The 8 AI models worth knowing right now, what each is genuinely best at, the honest weakness of each, and what it costs. Plus the switch-between-models workflow that beats picking a favorite.
Everyone keeps asking me the same thing. Which AI model is the best one? I get why people want a single answer. But I think it is the wrong question to ask.
The better question is not which model is best. It is which model is best for this task. The people getting the most out of AI stopped picking a favorite. They switch between models based on the job in front of them, and once I saw the pattern I could not unsee it.
So here is the actual cheat sheet. The eight models worth knowing right now, what each one is genuinely good at, and the honest weakness of each. Save this one.
Scroll sideways on your phone to see the whole table. Cost is per million tokens, shown as input and output, which is how these are actually billed.
| Model | Reach for it when | Real weakness | Cost in / out |
|---|---|---|---|
| Claude Fable 5 | The hardest problem you have. Best coding scores of anything you can use right now. | Most expensive on this list. Overkill for everyday work. | $10 / $50 |
| Claude Opus 4.8 | Long jobs that run for hours. Big migrations, deep research, agents that hold context. Great natural writing. | Pricey, and slower than you want for quick questions. | $5 / $25 |
| Claude Sonnet 5 | Your daily driver. Plans, uses a browser and terminal, runs on its own. | Uses more tokens per task, so at max effort it can cost more than Opus. | $2 / $10 |
| GPT-5.6 Sol | Hard multi-step problems and coding that spans files, tests, and follow-up fixes. | Priciest of the GPT tiers, and you rarely need this ceiling. | $5 / $30 |
| GPT-5.6 Terra | The broad middle of real work. Support replies, document analysis, drafting at scale. | Not the top ceiling. Hard reasoning goes to Sol. | $2.50 / $15 |
| GPT-5.6 Luna | Summarizing, labeling, extracting, first drafts. One fifth the cost of Sol. | Long-document recall falls off a cliff. Do not hand it a huge file. | $1 / $6 |
| Gemini 3.5 Flash | Speed, and anything needing live Google Search grounding. | Gemini writing can read a little flat next to Claude. | $1.50 / $9 |
| Grok 4.3 | Breaking news and live X, plus video you want it to actually watch. | Trails the others on coding, and takes about 12 seconds to start answering. | $1.25 / $2.50 |
Prices checked July 2026. Sonnet 5's intro pricing rises about 50% on September 1, 2026.
If You Only Remember Four Things
Hardest problem you have: Claude Fable 5.
Everyday work: Claude Sonnet 5 or GPT-5.6 Terra.
Cheap and high volume: GPT-5.6 Luna or Gemini 3.5 Flash.
What happened in the last hour: Grok 4.3.
This is the one to screenshot. Find what you are actually doing, use the first pick, and fall back to the second if you do not have access to it.
| What you are doing | Use this | Or this | Why |
|---|---|---|---|
| Writing people will read blogs, newsletters, emails in your voice | Claude Opus 4.8 | Claude Sonnet 5 | Most natural prose, and it holds your tone over a long piece. |
| Short punchy copy hooks, subject lines, ads, captions | GPT-5.6 Terra | GPT-5.6 Sol | GPT is stronger at short business copy than long-form voice. |
| Hardest coding problem | Claude Fable 5 | Claude Opus 4.8 | Top coding score of any model you can use today. |
| Everyday coding and code review | Claude Sonnet 5 | GPT-5.6 Terra | Handles most real work without the flagship price. |
| Agents and terminal work | GPT-5.6 Sol | Claude Sonnet 5 | Sol genuinely leads on agentic and terminal operation. |
| A job that runs for hours migrations, deep research | Claude Opus 4.8 | Claude Fable 5 | Built to hold context across long autonomous work. |
| Work you will not double-check | Claude Opus 4.8 | Grok 4.3 | Both are unusually willing to say they are unsure instead of inventing an answer. |
| Research that must be current | Gemini 3.5 Flash | Grok 4.3 | Most reliable live Google Search grounding. |
| Breaking news, live sentiment | Grok 4.3 | Gemini 3.5 Flash | Reads X live rather than a stale index. |
| Big documents and spreadsheets | Gemini 3.5 Flash | Claude Opus 4.8 | Chews through large files fast without slowing down. |
| Video you want understood | Grok 4.3 | Gemini 3.5 Flash | Takes video directly, up to five minutes, and follows what happens. |
| Bulk simple tasks summaries, labeling, extracting | GPT-5.6 Luna | Gemini 3.5 Flash | Cheapest way to run volume. Just never on long documents. |
The table gets you moving. This part is the why, so you can make the call yourself when a new model shows up next month.
