Grok 4.6 Matches GPT-5.6 Sol on Intelligence Index With Half the Context Turns

xAI's research team reportedly ran Grok 4.6 through an internal long-horizon coding challenge before the public release — a multi-stage task involving generating a new module, writing tests, catching its own errors, and iterating to a working result. The model completed it in 53 turns. A comparable run on a competing frontier model took 103 turns and consumed roughly four times as many input tokens. That turn-efficiency gap is the primary engineering story of the August 12, 2026 release: Grok 4.6 doesn't necessarily win on raw benchmark scores at the frontier, but it's built to finish long agentic jobs with less overhead.

Vitals

• Model ID: grok-4.6
• Context window: 500,000 tokens
• Reasoning levels: low, medium, high (default), xhigh (new)
• Modalities: Text + image input; text output
• Knowledge cutoff: February 1, 2026
• Standard pricing: $2.00 input / $6.00 output per 1M tokens (under 200K tokens); $4.00 / $12.00 per 1M (200K+ tokens)
• Priority processing: service_tier flag available at double the standard rate
• Availability: xAI API, Cursor, Grok Build, GitHub Copilot; released August 12, 2026

Benchmark breakdown

Intelligence index: On the Artificial Analysis Intelligence Index — a composite of coding, reasoning, and knowledge tasks evaluated by third parties — Grok 4.6 scored 61, tying [GPT-5.6 Sol](/models/gpt-5-6-sol) and placing just below Claude Opus 5 (63) and Claude Fable 5 (62). The score puts it unambiguously at the frontier for the first time in the Grok 4.x line. (Source: Artificial Analysis, independent third-party.)

Agentic coding: On Terminal-Bench 2.1, which tests models running real shell sessions to complete coding tasks autonomously, Grok 4.6 scored 88.4% — consistent with leading models in this class. On GDPval-AA v2, which uses economic value as a proxy for task completion quality on real-world professional tasks, it reached an Elo of 1,753, ranking just behind Claude Opus 5 with overlapping confidence intervals. (Sources: xAI blog, Artificial Analysis.)

Turn efficiency: The standout differentiator in xAI's own reporting is agentic turn efficiency. On long-horizon tasks, Grok 4.6 averaged ~53 turns and ~0.5B input tokens to reach task completion. The closest competitors ranged from 90–103 turns and 1.5–2.0B input tokens for equivalent tasks. At $2/$6 per million tokens, that 4× input reduction is material for production agentic deployments running many parallel sessions.

Knowledge work: On τ³-Banking, a benchmark evaluating complex financial analysis and regulatory knowledge tasks, Grok 4.6 scored 50.7%, ranking among the top models. This is consistent with xAI's stated focus on knowledge-intensive work alongside code.

What's new in 4.6

The xhigh reasoning level is the most significant new surface. Below it, high is the default for most API calls; xhigh triggers a longer internal chain-of-thought pass, similar in concept to the effort dial in Claude Opus 5 or the thinking levels in Gemini 3.7 Flash. xAI notes xhigh shows the largest gains on knowledge work and legal reasoning tasks rather than pure coding, suggesting the extended thinking budget is helping with ambiguous, open-ended tasks more than structured code generation.

The self-verification capability is harder to quantify but appears in the agentic efficiency data. Grok 4.6 reportedly checks its own outputs before proceeding at each stage of a multi-step workflow, catching common classes of errors that previously required a round-trip to the caller. This is distinct from chain-of-thought reasoning — it's a behavioral pattern trained into the model's agentic trajectories during its reinforcement learning stage.

Try it yourself

Illustrative prompts based on Grok 4.6's reported agentic strengths.

• Try a long-horizon coding task via the xAI API with reasoning_level: "high": "You have access to this repository. Add a complete rate-limiting middleware layer to all authenticated API routes, with configurable limits per role. Include unit tests covering limit enforcement, bypass attempts, and header injection."
• For knowledge-work tasks where xhigh should help: "Summarize the current regulatory exposure for a mid-size US bank under Basel IV and DOGE-era OCC guidance changes, identifying the three highest-priority compliance gaps and suggested remediation timelines."

What this means for the agentic market

Grok 4.6 is the clearest signal yet that xAI is competing for the same enterprise agentic workload that Microsoft MAI-Cyber-1-Flash and Google's Gemini Managed Agents are targeting. The distinction is delivery mechanism: Grok 4.6 is a raw API play with Cursor integration, not a platform play. It's designed for developers building their own agent orchestration, not for buying into a managed agent runtime. At $2/$6 per million tokens and the turn-efficiency advantage, the economics favor high-volume production deployments where turn count directly maps to cost.

The AA Index score of 61 — matching [GPT-5.6 Sol](/models/gpt-5-6-sol) — represents the most competitive benchmark position the Grok line has held against the top two closed frontier models. Whether the efficiency advantage holds up under real-world diversity of tasks will be the key question as developers run it through production workloads over the coming weeks.