this is the best trick to maximum usage limits... on chatgpt codex codex's best kept secret is that your main agent doesn't have to do everything... custom agents are just files in ~/.codex/agents, and one file gives you a second worker on deepseek v4 flash > create ~/.codex/agents/deepseek-worker.toml > set model = "opencode-go/deepseek-v4-flash" with model_reasoning_effort = "max" > keep it bounded: one task packet, no scope creep, report back ```toml name = "deepseek_worker" description = "bounded implementation, testing, and cleanup on deepseek v4 flash" model = "opencode-go/deepseek-v4-flash" model_reasoning_effort = "max" ``` then @ deepseek_worker in the composer... your root agent plans while the worker ships the implementation planning on the main model, execution on the flash lane... that's the whole trick (we run this exact file, last i checked it keeps the heavy turns off the main thread)show more

deepseek v4 pro is basically free right now 😳... teamorouter is offering deepseek v4 pro at almost no cost you can also use deepseek v4 flash for free what you get: - deepseek v4 pro free - deepseek v4 flash free - 1M context - openai compatible api - no subscription - credits never expire why this is worth checking: > v4 pro is currently listed at $0 input and output > flash is also available at $0 > works with claude code, codex and other tools > one api gives you access to multiple models getting started: 1. go to 2. create your account 3. open the dashboard 4. create your api key base url: 5. add it to your ai coding tool 6. select deepseek-v4-pro-free worth testing while it’s availableshow more

Codex can now run Deepseek-v4- flash! There's a catch... though. Deepseek's official setup switches your entire codex over to them, so your GPT models stop showing up at all. This is exactly what Codex Router is for. It adds models to the list instead of replacing them, so sol, grok, kimi and deepseek all sit in the same picker and i just grab whichever one suits the job. Deepseek v4-flash is $0.28 per million output tokens. opus 4.8 is $25. same picker, 89x apart. Links in the comment. setup's in the video 👇show more

this is literally f**king insane i just 2x my... usage limits on $200/mo codex i figured out how to use deepseek v4.1-flash on $10/mo opencode go for routine subagent work... while gpt-6 astra directs the project and sol handles implementation. here's how to set it up in 3 mins: → connect opencode go to codex through model-router → install quota flow, including its skill and agent profiles → open a fresh astra task and paste: quota flow tells flash to handle discovery and checks, sol to implement, and luna to review when needed. the same implementation agent keeps its context through the build → test → fix loop. every extra agent should earn its call.show more

holy sh*t this is f**king dangerous i just figured... out how to run Opencode in Codex It has Deepseek V4 Flash which replaces Opus 5 at 1/4th price You can get 10,000 request in only $10/month along with Kimi K3 and Qwen 3.5 Max [here is how you set it up] 1. install the 'codex-router' 2. Put in the Opencode Go API key 3. Done that's it Save this no matter what. This will be the best thing you do this weekshow more

DeepSeek V4 Flash 0731 first test. DeepSeek V4 Flash... 0731 is ridiculously cheap compared to Kimi K3, GPT-5.6, and Opus 5 For its price, this is a surprisingly capable model. First challenge: Generate a railway station in Three.js. The result exceeded my expectations for such a low-cost model. It’s definitely one to watch if you’re building 3D projects on a tight budget.show more

"You've reached your rate limit. Try again after 7pm."... every. fucking. day. $200/month - $2,400 a year - for Codex. then i opened the DeepSeek pricing page. Someone made DeepSeek a native subagent for Codex. Heavy work goes there, light stays on GPT-5. Same code out the other end. 35x cheaper. DeepSeek V4 Flash lives on its own API key, not on my Plus quota. One command: npx skills add oil-oil/codex-deepseek-subagent -g -y Restart Codex, tell it "set up DeepSeek as a subagent", done. First day in a month I'm still working in the evening instead of hitting the wall. save this before your next rate-limit ↓show more

QWEN 3.8 MAX + DEEPSEEK V4 PRO BOTH FREE... ON ONE ENDPOINT • the gateway > Qwen3.8-Max (2.4T MoE) + DeepSeek V4 Pro free tiers: > Sign up -> one API key -> start with no card for free tier. > Free is tight by design -- they’re letting you taste the real thing before you scale. • wiring it up > Base url: >Model IDs exact: qwen/qwen3.8-max-free and deepseek/deepseek-v4-pro-0813-free. > Drop straight into Cursor/Claude Code/any OpenAI-compatible client. Good for long agent runs you leave open on a second screen, slow for anything interactive. Point it at side projects and experiments, not at the code you would mind a stranger reading ↓show more

Got DeepSeek V4 Flash running on 2x H200s at... 160–200 tok/s on JarvisLabsAI this speed is perfect for in the loop things I do with these agents. It feels like a GLM-5.2-class model with much lower hardware requirements. I’m going to daily-drive it for a bit and see how it performs, but first impressions are really good.show more

