Codex users: do this right *now*. Max reasoning effort... is off by default. Luna at Max reasoning is ~ Sol Medium / Opus 5 Medium level at 1/6th the cost. Change your life today.show more

Opus 5.5 works best on 'low' reasoning effort. I... ran some tests as part of a project I'm working on. Opus 5.5 on 'low' reasoning vs. 'max' was at parity on task completion but 12x lower cost! Set 'low' reasoning effort by default and increase it for the hardest problems.show more

Gemini 3.6 Flash is now on DeepSWE at 49%,... roughly on par with Opus 4.8 at medium reasoning.show more

HERMES AGENT NOW RUNS CLAUDE OPUS 5. NEAR FABLE... 5 INTELLIGENCE. HALF THE PRICE. SELF-VERIFIES ITS OWN WORK. AVAILABLE TODAY VIA NOUS PORTAL (20% OFF ALL MODELS). Anthropic shipped Opus 5 on July 24, 2026. same $5/$25 per million tokens as Opus 4.8. but the benchmarks tell a different story. WHAT CHANGED FROM OPUS 4.8: FrontierBench v0.1: Opus 5: 43.3%. Opus 4.8: 18.7%. 2.3x jump on the same test. ARC-AGI-3: Opus 5: 30.2%. 3x better than the next closest model. beat Fable 5 on 8 out of 13 benchmarks. at half the cost ($5/$25 vs $10/$50). same price as Opus 4.8. twice the intelligence. no reason to stay on 4.8. THE SPECS: model ID: claude-opus-5 context: 1M tokens (default and maximum) max output: 128K tokens thinking: on by default effort toggle: low / medium / high per request fast mode: $10/$50, 2.5x faster knowledge cutoff: May 2026 minimum cacheable prompt: 512 tokens (was 1,024) SELF-VERIFICATION (the biggest change): Opus 5 checks its own work automatically. Anthropic says: delete your verification prompts. "include a final verification step" now causes OVER-verification because the model already does it. for Hermes /goal tasks this is a direct upgrade. the judge checks evidence. the model also checks evidence. double layer of verification without extra tokens. EFFORT TOGGLE: low: fast, cheap, routine work. medium: balanced, daily tasks. high: full reasoning, complex problems. set per request. not a global switch. matches Hermes /reasoning command: /reasoning low (routine) /reasoning high (complex) Opus 5 effort toggle + Hermes reasoning control = precise cost management per turn. WHERE OPUS 5 FITS IN HERMES: DAILY DRIVER (replaces Opus 4.8): same price. 2.3x better benchmarks. set as your main model: Desktop app / Dashboard: Models → claude-opus-5 CHIEF OF STAFF: synthesis across multiple agents. reads Kanban, prioritizes, routes tasks. self-verification catches routing errors before they cascade. COMPLEX CODING: SOTA on agentic coding benchmarks. FrontierBench 43.3% = best public model for coding. set as coder profile model. /GOAL TASKS: self-verification + completion contracts = the model proves its work AND double-checks the proof. long-horizon goals finish correctly more often. MoA AGGREGATOR: strongest synthesis model at $5/$25. pair with GPT-5.6 and Grok 4.5 as references. Opus 5 aggregates. best quality at mid-range price. presets: max-quality: reference_models: - provider: openai-codex model: gpt-5.6-sol - provider: xai model: grok-4.5 aggregator: provider: anthropic model: claude-opus-5 COMPUTER USE: near-Fable 5 quality for browser automation. at half the token cost per session. computer_use tasks burn lots of vision tokens. Opus 5 halves that bill vs Fable 5. WHAT TO KEEP OPUS 5 AWAY FROM: cron monitoring: too expensive. use DeepSeek or no_agent mode. sub-agent grunt work: use GPT-5.6 Luna ($1/$6) or DeepSeek. auxiliary tasks: use Gemini Flash. routine web extraction: use a cheap model. Opus 5 is for the turns where quality compounds. planning, synthesis, verification, complex reasoning. budget models handle everything else. NOUS PORTAL: 20% OFF ALL MODELS Nous Portal currently runs a 20% discount on all models including Opus 5. $5/$25 official → $4/$20 through Nous Portal. the cheapest way to run Opus 5 right now. hermes setup --portal select claude-opus-5 as your model. discount applies automatically. Opus 5 replaces Opus 4.8 everywhere. same price. better at everything. no tradeoff. straight upgrade. hermes update /model claude-opus-5show more

Rejoice. Just following up with another quick W in... Codex You can now configure your reasoning level in plan mode separately directly from your config file. This is huge for Plus users who want to plan with high or xhigh reasoning levels, and then switch over to medium reasoning for implementation, without needing the slash command. This is a great way to save your usage limits, and now it happens automatically. Even if you're on Pro, this should make you very happy. Prior to this, it was switching you automatically to medium every time you planned, which was pretty annoying. Place this near the top of your config file: plan_mode_reasoning = "high" (or xhigh) 0.150.0 is a massive quality of life update. They're clearly listening. This time I am shouting out Charlie. 🙏show more

