Grok 4.7 vs Claude Opus 5.5: Benchmarks and Price Side by Side

Grok 4.7 landed on September 21, 2026. Claude Opus 5.5 followed a day later. One charges $2 per million input tokens and $6 per million output tokens. The other charges $4 and $20. A price page shows that gap in two seconds, but it can't tell you whether the extra spend buys better work on your tasks. This breakdown puts the vendor numbers, the independent runs from Vals AI and a public intelligence index, and both price sheets side by side, then turns them into plain cost math you can check yourself.

The Short Answer

Claude Opus 5.5 is the stronger model on most tests, and Grok 4.7 is much cheaper. In Vals AI's head to head, Opus 5.5 finished ahead on 20 of 22 shared benchmarks while Grok 4.7 led on 2. On the independent Intelligence Index (version 4.3.2), Opus 5.5 scores 58 and ranks first among 225 models. Grok 4.7 scores 46 and ranks 29th, which is still well above the median of 26 for comparable models.

Access differs too. Grok 4.7 is available through the Grok API, Cursor, and a free tier in Grok Build, but there is no free API tier. Opus 5.5 runs on the Claude API, Amazon Bedrock, Google Cloud, and Microsoft Foundry, with a knowledge cutoff of June 2026. Its thinking is adaptive and always on, with five effort levels: low, medium, high, xhigh, and max.

💡 Rule of thumb: Grok 4.7 reaches about 82% of Opus 5.5's Vals Index score (54.95 versus 66.97) for roughly a third to under half of the bill. If a wrong answer costs you an hour of cleanup, the Opus premium usually pays for itself. If you are summarizing, drafting, or tagging at volume, Grok is the smarter spend.

Price Per Million Tokens

Input and Output Rates

Both models bill by the token, and the sheets look similar until you read the output line.

Output is where the gap lives. Input costs 2x more on Opus 5.5, but output costs 3.3x more. Cached reads run the other way: Opus 5.5 charges $0.20 against Grok's $0.50, which makes it the cheaper pick for agents that keep re-reading the same long context.

Cache and Long Prompts

Grok 4.7's headline $2 and $6 only apply while your prompt stays at or under 200,000 tokens. Past that point, every rate doubles to $4 input, $1 cached, and $12 output. Since its context window is 500K, the cheap zone spans only the first 40% of it.

Opus 5.5 is priced 20% below Opus 5, with cache writes at $5 for five minutes or $8 for an hour. A fast mode preview exists on the Claude API at $8 input and $40 output. One trap: changing the effort level in the middle of a session invalidates the prompt cache, so cheap cache reads quietly become full-price input. Pick an effort level and hold it.

What a Real Workload Costs

List prices at three daily workloads, with no caching or batch discounts applied:

The more your workload leans on output, the wider the gap grows. Vals AI measured real runs rather than formulas. Running the Vals Index cost $32.14 on Opus 5.5 and $12.12 on Grok 4.7, about 2.7x. The Finance Agent test cost $9.22 versus $2.72. ProofBench was nearly even at $0.96 versus $0.79.

Verbosity won't rescue the Grok bill either. The independent Intelligence Index run recorded 240M output tokens from Grok 4.7, against a median of 81M for comparable models. Opus 5.5 produced 260M. Both talk a lot, so the per-token price difference passes almost straight through to your invoice.

Benchmarks Side by Side

Treat every number below with its source attached. Some scores are reported by the vendor, some come from independent runs, and the same model can land in very different places depending on who ran the test.

Coding and Terminal Work

Coding is where the two models separate most clearly.

Averaged across Vals AI's coding tests, Opus 5.5 scores 67.13% and Grok 4.7 scores 43.60%. The one close result is Vibe Code Bench, at 86.17% versus 90.29%. Grok 4.7 also posts 71.0% on DeepSWE v1.1 at high effort, a test where I found no Opus 5.5 figure. Opus 5.5 adds 54.4% on FrontierCode v1.1, 1.1 points ahead of GPT-6 Astra.

Reasoning and Knowledge Work

The reasoning gap is just as visible. On the Vals Index, Opus 5.5 scores 66.97% to Grok's 54.95%. ProofBench v1.1, which Vals AI files under math, is the most lopsided result on the board: 100% versus 26%. Science tests follow the same pattern, with Opus 5.5 averaging 58.65% and Grok 4.7 averaging 34.83%.

The Opus 5.5 launch tables add a few more results: 67.7% on Humanity's Last Exam with tools, an Elo of 1846 on GDPval-AA v2.1 for knowledge work, 81.8% on OSWorld 2.0 for computer use, and 89.0% on Chartography for chart reading. Grok 4.7's launch notes lean on different tests: 64.0% on EEBench for electrical engineering and 56.7% on HealthBench Professional.

Where Grok 4.7 Wins

Grok's two wins in the Vals AI comparison are specific:

• Harvey's Legal Agent: 12.50% for Grok 4.7 versus 3.75% for Opus 5.5. Both scores are low, so treat it as a lead on a very hard test.
• CyberBench v1.1: 69.46% versus 55.36%, a gap of 14 points.

Grok also edges the legal category average (29.81% against 27.12%), though Opus 5.5 wins Legal Research Bench 50.48% to 47.12%. Healthcare is nearly tied, at 70.61% for Opus and 69.47% for Grok.

Context, Speed, and Output Limits

500K Versus 1M Tokens

The independent Intelligence Index listing puts Grok 4.7's window at 500,000 tokens, roughly 750 pages of text. Grok's own launch documentation leaves the figure out, so check it against your provider before you build around it. Opus 5.5 offers 1 million tokens, roughly 1,500 pages, with up to 128K tokens of output per response. Batch jobs can stretch to 300K output tokens with a beta header.

