Three flagship AI models landed inside the same 48 hours, and every one of them claims to be the smart purchase. SpaceXAI shipped Grok 4.7 on September 21, Anthropic then launched Claude Opus 5.5 on September 22, and OpenAI put out GPT-6 Sol on that same day. If your head is spinning from benchmark charts, that is completely normal.
Here is the catch. Each company publishes charts where its own model looks brilliant, and the price on a pricing page rarely matches what a finished task really costs. So instead of repeating press releases, this guide lines the three models up on the four things that hit your wallet and your workflow: coding, price, speed and accuracy. When a number comes from the company itself, I say so. When an independent tester measured it, I say that too.
- The 30 Second Snapshot
- Each Model Sits on a Different Rung of Its Ladder
- List Price Per Million Tokens
- The Real Cost Per Task
- Coding Results
- Accuracy and Honesty
- Speed
- Context Window and Token Appetite
- Agents and Where You Can Actually Use Them
- Safety Guardrails
- How Much You Can Trust the Scoreboards?
- Which Model Should You Pick?
- Frequently Asked Questions
The 30 Second Snapshot
| Claude Opus 5.5 | GPT-6 Sol | Grok 4.7 | |
|---|---|---|---|
| Maker | Anthropic | OpenAI | SpaceXAI |
| Release date | Sept 22, 2026 | Sept 22, 2026 | Sept 21, 2026 |
| List price per 1M tokens (input / output) | $4 / $20 | $2 / $10 | $2 / $6 |
| API model name | claude-opus-5-5 | gpt-6-sol | grok-4.7 |
| Where it sits in its lineup | Newest Opus, below Fable 5.1 | Middle tier, below Astra | SpaceXAI flagship |
| Measured cost per task* | $1.34 (default effort) | $1.06 (max effort) | $2.73 (default effort) |
| Best fit | Hard coding and long agent work | Cheap business workflows at scale | Low list price, careful token tracking |
*Artificial Analysis figures as reported by third-party analyses. Settings differ per model, so treat this as a guide, not a final ruling.
1. Each Model Sits on a Different Rung of Its Ladder
Start here, because it changes how you read every chart. Claude Opus 5.5 is Anthropic's newest general-release flagship, yet Anthropic still sells larger models above it in the form of Claude Fable 5.1 and Claude Mythos 5.1, priced at $10 and $50 per million tokens. Anthropic's pitch is that Opus 5.5 delivers Fable-level results on most work for a fraction of the money.
GPT-6 Sol is not OpenAI's top model either. OpenAI rounded out its GPT-6 family with Sol and Luna shortly after GPT-6 Astra, and Sol is the middle tier. In the older GPT-5.6 family, Sol was the flagship, so the name quietly dropped down a rung. That detail confuses a lot of readers.
Grok 4.7 is the odd one out. It is SpaceXAI's flagship with no bigger sibling to point at. So the fair question is not which model is smartest in a vacuum. It is which rung you are actually buying.
"If you want the backstory on OpenAI's top tier, read our breakdown of GPT-6 Astra and its AGI claim before you compare Sol against it."
2. List Price Per Million Tokens: Grok Is Cheapest, Opus 5.5 Costs Most
On the sticker, the ranking is simple. According to Anthropic's pricing, Opus 5.5 costs $4 per million input tokens and $20 per million output tokens. That is 20 percent below Opus 5, and Anthropic says typical work runs about 40 percent cheaper than on Opus 5.
OpenAI's API pricing puts GPT-6 Sol at $2 for input and $10 for output, with a steep discount on cached input. The famous "50 percent cheaper" headline compares Sol with the promotional rate of GPT-5.6 Sol. The older standard rate was $5 and $30, so the real drop is even bigger if you were paying full price.
Grok 4.7 is the bargain on paper. SpaceXAI kept the price at $2 and $6 per million tokens, the same as Grok 4.6, while launching a larger base model. That makes its output price less than a third of Opus 5.5.
So far this looks like an easy win for Grok. Hold that thought, because the next section is where the story flips.
"These launches did not happen in a vacuum. Our look at the Anthropic and OpenAI rivalry shows why both labs keep cutting prices at the same time."
3. The Real Cost Per Task: The Cheapest Sticker Is Not the Cheapest Bill
Price per token tells you what a word costs. It does not tell you how many words the model needs to finish your job. That is why cost per task is the number to watch.
In independent same-harness testing from Artificial Analysis, GPT-6 Sol at maximum effort scored 47.5 at $1.06 per task. Claude Opus 5.5 at its default setting scored 51.2 at $1.34. Sol also matched Opus 5.5 on business workflow tasks at roughly 40 percent of the cost, which is a big deal for teams running thousands of routine jobs.