Claude Fable 5
Anthropic · the ceiling · $10 / $50
Good At
Not Good At
Buy it if: you hit a wall the other models cannot get past, and being right matters more than the cost.
Claude Opus 4.8
Anthropic · the long-haul worker · $5 / $25
Good At
Not Good At
Buy it if: you are writing something real, or running long jobs where a confident wrong answer would cost you.
Claude Sonnet 5
Anthropic · the daily default · $2 / $10
Good At
Not Good At
Buy it if: you want one model for most of your week and you do not want to think about it.
GPT-5.6 Sol
OpenAI · the flagship · $5 / $30
Good At
Not Good At
Buy it if: you need hard problems solved fast and you are going to review the output anyway.
GPT-5.6 Terra
OpenAI · the middle · $2.50 / $15
Good At
Not Good At
Buy it if: most of your work is business-as-usual and you want the best value per task.
GPT-5.6 Luna
OpenAI · the cheap one · $1 / $6
Good At
Not Good At
Buy it if: you have a pile of small boring tasks and you are paying too much to run them elsewhere.
Gemini 3.5 Flash
Google · the fast one · $1.50 / $9
Good At
Not Good At
Buy it if: you want speed and current information, or your whole team already lives in Google.
Grok 4.3
xAI · the live one · $1.25 / $2.50
Good At
Not Good At
Buy it if: you need live information, you work with video, or you want frontier-adjacent quality for a fraction of the price.
Worth Knowing: The Free Lane
There is a second tier of models you can download and run for free, and they are close behind. The strongest right now are mostly Chinese, like DeepSeek, Qwen, Kimi, and GLM, plus Meta's Llama. They are called open weight, not open source, because the company hands you the finished model but not the training data or recipe. Not as strong as the eight above, but genuinely capable and free.
The workflow I keep seeing has three steps, and you do not use one model for all of them. You hand each part of the job to the model that is best at that part. Think first, then execute, then review.
Step 1
Think
Start with your smartest model. This is the one you use to plan the strategy, break the problem into pieces, and map out the approach. You want deep reasoning here, not speed. Give it room to think before anything gets built. In my flow this is a strong reasoning model like Claude's Fable 5.
Step 2
Execute
Now switch to your fastest model. The hard thinking is done, so this part is about doing the work quickly. Building, writing, coding, churning through the plan you just made. You do not need your deepest thinker for this, you need speed. A quick model like GPT-5.6 Sol does the heavy lifting fast.
Step 3
Review
Here is the step most people skip. Take the finished work and hand it to a different model to look for mistakes. Not the one that built it. A fresh model reads it cold and catches what the others missed. This single step has saved me more times than I can count.
Every model has different strengths. Every model also has different blind spots. That is the whole point of switching.
When one model builds something, it tends to be blind to its own mistakes. It made the same assumptions on the way in and on the way out. Ask it to check its own work and it will often tell you it looks great, because it is reading the problem the same way it did the first time.
A second, different model does not carry those same blind spots. It reads the work cold, with no attachment to how it got made, so it notices the gaps the first one talked itself past. It is the same reason a friend catches the typo you read past ten times. Fresh eyes see what tired eyes cannot.
The One Rule
The reviewer has to be a different model than the one that did the work. Same model, same blind spots. If you send the work back to the model that built it, you are asking it to catch a mistake it was already blind to. Switch the model and you switch the point of view.
Here is how the eight above map onto real jobs. This is a starting point, not a rulebook.
One Honest Note
Do not get too attached to the exact names. These change every few months, and something on this list will be replaced before the year is out. What stays true is the shape: smartest to think, fastest to build, a different one to review, cheapest for the boring stuff. Learn the shape and you can slot new models into it without redoing your whole setup.
Here is how I explain it to people. AI models are like streaming services. Netflix, Hulu, all of them. If you only ever open one, you miss all the good stuff sitting on the others.
Nobody watches only Netflix and thinks they have seen everything worth watching. The good shows are spread across all of them. The skill is knowing which app to open for what you are in the mood for.
AI works the same way. The advantage is not owning the one perfect model. It is knowing which one to open for the job in front of you, and being able to switch in seconds.
The Takeaway
Stop hunting for the one best model. Start building a lineup. Your smartest model to think, your fastest to build, and a different one to review. That switch, from a favorite to a workflow, is what separates the people getting real work out of AI from the people still asking which one is best.
© 2026 Mariah Brunner. All rights reserved.