DEEPSEEK V4 FLASH AND QWEN3.6 ARE FREE ON AMD'S... OWN CLOUD AT $10 OF USAGE A DAY • AMD Token Factory > DeepSeek V4 Flash, Qwen3.6 35B, MiniCPM5 and MiniCPM-V46 at zero cost: > $10 every day, not once -- the counter resets daily. > Everything outside that list runs on Firework AI credits. • SuperGrok, seven days > Grok's paid tier free for a week: > A card is required and it renews on its own, so set the reminder the moment you start. > Availability still depends on your region. AMD built this the way NVIDIA built NIM -> the chip vendors are handing out inference now, because what they are really buying is which silicon you learn on. One of these resets every morning. The other one you only get once ↓show more

you don't need Seedance 2.5, here's cheaper and more... efficient workflow we made this entire game shooting scene in one shot for $1.97 with DeepSeek V4 Flash 0731 + MiniMax H3 we use DeepSeek to code the raw Three.js scene first: exact camera movement, character motion, timing, everything. keep tweaking it there for basically pennies. then feed the final footage into H3 and let it cook the realism 48 mins, $1.97 total, one H3 generation way cheaper than rerolling a video model 10 timesshow more

i found a way to make UNCENSORED AI AGENT... on a RTX 4090 GPU (!!!) with LOCAL 30B model weights this is GLM-4.7-Flash with abliteration, need 24GB VRAM, safety alignment surgically removed from the weights, the model has native tool calling, it actually executes bash, edits files, runs git (1) use ollama to pull weights of GLM > ollama pull huihui_ai/glm-4.7-flash-abliterated:q4_K (2) proxy it to any coding agent via ollama > ollama launch claude --model huihui_ai/glm-4.7-flash-abliterated:q4_K > ollama launch codex --model huihui_ai/glm-4.7-flash-abliterated:q4_K > ollama launch opencode --model huihui_ai/glm-4.7-flash-abliterated:q4_K (3) have funshow more

There's a FREE public endpoint for deepseek v4 flash... 0731 😳 no account or no card needed, just a url victormustar from hugging face made it. openai-compatible chat completions. anyone can use it. what you get for $0: -82.7 terminal-bench (opus 4.8 is ~85) -swe-bench 54.4 — 7.3 before the update -1M context, thinking mode, tool calling -no signup, no key, no billing what this replaces: -Claude Opus 4.8: $15/M in, $75/M out -Cursor: $20/mo all for $0 how to set it up: 1. base url: 2. model: deepseek-ai/DeepSeek-V4-Flash-0731 3. api key: anything Works in Hermes, Cursor, OpenCode, Aider, Cline, Claude Code (via proxy), and any OpenAI tool Important: ~12 req/min per IP. shared box. be nice. use this before it gets popularshow more

DeepSeek R1 is *the* best model available right now.... It's at the level of o1, but you can use it for free, and it's much faster. A huge leap forward that nobody saw coming. No wonder so many people are throwing tantrums online trying to discredit the Chinese students who built this. You can use DeepSeek in Visual Studio Code right now: 1. Install the Qodo Gen AI extension 2. Select DeepSeek R1 from their list of models The Qodo team is hosting DeepSeek on their servers, so none of your data will go to China. I've been building a Tetris game using DeepSeek, and this is the most impressive model I've seen so far.show more

We can now run GPT-5.6 Luna Max over 5,000... extra times a week for only $10. A lot of us are out of Codex usage right now. So we wired Luna Max from OpenCode Go directly into our Codex Router!! It's the same Luna we already run in Codex, it just spends the $10 sub instead of our ChatGPT plan, and the reasoning level still works so we keep it on max. The caps are 5,100 Luna requests per week and 10,250 per month. Codex cuts us off, we've still got a full week of Luna sitting there. And we never leave Codex. just one more model in the picker, grab it when the wall hits and keep going.show more

if you use Codex and you're stuck on GPT... models only, this fixes that. it's called codex-router, open source. drops other models straight into your normal Codex picker, right next to the GPT ones you already have. what it adds: - Grok, Kimi, Deepseek, Claude, all in the same picker - oauth login per provider, no api key needed - your GPT models and Chatgpt login stay untouched setup: point Codex at the repo, let it read the readme, it installs itself one snag: if you've got the Chatgpt app and a separate Codex on your path, you can end up running two different Codex versions, and the older one can choke on newer config it doesn't recognize. if the install looks off after, that's probably why, reinstall clean.show more

herdr-projects v1 is out - rewritten from scratch as... a mission control for herdr 🐏 heads up: it's a breaking change. want the old version? it lives on in the legacy branch and the v0.2.35 tag. how v1 works: → talk to one coordinator - say what needs doing, it turns it into tasks on a board → press tab and a task gets a worker agent - claude, codex or pi (more coming) → each worker builds in its own worktree and branch, kept up to date with main → when it's done, your checks run and a second agent reviews it - fails go straight back to the worker → the board shows what needs you, what's ready to approve and what's still working → you can jump in to steer agents in herdr anytime → board is available on your phone via herdr-web-ui also in: automations (schedule and event based), best-of-n, time and token limits, fallback agents, and much more install: herdr plugin install eliasstravik/herdr-projects on 0.2? run the same install - your old projects are set aside in ~/.herdr-projects-legacy, never deleted repo: enjoy!show more