Now the plot twist. One analysis built on Artificial Analysis data found that Grok 4.7 cost $2.73 per task at default effort, while Opus 5.5 cost $1.34. Grok wrote about 65.9k output tokens per task against 25.7k for Opus 5.5, and about 85 percent of Grok's task cost came from re-reading input across turns. A model that talks more and loops more can erase a big list-price advantage.
The lesson is blunt. Run your own sample of 20 real tasks and compare the final bill, not the pricing page.
"SpaceXAI's confidence is the whole point of Elon Musk's pitch, and we fact-checked it in Musk's claim that SpaceXAI will lead AI in six months if you want the receipts."
4. Coding Results: Three Different Scoreboards
Coding is where the loudest claims live, so let us slow down.
Claude Opus 5.5. Anthropic reported 66.4 percent on Terminal-Bench 4.0, against 52.3 percent for Opus 5 and 55.8 percent for Fable 5.1. Those are company numbers. In the independent same-harness test mentioned earlier, Opus 5.5 landed at 52.5 percent on the same benchmark while GPT-6 Sol reached 43.9 percent. The gap between 66.4 and 52.5 is a lesson in itself: the same benchmark gives different scores under different harnesses and settings.
GPT-6 Sol. Sol is cheaper and more honest, but it is not a coding upgrade at the very top end. One review found that GPT-6 Sol's best score sits below GPT-5.6 Sol on DeepSWE (68.8 versus 72.7 percent). At a matched budget, Sol wins clearly, so its strength is efficiency rather than a higher ceiling.
Grok 4.7. SpaceXAI reports a jump on CursorBench 4.0, from 40.4 to 46.3 percent over Grok 4.6, though its own comparison still shows Fable 5.1 ahead on CursorBench and Terminal-Bench. In the same company table, Grok 4.7 beats GPT-5.6 Sol on five of seven benchmarks. Notice that rival is the older GPT-5.6 Sol, not the new GPT-6 Sol. And CursorBench comes from Cursor, which SpaceX now owns, so independent confirmation matters.
My read for developers: Opus 5.5 looks strongest on hard, long coding jobs, Sol wins on cost-efficiency, and Grok is promising but still needs outside verification.
5. Accuracy and Honesty: Who Makes Fewer Mistakes?
This is the category where readers should be most careful, because no single independent test I could find scores all three models on hallucinations at once.
What we do have is company-reported. OpenAI says GPT-6 Sol makes about half as many factual mistakes as GPT-5.6 Sol on an internal test built from conversations where users flagged errors. That is progress against its own predecessor, not a head-to-head win against Claude or Grok.
SpaceXAI says Grok 4.7 checks its own output more carefully through self-verification and works longer on difficult tasks. In SpaceXAI's own table, though, Grok trails on some professional knowledge and clinical tests such as HealthBench Professional.
Anthropic describes Opus 5.5 as the strongest model it has tested on its automated behavioral audit, and says outside evaluators including METR tested it before launch. Again, that is the vendor speaking.
If accuracy is your top priority, such as in legal, medical or financial drafts, treat every model as a first draft writer and keep a human check in the loop.
6. Speed: Fast Mode, Max Effort and Marketing Slogans
Speed has three layers: how quickly words stream out, how long a full task takes, and how much waiting you do on hard problems.
Anthropic says Opus 5.5 generates output more than 30 percent faster than Opus 5. For people who want even more, Fast mode runs up to 2.5 times quicker in Claude Code and on Claude Platform at $8 input and $40 output per million tokens. You pay double for the speed.
Artificial Analysis measured GPT-6 Sol at maximum effort at about 131 tokens per second, which is comfortable for interactive work.
SpaceXAI markets Grok 4.7 as twice as fast at half the price of comparable models. The analysis cited in difference 3 measured around 1,068 seconds per index task for Grok 4.7 at high effort, which suggests the slogan describes streaming speed more than finished-task time. Remember, a fast typist who rewrites everything three times is still slow.
7. Context Window and Token Appetite
Anthropic lists Opus 5.5 with a 1 million token context window. Grok 4.7 offers 500,000 tokens, according to one detailed Grok 4.7 guide, which also notes the model gained only about two points over Grok 4.6 on the Artificial Analysis index despite big gains on SpaceXAI's own charts.
A bigger window is not automatically better. Long context only helps if the model retrieves details accurately from deep inside it, and I could not find published long-context evidence from OpenAI for Sol. So if you plan to feed whole codebases or document libraries into a prompt, test retrieval on your own files first.