GPT 5.6 Luna Max vs 5.6 Sol Medium… Yeah,... it’s not even a question 😭 Sol on MEDIUM produced a much better result than Luna on MAX—and needed only around HALF the time. Same harness. Better generation. Faster result. Luna may be cheaper, but if you have the budget, I would absolutely use Sol. Saving money is not worth it when the weaker output creates hours of extra work later.show more

Moonshot's Kimi K3 is free on NVIDIA right now... 😳 2.8T params, 1M context, multimodal (text + image). Max reasoning on by default. → → sign up → select Kimi K3 → start No card, no billing. Go grab it.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

The model is faster, the pelican isn't as good!... GPT-5.3 Codex Spark on the left, GPT-5.3 Codex 5.3 on the right - both at medium quality settingsshow more

GPT-5.5 by Reasoning Effort: I've asked it in Codex... to create a physics-based visualisation of RL cycles for different sized models (70b, 1t, 10t), to demonstrate how the amount of RL you can do differs by model size. My assessment of each: - Low: weird slop - Medium: kinda cooked - High: sort of tried but ultimately incoherent - Extra High: elite - really nice idea and well executed Obviously this is just one shot, but worth trying different reasoning levels for the new models, medium seems to be pretty good for GPT-5.5 and it was really bad for many previous GPT models.show more

Introducing Span-02: anytime reasoning for decisions. Reasoning models make... you pick an effort level and wait. Span-02 takes a deadline and always returns its best decision so far. It gets better the longer it thinks. With reasoning off, it beats Jev at 1/4 of the price, and runs at 1/3 the latency of decision models at its level. It can: - Answer with numbers and scores, not just probabilities and choices - See images and screens (multimodal) - Take a configurable reasoning time And it’s fully open weight!show more

ANTHROPIC JUST DROPPED THE OFFICIAL GUIDE TO PROMPTING OPUS... 5 This is the most important prompting guide for anyone using Claude. Bookmark this before you forget. Most people still prompt Opus 5 like older models. That's the mistake. > give the complete task upfront — don't drip-feed instructions. > explicitly ask for shorter responses if you want them. > use low/medium effort by default. increase effort only when needed. > let it finish the entire feature instead of asking for partial implementations. > use subagents intentionally for large codebases, not every task. Opus 5 is at its best when you stop micromanaging it and let it own the work. Read it before writing your next prompt. Claude → Opus 5 → Agentic Execution → Production-Ready Output → Moneyshow more

This is amazing. Do this: 1. Set model to... Opus 4.8 2. Reasoning effort to /ultracode Enables Claude Code's new Dynamic Workflows. Claude will autonomously detect complex tasks, write an orchestration script, and spawn an agent swarm.show more

codex robot build update: this is the result of... a ~12hr overnight task by gpt-6 astra on max reasoning; devil is in the details i plan to design thru weekend, then start making parts early next week peep the custom pcba for the canbus lighting controllers OpenAI Developers 👀show more

🐐 Gemini 3 Pro GA One shot prompt is... in comment with the codepen link I repeat no model in this entire world able to implement this level of physics and spatial reasoning Not even Opus 4.6 and Gpt-5.3 codex , this is like a generation gap Sub Woofer submitted thisshow more

Jev + Opus 5.5 is the most underrated setup... in AI right now, and i don't get why nobody's talking about it. I stopped letting Opus make every small decision in my agents. Jev makes them now. My Opus bill dropped ~500% on the same tasks, same results. Here's what Jev handles: - which files and notes to load before Opus sees anything - which effort level each task actually needs - what to do when a tool fails - which tests to run, and when to stop Opus only gets called for the hard reasoning. Every decision is a typed result the host checks before it runs. The exact prompt to set this up in your workflow is below.show more

A small codex workflow that does WONDER, at almost... no cost Ask GPT 5.6 Luna (Max) to use the ImageGen skill for a 3D low-poly object. Then to use the img2threejs skill. Tada. I didn't even spend 1% of my weekly tokens for this.show more

Kepa pushing Max Dowman to lift the trophy at... 16 is the best video right now 😂🏆”show more

DeepSeek V4 Flash being ranked almost equal to Opus... 4.8 is actually insane to me. Against Kimi K3, Opus 5, GPT-5.6 Sol, and Qwen 3.8 Max Preview, you give up a LOT by choosing DeepSeek. This is not a 2-point difference in practice. I’ll post the Opus 4.8 comparison next because you need to see this.show more

I bet you didn't know that by default Codex... only runs max 3 subagents concurrently. That's not ambitious enough for Astra. OpenAI tested Astra with up to 64 subagents. Copy this into your config.toml: [agents] max_concurrent_threads_per_session = 64 Astra orchestrating 64 Luna subagents in parallel is a sight to behold!show more

Claude Code's effort parameter is something you need to... keep in mind before starting any task It's not just about picking the right model anymore (Haiku, Sonnet, Opus). Now you also need to think about which effort level to use before each task. One tip I always go back to: when Opus can't solve a problem, just adding ultrathink makes things click, it's almost magic. We wrote a post at Hedgineer benchmarking each effort level by cost and time Read it here:show more