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ChatGPT & LLMs

Grok 4.6 Scores 61: How to Use It Today

Grok 4.6 scores 61 on the Artificial Analysis Intelligence Index. What the number means, how to access it, and practical ways to use the model right now.

6 min readBeginner

Most people saw “Grok 4.6 scores 61 on the Artificial Analysis Intelligence Index” and stopped at the leaderboard screenshot. The quieter detail: on long-horizon agent work it finishes tasks in roughly half the turns and a quarter of the input tokens of Claude Opus 5 max – while charging a fraction of the output price. That efficiency is what actually changes your bill.

I hit this right after another month of Opus-priced agent runs that chewed through budget on multi-file refactors. The score dropped August 12, 2026. HN lit up. I only cared about one question: can I get frontier-tier agentic behavior without the $5/$25-$30 token rates?

What a 61 on the Artificial Analysis Intelligence Index actually measures

Same ballpark as GPT-5.6 Sol max. Behind Claude Opus 5 max (63) and Claude Fable 5 max-with-fallback (62). Ahead of Kimi K3. That’s the ranking the Artificial Analysis write-up gives Grok 4.6 (high) at 61 – a 5-point jump over Grok 4.5’s 56, and +23 versus Grok 4.3. #6 of 184 models on their board.

It isn’t one quiz. AA’s methodology for Intelligence Index v4.1.1 weights Agents 34%, Coding 24%, Scientific Reasoning 24%, General 18%. Nine evals underneath: GDPval-AA v2, τ³-Banking, Terminal-Bench v2.1, SciCode, Humanity’s Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR.

Where the agent story shows up in the numbers:

  • GDPval-AA v2 Elo 1753 – behind only Opus 5; statistically tied with Fable 5 and Qwen3.8 Max
  • τ³-Banking 50.7% (multi-turn tool-using customer service)
  • Terminal-Bench v2.1 88.4%
  • AA-Briefcase Elo 1577, with ~53 turns and ~0.5B input tokens average versus ~103 turns / ~2.0B for Opus 5 max

Cost per Index task lands at $0.84. Short-context API sticker (as of August 2026): $2 input / $6 output per 1M – over 60% under Opus and Sol on output. Turns out xAI’s own launch post also cites CursorBench 3.2 at 69.9%, DeepSWE 1.1 at 65.9%, and FrontierCode Extended at 61.3%. Speed on AA sits around 67.6 tok/s (slower than average). Slightly chatty on the Index run: 72M output tokens vs a ~71M median.

Think of 61 less as “smarter than everyone” and more as “frontier enough that the cost curve becomes the product.”

Get Grok 4.6 running in under 10 minutes

Three doors – chat, IDE, or API.

  1. Consumer chat / Build – SuperGrok is $30/month and includes Grok 4.6 (higher tiers add usage and 1080p video). Free tier is thinner. Grok Build had a first-week 2× included-usage promo at launch; treat that as time-limited.
  2. Cursor – Live in desktop, web, iOS, CLI, and SDK. Same launch-week 2× usage boost on Grok 4.6. Pick it for chat, Composer, or agent runs.
  3. API – Key at console.x.ai. Model id: grok-4.6. Also on OpenRouter, Vercel, Cloudflare. OpenAI-compatible endpoints work with a base URL swap.
curl https://api.x.ai/v1/chat/completions 
 -H "Authorization: Bearer $XAI_API_KEY" 
 -H "Content-Type: application/json" 
 -d '{
 "model": "grok-4.6",
 "messages": [
 {"role": "user", "content": "Refactor this Flask app into a modular package with tests."}
 ]
 }'

Or with xAI’s Python SDK pattern: create a client, chat.create(model="grok-4.6"), append a user message, sample. Context window is 500k. Text + image in, text out. Knowledge cutoff is February 1, 2026 – enable server-side web_search / x_search when you need anything newer. Full rate card lives on the xAI pricing docs.

Pro tip: Set reasoning_effort on day one. Default is high. Options: low / medium / high / xhigh. Reasoning cannot be turned off. Leave the default while you “just try the model” and you’ll burn more reasoning tokens than people coming from lighter defaults expect.

Advanced usage that matches how it was trained

Long-running agents. Multi-step coding. Vague product idea → working first cut. That’s the training target. Prefer multi-turn trajectories over one-shot prompts.

Pattern that works in Cursor Composer or your own loop:

  • Concrete end state (“ship a working multi-sheet Excel model that pulls public metrics and leaves sticky notes for assumptions”).
  • Research unknowns → structure files → implement → self-test before “done.”
  • Visual/interactive work: demand a strong first pass of structure + visual language in one go, then iterate.

API agents: pair reasoning_effort: "high" or "xhigh" with tools (code_execution, web_search, collections). Low effort for latency-sensitive tool loops. Medium when you’re cost-sensitive but still want planning.

The catch is cache. Cached input is $0.50 per 1M on short context – up from $0.30 on Grok 4.5. Heavy coding sessions often spend most of the bill on cache read/write. Shape system prompts and repeated prefixes so they actually hit cache, or the 4.5→4.6 swap quietly costs more than the headline $2/$6 suggests.

Honest limitations before you switch everything

Dimension Grok 4.6 (high) note
Intelligence Index 61 (#6 / 184 on AA)
Short-context price (Aug 2026) $2 / $0.50 cache / $6 per 1M
Long-context (≥200k) $4 / $1 / $12 for the whole request
Speed ~67.6 tok/s – slower than average on AA
Verbosity on Index 72M output tokens vs ~71M median
Cutoff Feb 1, 2026 without search tools

Once a prompt crosses 200k tokens, every token in that request bills at the doubled long-context rate. Keep system prompts and retrieved context tight, or chunk on purpose. Tools (web_search, code_execution, and friends) also add per-1k-call fees on top of tokens – check the pricing page before leaving them always-on.

HN and r/singularity split the usual way: cost efficiency and agent turn-count get praise; some coders still prefer Fable/Opus for taste or peak coding feel.

Benchmarks aren’t destiny. Run your own eval suite on real tasks for a week before ripping other models out. Measure dollars per completed job, not sticker price – slight verbosity plus slower tokens still add up in chatty agent logs.

FAQ

Is Grok 4.6 better than Claude Opus 5 or GPT-5.6 Sol?

No on the Index – 61 ties Sol max and sits under Opus 5 (63) and Fable 5 (62). Yes often on $/task and agent turn-count. Pick by workload and budget.

How do I control cost on the API?

Picture a multi-hour coding agent holding a 50k system+repo prefix in cache. That prefix now prices at $0.50/M, not 4.5’s $0.30. Stay under 200k total prompt size so you never trip the $4/$12 long-context tier. Use medium or low reasoning for routine tool loops; save high/xhigh for hard planning.

Where should a beginner start this week?

Already on Cursor? Flip the model picker to Grok 4.6 and burn the temporary 2× usage on one real multi-file task. Chat-only? SuperGrok at $30/month is the low-friction door. API keys wait until you have a scripted agent that needs the same model outside an IDE.

People assume “set model name, done.” Wrong default will still bite you. Open Cursor or the xAI console, set grok-4.6, force reasoning_effort to the level you actually want, and rerun one multi-step job you paid Opus rates for last month. Compare turn count and dollar cost. That’s your benchmark.

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