Remember the Grok price doubling at 200K. A job that feeds 400K tokens of contracts into Grok lands in the higher tier, while no long prompt tier is listed for Opus 5.5.

Speed and Verbosity

On raw output speed, Opus 5.5 streams at 95.3 tokens per second and Grok 4.7 at 72.6, which sits below the 78.5 median for comparable models. Time to first token is a messier story. The same index lists Grok 4.7 at 73.9 seconds on its xhigh reasoning setting. Its figure for Opus 5.5 at max effort is 731 seconds, which looks like an outlier, so I wouldn't lean on it.

Wall-clock time on whole tasks went both ways in the Vals AI runs. Grok 4.7 finished the Vals Index in 35 minutes versus 1 hour 19 minutes for Opus, and the Finance Agent test in 15 minutes versus 33. Opus won ProofBench, 5 minutes 51 seconds against Grok's 12 minutes 47 seconds. Which model finishes first depends on the task.

Which One Fits Your Work

Pick Grok 4.7 When

• You process high volumes of text and the bill is the main constraint.
• Your prompts stay under 200K tokens, where the $2 and $6 rates hold.
• The work is legal agent tasks or security testing, where it posted its two wins.
• You can accept a lower ceiling on long agentic coding runs.

Pick Opus 5.5 When

• You run agents, terminal tasks, or code migrations where a failed step is expensive.
• You feed in long documents beyond 500K tokens, or you need image input.
• You rely on prompt caching, since cache reads cost $0.20 per million.
• You want the top Intelligence Index score and can budget for it.

Many teams will end up using both. Route bulk work such as tagging, first-draft summaries, and routine extraction to Grok 4.7, then escalate the hard cases to Opus 5.5: long agent runs, proofs, and migrations. A failed test or a low confidence score can trigger the handoff. On a back of the envelope basis, sending 75% of the Vals Index work to Grok and 25% to Opus would cost about $17 instead of $32.14.

💡 Check before you switch: Opus 5.5 rejects several settings older Claude integrations relied on. Disabling thinking returns a 400 error, forced tool use (tool_choice set to any or a named tool) returns errors, and the older computer_20251124 tool is rejected. Anthropic also re-routes most cybersecurity requests to Opus 4.8, so test security work directly instead of assuming.

Why Benchmarks Mislead

Look at Grok 4.7's Terminal-Bench 4.0 score. The vendor reports 38.0%. Vals AI measured 28.79%. The independent Intelligence Index run measured 26%. Same model, same benchmark name, a 12 point spread, depending on harness, effort setting, and who ran it.

Opus 5.5 has its own asterisks. Its default effort is medium, but headline scores come from xhigh or max effort, which cost more and run longer. The independent index also compares Opus at max effort against Grok at xhigh, so the two sit on different settings. Anthropic itself cautions that benchmark margins have become a less reliable predictor of real world differences at this capability level.

So run your own test. It takes an afternoon:

1. Pick 20 real prompts from your actual workload, not toy examples.
2. Run each on both models at the effort level you would use in production.
3. Record cost per task, retries, and wall-clock time.
4. Score outputs blind, without knowing which model wrote which.
5. Compute cost per accepted answer, not cost per token.

Try Similar Models on Picasso IA

Neither Grok 4.7 nor Claude Opus 5.5 appears in the Picasso IA catalog as of this writing. The nearest options are available today, and you can use them without API credentials or setup.

Models Available Now

Other options for a three way test include GPT 5.6 Sol, Gemini 3.1 Pro, and Kimi K2.6.

Use Claude Opus 4.7 on Picasso IA

1. Open the Claude Opus 4.7 page.
2. Type your question or paste your code into the Prompt field. It's the only required input.
3. Add a System Prompt if you want a fixed role, such as "You are a code reviewer".
4. Leave Max Tokens at 8,192 for long answers, or lower it for short replies.
5. Upload a screenshot or diagram if your question depends on it. Images are scaled to 0.5 megapixels by default to save time.
6. Run it, then keep refining in follow-up prompts.

Use Grok 4 on Picasso IA

1. Open the Grok 4 page.
2. Write your question in Prompt. Multi-step problems are where Grok 4 does best.
3. Keep Temperature at the 0.1 default for focused answers, or raise it for brainstorming.
4. Raise Max Tokens above the 2,048 default if answers get cut off.
5. Adjust Presence Penalty and Frequency Penalty only when the output starts repeating itself.

💡 Tip: Send the same prompt to both models and paste the replies side by side. Ten minutes of that tells you more than another benchmark table.

Create Your Own Images on Picasso IA

Let the Model Write Your Prompts

A strong language model is also a strong prompt writer. Ask Claude Opus 4.7 or Grok 4 to draft your image and video prompts, then paste the results into a generator:

Write five photorealistic image prompts for a blog post comparing two AI models. Each prompt needs a subject, a location, the lighting direction, a camera angle, and a lens. Keep every prompt under 70 words.

The structure matters: subject, setting, light, camera, lens. That order gives image models the details they need to produce sharp, natural results.

Image and Video Models to Try

For images, try Seedream 4.5, GPT Image 2, Flux 2 Pro, or Nano Banana Pro. For short clips, Seedance 2.0, Veo 3.1, and Kling v3 Video turn a prompt or a still image into motion.

Now it's your turn. Open Picasso IA, ask a language model for three prompts, and run them through an image model. Pick your favorite result, animate it with a video model, and compare how each model reads your instructions. The fastest way to know which model suits you is to put your own prompt in front of them.