#4 Claude Opus 4.7
none- Cost
- $0.051
- Time
- 24.2s
- Tokens
- 2,181 tok
Anthropic
Release: 2026-04-16
Tested on: 2026-04-16 15:59
anthropic/claude-opus-4.7::none
~5T total (~500B active)MoEClosedEstimated
(medium)
(none)
Summary
Claude Opus 4.7 scores 9.2 on AI BENCHY and ranks #4. It has N/A reliability, a 88.9% pass rate, $0.505 total cost, and 3.13s average response time.
What makes Claude Opus 4.7 unique: It stands out most in Domain specific, where it ranks #2, while Anti-AI Tricks is its weakest area at #12. It is one of the highest-ranked models overall. It is notably fast compared with similar models.
Archived model: this model is no longer updated or tested on new tests.
Model facts
Researched on 2026-08-12
- Parameters
- ~5T total (~500B active)
- Architecture
- MoE
- Availability
- Closed
- License
- -
Best estimate from public evidence; the vendor did not disclose every value. External industry estimate; vendor has not disclosed the architecture.
9.2
Consistency
10.0
N/A
$0.505
Total Output Tokens
6,326
Total Input Tokens
0
Input Price
$5.000 / 1M
Output Price
$25.000 / 1M
Flaky tests
0
Flaky tests had mixed outcomes across runs (at least one pass and one fail).
Hamster playing table tennis
Prompt: Create a detailed SVG illustration of a hamster playing table tennis.
Run history
| Tested on | Score | Reliability | Tests Correct | Total Cost | Compare |
|---|---|---|---|---|---|
| 2026-05-08 13:36 Re-test | 6.6 | 10.0 | $0.505 | Compare | |
| 2026-05-08 13:36 Re-test | 6.6 | 10.0 | $0.505 | Compare | |
| 2026-05-08 13:36 Re-test | 8.9 | 10.0 | $0.505 | Compare | |
| 2026-05-08 13:36 Re-test | 8.9 | 10.0 | $0.507 | Compare | |
| 2026-05-08 13:36 Suite changed | 8.9 | 10.0 | $0.507 | Compare | |
| 2026-04-16 15:59 First recorded run | 9.2 | N/A | $0.505 | Current run |
Run comparison
| Run | Benchmark coverage | Score | Consistency | Reliability | Tests Correct | Flaky tests | Total Output Tokens | Total Input Tokens | Total Cost | Response Time (avg) |
|---|---|---|---|---|---|---|---|---|---|---|
| 2026-04-16 15:59 · First recorded run | 54/54 attempts | 9.2 | 10.0 | N/A | 16/18 | 0 | 6,326 | 0 | $0.505 | 3.13s |
| 2026-05-08 13:36 · Re-test | 57/57 attempts | 8.9 | 10.0 | 10.0 | 16/19 | 0 | 6,265 | 69,576 | $0.505 | 3.02s |
| Difference | — | +0.3 | 0.0 | 0 | 0 | +61 | -69576 | +$0.001 | +107ms |
Benchmark coverage differs: 54/54 attempts (Target: 3 repeats per test) versus 57/57 attempts (Target: 3 repeats per test). Totals and repeat-sensitive metrics are not directly comparable.
These two runs used different benchmark suites, so the deltas reflect both model changes and suite changes.
Charts
Choose the first model, then click a second model to open a side-by-side page.
Top Models by Score
Score vs Total Cost
Response Time (avg)
Score vs Response Time (avg)
Total Output Tokens
Score vs Total Output Tokens
Category Breakdown
| Category | Score | Consistency | Tests Correct |
|---|---|---|---|
| Anti-AI Tricks | 8.3 | 10.0 | |
| Coding | 10.0 | 10.0 | |
| Combined | 9.5 | 10.0 | |
| Data parsing and extraction | 10.0 | 10.0 | |
| Domain specific | 7.7 | 10.0 | |
| General Intelligence | 10.0 | 10.0 | |
| Instructions following | 10.0 | 10.0 | |
| Puzzle Solving | 10.0 | 10.0 | |
| Tool Calling | 10.0 | 10.0 |