Codex can run Qwen-3.8-max now as well!! Alibaba most... capable model, dropped today and it's already in my codex picker. It's a token plan subscription, not metered api billing. You take the key from your Qwen plan, drop it into Codex Router, and it spends down the plan instead of your card. There's a catch though. Qwen's official setup switches your whole codex over to them, so your ChatGPT models stop showing up at all. That's exactly what Codex Router is for. It adds models to the list instead of replacing them, so sol, Grok, kimi, Deepseek and now Qwen 3.8 max all sit in the same picker and it can grab whichever one suits the job. Router's open source, setup's in the video 👇show more

I went a little overboard with Codex last week... and burned through my entire weekly allowance in two days. Luckily, my quota reset today. Otherwise, I’m not sure what I would’ve done. It got me thinking: instead of asking one large model to handle everything from start to finish, why not let a stronger model plan the project and review the work, while a model built for execution handles the day-to-day implementation? So I tried it. The result was better than I expected. I used GPT-5.6 Sol in Codex as the decision-maker, then ran Ling-3.0-flash from Ant Ling inside OpenCode as the execution engine. Together, they built a small 3D farming game. Before writing any code, I had Codex create four documents: SPEC.md defined the product scope and the lines we couldn’t cross. ARCHITECTURE.md laid out the isometric coordinate system, state machine, and module boundaries. TASKS.md broke the project into small jobs Ling could tackle one at a time. ACCEPTANCE.md explained how each step would be tested and what “done” actually meant. Then I gave Ling a very straightforward role: You are the execution model for this project. Read all four documents before you begin. Work only on the task assigned for this round. When you’re done, run typecheck, test, and build. If anything fails, read the error, fix it, and run the checks again. Do not move on to the next task early. Ling handled dependency installation, project structure, strict TypeScript configuration, test setup, and a production build in 6 minutes and 3 seconds. It ran into issues with the Vite test config, a TS6310 error, and a missing jsdom dependency along the way. Instead of stopping at the first error, it kept reading the logs and fixing the problems until all three checks passed. The speed was honestly hard to believe. If you exclude the time spent waiting on tools, it was producing more than 100 tokens per second. That made the whole development loop feel noticeably faster. After this experiment, I’m planning to keep using the same workflow. If the task is small, there’s no reason to call an expensive planning model for every single step. If the task is large, handing the entire project to a Flash model in one prompt isn’t a great idea either. The setup that makes more sense to me is: Use a more capable model such as Codex to explore the project, make architectural decisions, and break the work down. Put the constraints into specs, schemas, types, and tests instead of leaving them buried in chat history. Give Ling-3.0-flash a steady stream of clear, verifiable implementation tasks. Report bugs with structured context and actual error logs, rather than saying, “It still doesn’t work.” Bring Codex back in for architecture reviews, visual checks, and changes that affect multiple parts of the project. The point of this setup isn’t to give AI a big “build the whole project” button. It’s to turn software development into a pipeline with a much more sensible cost structure: Codex figures out the plan, sets the boundaries, and catches problems. Ling-3.0-flash moves quickly, calls tools reliably, and works through well-defined tasks at scale. For agent workflows that involve lots of repetitive edits, production tasks, and tool calls, this may be a more practical answer than simply using the biggest model for everything.show more

Big win for open-source LLMs! DeepSeek V4 Pro holds... the top open-weights score on SWE-bench Verified, in the GPT-5.5 range. GLM 5.2 leads the open-weight intelligence index and sits near the closed frontier on long-horizon coding. But this leaderboard number is a weak proxy for real performance. It comes from one task set, run through one harness, served at one precision. The same weights can even score differently across providers, since many hosts quantize activations to fp8 and drift the model off its reference weights. Real performance is determined based on whether a model can read a repo, make coordinated edits across files, run the tests, and recover when one breaks. By that measure, the top open models hold up, but only inside the right harness. The teams that actually put DeepSeek V4 into production pipelines as a frontier substitute got there through the harness they built around the model, not by picking a stronger model. If you want to see this in practice, Cline (64k+ stars) has actually built that harness around open models, tuned so they run at production quality. And it's tuned so that these LLMs can run at production quality, with plan and act modes, checkpoints, and terminal feedback. ClinePass is the new access layer on top of it. It runs a curated set of those models inside Cline, narrowed to the ones tested for coding-agent use, with 2 to 5x the standard rate limits and no separate provider accounts, keys, or billing to track. The video below shows the setup, and I worked with the team to put this together. It runs alongside custom keys and local models as well, not in place of them.show more