Three frontier models went live in one week — and the gap between the most expensive and the cheapest is now so thin on real work that picking wrong could cost you 50 times more than it should. Here’s which wins for which job, and the cost number almost nobody is talking about.
Short answer
- Fable 5 is still the smartest — roughly 7 points ahead on hard software engineering.
- Grok 4.6 jumped 5 points in a month and tied Fable on one independent blind test.
- DeepSeek V4 Pro is ~57x cheaper on output — and ~276x cheaper on the cache reads agents actually rack up.
- Nobody wins at everything: plan with Fable, run volume on DeepSeek, use Grok for live data.
Three frontier models, live at once
DeepSeek V4 Pro went full release on 12 August, quietly. No launch video, no countdown, not even a tweet — they updated their pricing page and let the model speak. Grok 4.6 dropped from xAI a day earlier. And Claude Fable 5 has been sitting at the top of nearly every leaderboard for months as the model everyone is chasing.
So there are three frontier-level brains on the market at the same time. One is the smartest, one is the cheapest, one is the fastest riser — and which you should use depends entirely on what you’re doing.
There’s also one number in this comparison almost nobody is talking about, and it isn’t the intelligence score.
Raw intelligence: Fable 5 is still king
That’s not really in dispute.
| Benchmark | Result |
|---|---|
| SWE-style software engineering | Fable leads DeepSeek V4 Pro by about 7 points |
| Full stack benchmark | Fable leads by about 6 |
| Humanity’s Last Exam (with tools) | Fable 63, DeepSeek 60 |
| Artificial Analysis intelligence index | Fable sits 1 point above Grok 4.6 |
When the work is genuinely hard — messy problems, deep reasoning, long complicated builds — Fable wins. Anthropic built the best brain and this week didn’t change that.
What’s changed is how close the other two got.
Grok 4.6 is the fastest riser
Grok 4.6 scored 61 on that same intelligence index — one point behind Fable, level with GPT 5.6 Sol.
Here’s the part that should make you sit up. One month ago Grok 4.5 scored 56. xAI jumped five full points in about a month, when most labs take three to six.
In one independent blind test suite, Grok 4.6 actually tied Fable 5 on overall score. And because it costs so much less to run, it took the number one spot on that cost-adjusted leaderboard. Grok 4.5 sat in 14th place on the same board a month earlier. Fourteenth to first, in one update.
Then DeepSeek. On Terminal Bench 2.1 — which tests how well a model works inside a computer and finishes real tasks — DeepSeek V4 Pro scored 87.9 against Fable’s 88.0. One tenth of one point. On Automation Bench, DeepSeek scored 31.8 against Fable’s 29.1, so DeepSeek actually won that one.
Hold those DeepSeek numbers loosely. They come from DeepSeek’s own testing, not independent testers. The pattern across everything they published points the same way, but wait for outside confirmation before treating the exact figures as settled.
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The number nobody is talking about: 276x
DeepSeek V4 Pro costs roughly 23 times less than Fable 5 on input and about 57 times less on output. Grok 4.6 sits in the middle, around half what other frontier models charge, with some testers finding it about a tenth of Claude’s cost on output.
But even that isn’t the number. The number is 276.
When an AI agent works on a task it doesn’t read your instructions once. It reads them again at every step. Picture a worker who opens the full job folder before every single action — open the folder, read everything, do one thing, open it again, read it again, do the next thing. That folder gets read hundreds of times.
When a model rereads something it’s already seen, that’s a cache hit. And cache reads on DeepSeek V4 Pro cost around 276 times less than cache reads on Fable 5. On OpenRouter, DeepSeek V4 Pro shows a cache hit rate of about 92%.
So the headline says 57 times cheaper, but for long-running agents — the exact work most people want AI doing — the real gap is bigger. That’s the number that matters if you run agents all day.
Proof that people are already on this: the number one app sending traffic to DeepSeek V4 Pro on OpenRouter right now is Hermes agent, with over 2 billion tokens. Hermes users quietly made DeepSeek the number one brain within days of release.
The harness problem
A model isn’t just a score. It’s something you have to actually use, and this is where the three split completely.
| Model | Its home | Verdict |
|---|---|---|
| Fable 5 | Claude Code, the desktop apps, Cowork | A full house built around the model — that polish is part of what you pay for |
| Grok 4.6 | Cursor, Grok Bot | Scattered. Cursor is coding-first, Grok Bot runs out of tokens fast — a frontier model without a finished wrapper |
| DeepSeek V4 Pro | None — it’s an API model | Bring your own harness |
DeepSeek having no consumer wrapper sounds like a weakness, and for most people it is. But if you already run an agent setup, it’s the opposite: your setup is the harness, and DeepSeek is just an extremely cheap brain you drop inside it. Same goes for Grok.
The harness problem only hurts people who don’t have their own system. For people who do, it disappears completely.
What each one uniquely does
Grok: real-time X, and it admits when it doesn’t know
Grok is wired directly into X. No plugins, no workarounds. If your business depends on knowing what people are talking about right now — trends, competitive research, what just dropped — Grok pulls that live. Fable can’t. DeepSeek can’t. It also generates images and turns them into video, which neither of the others do natively, and it runs at roughly 100 tokens per second.