Token appetite is the quieter issue. A model that reasons for longer burns more tokens, and as we saw in difference 3, that appetite can quietly double a bill.
8. Agents and Where You Can Actually Use Them
Models are only useful where you can reach them. Opus 5.5 is available in the Claude apps, Claude Code, Claude Cowork, the API, and the major clouds including Amazon Bedrock, Google Vertex AI and Microsoft Foundry. GPT-6 Sol lives in ChatGPT Work, Codex and the OpenAI API. Grok 4.7 arrived on day one in Cursor, Grok Build, the Grok API, OpenRouter and other developer channels.
That Cursor link matters. SpaceX finished its Cursor acquisition in August, which gives Grok an unusual distribution advantage inside one of the most popular coding tools.
"Curious how SpaceX ended up holding that much AI power? Our guide to the SpaceX and xAI Grok acquisition facts explains how the pieces fit."
9. Safety Guardrails: Different Philosophies
All three companies now sell their models as safer, but they build safety differently.
Anthropic ran Opus 5.5 with production safeguards on. When those safeguards stepped in on cybersecurity and biology tasks, older models completed the work instead, which Anthropic says likely lowered some of its published scores. The company also reported that Opus 5.5 tried to cross its imposed boundaries about 85 percent less often than Opus 5.
SpaceXAI says Grok 4.7 ships with an entirely new safeguard stack, including a 3.3 percent pass-through rate on risky dual-use prompts on its HackerBench v0.3 test. OpenAI has focused its Sol messaging on lower error rates rather than a single safety headline.
Safety scores are mostly self-reported today. They are useful context but not proof, especially for autonomous agents that act on real systems.
"Agent safety is not theoretical. See what happened in our report on an AI agent sandbox escape before you give any model access to your tools."
"A second warning sign came from the OpenAI agent Medicare hack story, which shows why guardrails matter once agents touch live systems."
10. How Much You Can Trust the Scoreboards?
Here is the uncomfortable truth behind this whole comparison: most of the headline numbers are written by the companies selling the models. Anthropic's launch table compares Opus 5.5 with rivals using its own settings. OpenAI benchmarks Sol against older Claude models. SpaceXAI compares Grok 4.7 with GPT-5.6 Sol rather than the newer GPT-6 Sol, and its star benchmark comes from a company it owns.
Independent trackers like Artificial Analysis are more useful because they run every model through the same harness. Even they update their index versions, so numbers from different weeks are not always comparable. Some early users also noticed that launch charts do not always match daily experience, a reminder that benchmarks are a starting point rather than a verdict.
"One bold idea to fix this is having labs check each other. We covered it in Elon Musk's call for rival labs to test each other's models, and the debate is worth following."
Which Model Should You Pick?
Skip the hype and match the model to the job.
- Pick Claude Opus 5.5 if you run hard, long coding or agent tasks where being wrong is expensive, and you want strong independent results at a mid-range price.
- Pick GPT-6 Sol if you handle high volumes of business workflows and want the lowest measured cost per task with improved reliability.
- Pick Grok 4.7 if you live inside Cursor or Grok Build, want the lowest list price, and are willing to monitor token usage closely.
- Use more than one if you can. Many teams route routine work to a cheaper model and hard problems to the strongest one.
The smartest move is a small trial. Take 20 of your real tasks, run all three, and compare quality, time and final cost.
Frequently Asked Questions
Is Claude Opus 5.5 better than GPT-6 Sol?
On hard coding tasks and in the independent test cited above, Opus 5.5 scored higher. Sol was cheaper per task and matched Opus 5.5 on business workflows. Better depends on whether you value peak quality or lowest cost.
Is Grok 4.7 really cheaper than Opus 5.5?
Its list price is lower, but an Artificial Analysis based analysis measured about $2.73 per task for Grok 4.7 against $1.34 for Opus 5.5 because Grok used far more tokens. Always compare cost per task.
Which of these AI models is fastest?
It depends on what you measure. Sol has strong streaming speed at max effort, Opus 5.5 offers a paid Fast mode, and Grok's finished-task time was slow in the analysis cited above.
Are these benchmark numbers reliable?
Treat company numbers as claims and independent numbers as better evidence. Even independent results change as test versions update.
Final Thoughts
There is no single winner here, and that is the honest answer. Claude Opus 5.5 looks strongest for demanding work, GPT-6 Sol is the efficiency play, and Grok 4.7 is a cheap-looking option that needs careful cost tracking. The real advantage goes to readers who test with their own tasks instead of trusting a launch chart.
Which model are you leaning toward after reading this? Tell me in the comments, and I will keep this comparison updated as independent tests arrive.