Grok 4.6 was fast.The context was expensive.

Grok 4.6 delivered a genuinely strong run, then stopped while it still had more than half of the hour available.

It produced a valid, self-contained artifact and answered 26 of 100 private questions exactly. The run was operationally clean: the agent stayed in one pinned session, the broker recorded no protocol errors, nine candidate packages were promoted successfully, and the selected candidate was finalized before the deadline.

But the result is still provisional. It is one autonomous run, not the three seeded runs required for an official estimate. The right interpretation is “best observed Grok 4.6 run so far,” not “repeatable Grok 4.6 average.”

The expensive part was not fresh prompting or output. $9.00 came from cached context reads.

OpenCode ran a long, highly active agent session. As the transcript accumulated code, tool results, validation output, and decisions, later model turns revisited the growing history. Grok’s automatic prompt cache reduced the price of that repeated prefix—but cached tokens are discounted, not free.

Reconstruction uses the OpenRouter catalog rates available on August 12, 2026: $2/M fresh input, $6/M output, and $0.50/M cached input. OpenRouter documents Grok cache reads at one-quarter of normal input price and automatic prompt caching. Sources: OpenRouter model catalog and prompt-caching documentation.

Caching helped substantially. Repricing those 18 million repeated tokens as ordinary $2/M input would put the same usage near $36.80. The cache saved roughly $27; it simply could not make an enormous repeated context free.

Grok did not rely on a language model alone. It built a hybrid completion system: explicit task-solving logic handled recognizable structures, while statistical copying and a small trained byte model covered uncertain cases.

The run was unusually compressed. Grok moved from inspection to a timeout-safe candidate quickly, completed its larger training pass with most of the hour still available, and then spent the final stretch widening and retesting its inference logic.

The session’s implementation volume was high: 137 recorded messages, 181 tool uses—including 95 edits—and 56 compute commands. That intensity helped produce a sophisticated artifact quickly. It also explains the growing transcript and the dominant cache-read bill.

Against the three-run Grok 4.5 result already on ARI Bench, Grok 4.6 was both stronger and cheaper in this observed run. The comparison is directional, not definitive: Grok 4.6 has one xhigh run, while Grok 4.5’s displayed number averages three high-effort seeds.