But the thing that impressed me most was a trap test: ten problems to fix, five of them fake. Most models invent answers for the fake ones. Grok 4.6 caught them — said this doesn’t exist, and moved on. Making things up is the number one reason people stop trusting AI with real work, so a model that admits when something isn’t there is one you could actually leave alone with a job. Databricks found the same pattern on their office QA benchmark, where Grok set the top score on reading reports and pulling numbers out of messy files.
Fable: the hardest work
When a task is long, ambiguous and high stakes — planning a whole campaign, untangling a complicated client problem, designing a system from scratch — Fable 5 is still the one to trust. That seven-point lead isn’t a rounding error; on genuinely difficult multi-step work it shows up as fewer mistakes and fewer restarts.
DeepSeek: volume
It’s a mixture-of-experts model with 1.6 trillion total parameters but only 49 billion active at any time. Picture a company with 1.6 trillion employees where only the relevant 49 billion turn up for each task — that’s how it stays cheap. It’s engineered for it, not selling below cost to grab market share.
A 1 million token context window — roughly ten novels at once — and up to 384,000 tokens of output in one go. It’s built to grind through enormous amounts of work without complaint.
DeepSeek’s three catches
- It can’t see images. If your workflow depends on screenshots or reading documents as pictures, it’s out. DeepSeek have reportedly said vision doesn’t advance the research goals they care about, so don’t sit waiting for it.
- A significant price increase is coming. They’ve posted a notice across the whole API with no date and no amount. Today’s pricing is real but probably won’t stay. That said, they’d have to raise prices many times over before the value maths disappears — and they know that.
- Their terms let them train on what you send through the official API. Other providers host the model without that condition and OpenRouter says more are coming online, but on day one that’s a real trade-off. If your work is sensitive client data, factor it in.
The winner is a team, not a model
Nobody wins at everything, and that’s the most useful finding here. The pattern the smartest operators have landed on doesn’t pick one — it uses all three like a team.
| Role | Model | What it does |
|---|---|---|
| The planner | Fable 5 | Runs once. Designs the workflow, makes the hard decisions, reviews the final output. Top price, but only for the moments that deserve it |
| The workhorse | DeepSeek V4 Pro | Runs thousands of times. Research, drafting, sorting, monitoring, follow-ups — every repetitive high-volume task |
| The specialist | Grok 4.6 | Real-time market awareness through X, document and data work, image and video generation |
So: DeepSeek for your agents, Grok for marketing, Fable for designing systems. Plan with Fable, implement with DeepSeek.
And this contest isn’t settling. Elon says Grok 4.7 is a few weeks away. DeepSeek jumped their own SWE score from 12.8 in the April preview to 62.7 in this release — a 50-point leap. Anthropic will answer, because Anthropic always answers. Every round drives the cost of intelligence down further, which makes your agents cheaper to run whichever model you pick.
Want to run all three without rebuilding? The Agent OS in the AI Profit Boardroom lets you plug in Claude, Hermes and OpenClaw and swap the brain underneath without touching your workflows — so when a comparison like this shifts, you switch models in minutes. You get the install file, a 30-day roadmap, daily updates and four coaching calls a week to ask which model fits your exact workflow. Start free with the free AI course and community.
FAQ
Which is best: DeepSeek V4 Pro, Fable 5 or Grok 4.6?
Fable 5 for the hardest reasoning, DeepSeek V4 Pro for high-volume agent work at a fraction of the cost, Grok 4.6 for real-time data, office-style document work and media generation. Use all three.
How much cheaper is DeepSeek than Claude?
Roughly 23x less on input and 57x less on output — and around 276x less on cache reads, which is what actually matters for long-running agents.
What is the 276x figure about?
Agents reread their instructions at every step. Those rereads are cache hits, and DeepSeek’s cache reads cost about 276 times less than Fable 5’s, with a ~92% cache hit rate on OpenRouter.
Is Grok 4.6 really close to Fable 5?
On one independent blind test suite it tied Fable on overall score and took first place once cost was factored in — up from 14th a month earlier.
What can’t DeepSeek do?
It can’t see images, a significant price rise is coming, and its official API terms allow training on what you send. Use another host if that last one matters.
Why does Hermes matter in this comparison?
Hermes agent is the number one app sending traffic to DeepSeek V4 Pro on OpenRouter, with over 2 billion tokens — agent users found the cheap brain first.
Are the DeepSeek benchmarks trustworthy?
They’re DeepSeek’s own numbers, so treat them as claims until independent testers confirm. The direction is consistent across everything published.
What’s the practical setup?
Plan with Fable, implement with DeepSeek, and use Grok for anything needing live data or media. Run them behind one dashboard so switching is a dropdown, not a rebuild.
The bottom line
On DeepSeek V4 Pro vs Claude Fable 5 vs Grok 4.6, Fable is still the smartest, Grok 4.6 just proved xAI can reach the frontier in a single month with live data nobody else has, and DeepSeek V4 Pro made frontier-adjacent intelligence nearly free for the work most businesses actually need. Don’t pick one — plan with the expensive one and run everything else on the cheap one.
About Julian Goldie
I run Goldie Agency, a 7-figure SEO agency, and teach this daily on a 400K+ subscriber YouTube channel. 240+ client projects on Upwork at a 100% job-success score, 10+ years through every major Google update. My systems are in the AI Profit Boardroom; my link building book is free here.