Opus 5.5’s benchmark score rebounded; the latest run is 12 days old.
Call: mixed monitor movement, not evidence of a broad decline or deliberate nerf. BridgeBench’s 16 October results put all four published NerfBench series inside its 90–110% band. Claude Opus 5.5 rose 10.1 points from 95.7% on 9 October to 105.8% on 16 October. The composite includes correctness, output tokens, and cost; it does not establish what typical users experienced.
What the board shows
| Series | Latest displayed score | Visible date history |
|---|---|---|
| GPT-6 Astra | 97.1% | 16 October latest; six listed dates since 3 September. |
| GPT-6.1 Sol | 98.0% | 16 October latest; four listed dates since 1 October. |
| Claude Sonnet 5.5 | 98.9% | 16 October latest; four listed dates since 28 September. |
| Claude Opus 5.5 | 105.8% | 16 October latest; seven listed dates since 22 September. Score rose from 95.7% on 9 October. |
The BridgeBench results board says none of its four tracked series is outside the stated ±10% range. Its last displayed point is 12 days old on this review date. Its methodology says each tracked model is tested at least three times a week; the dates visible on the board do not show that cadence. The public record does not say whether this reflects unpublished sessions, incomplete sessions, or a change in testing. The board is not a real-time alert on 28 October.
What “power” counts
BridgeBench describes 50 private tasks, each run three times per session, for 150 attempts. The first session when tracking begins becomes the frozen 100% reference; the method does not show that this is the model’s actual release-day performance. Its headline combines 60% correctness, 20% output tokens, and 20% cost. A cheaper run can therefore raise the composite while task pass rate falls. Codex does not report cost, so the method reallocates weights to 75% correctness and 25% tokens. OpenRouter-reported cost is used for its API route, and Claude Code uses the CLI’s list-price figure.
The publisher says a result must be outside the 90–110% band in two complete, comparable sessions in a row before it publishes a confirmed movement. Its stated sampling illustration estimates about nine points of chance variation in either direction at 95% for a model with a 70% pass rate; it also says lower pass rates vary more. The public method does not show calibration for other baseline pass rates or dependence among repeat attempts on the same fixed tasks. The board publishes composite percentages, not individual correctness, token, or cost components, outputs, or session-completeness records, so outside readers cannot reproduce the displayed score.
What can be compared
The method locks provider, model, and effort within a series and stores fingerprints for the suite and prompts, adapter, provider/model, effort, runtime and CLI versions, output limit, timeout, concurrency, and retry limit. A changed profile is not compared with the old reference. However, the OpenRouter series uses default upstream routing and does not pin the upstream provider or temperature. The score is therefore a measurement of a selected served path, not an attribution to model weights alone. The overview describes a $10,000 pledge for future benchmarking; it does not report a verified expenditure.
Other changes are separate
| Record | What changed | What it does not show |
|---|---|---|
| OpenAI release notes, 26 October | GPT-6.1 Terra is rolling out in Work and Codex. Some eligible Plus and Pro Work users may see Terra at Medium instead of GPT-6.1 Sol at Light in default Power presets; plan usage limits are unchanged. | This is a product/model-path change, not a matched task-quality result. Account and workspace settings determine availability. |
| Anthropic status | The Gmail connector error window ended at 05:29 UTC on 28 October and was marked resolved at 05:48. The provider said other connectors were unaffected; the page showed all systems operational at 12:04 UTC. | A connector error explains a tool/request path, not the quality of completed answers. |
| OpenAI status | The status page showed all systems operational when checked at 12:04 UTC. | A green status snapshot does not establish the route or outcome of an individual request. |
Reader’s next check
If the request did not finish, save the error and timestamp and check the provider status record. If a task completed poorly, rerun a safe fixed task with the same prompt, product surface, model selection, effort, and context; save the final output and score correctness separately from tokens, price, and correction time. Treat the Opus score rebound as one narrow coding-suite signal, not a promise about every Opus conversation.
See the current evidence ledger · Read the comparison method · Return to the current answer