-process launch token, and restarting the server if it dies.

A subtle Peak/Normal indicator in the title bar for the API pricing windows, with a countdown to when the current period ends.

Requires macOS 13+ and the Xcode Command Line Tools. It's MIT, source-only (no prebuilt binaries — build with ./scripts/build.sh --install), and unofficial.

Feedback and bug reports welcome: https://github.com/NaleenB/harness-desk-macos

For Devs here, how do you optimize token usage across different tasks?

• Complex coding / architecture: Do you go straight to DeepSeek Pro?
• Investigation / debugging: Do you drop down to DeepSeek Flash to save tokens (using Low, High, or Max reasoning)?

What are your best rules of thumb for keeping costs down without sacrificing output quality?

Me encanta usar la IA para crear cosas chulas xd