Grok 4.7, the xAI model in numbers

Grok 4.7 at a glance

Grok 4.7 is a language model from xAI, released on September 21, 2026. It is a very recent release. Its weights are not published, so it only runs remotely, through the xAI API or partner hosts (29 listed on models.dev). It has a reasoning mode: it can "think" before answering, which helps with multi-step problems but uses more tokens, and therefore more money.

We file it under mid-range models (34 models in this category on the site).

Benchmark results

According to results published by Epoch AI (checked on October 22, 2026), Grok 4.7 has a capability index of 79.9 out of 100, computed on 5 benchmarks from our basket.

That puts it at #28 in our weekly model ranking.

• GPQA Diamond (PhD-level science questions): 92.7% — the best tracked model, Gemini 4 Argon, reaches 96.4%
• OTIS Mock AIME (competition mathematics problems): 98.1% — the best tracked model, GPT-5.5 Pro, reaches 100%
• FrontierMath (very hard research-level mathematics): 53% — the best tracked model, GPT-6 Astra, reaches 93.7%
• FrontierCode (advanced programming tasks): 47.6% — the best tracked model, Claude Opus 5.5, reaches 54.6%

What it costs

Grok 4.7 costs $2 per million input tokens and $6 per million output tokens (developer's price, checked on October 22, 2026).

In practice, an agent task that reads 20,000 tokens and writes 2,000 costs about $0.052, or $52 for 1,000 such tasks.

That is 1.4 times the median output price of mid-range models ($4.38).

Tokens read back from cache cost $0.50 per million, which helps an agent that keeps resending the same context.

To estimate your own budget, use the agent cost calculator.

What it can do

Its context window reaches 500,000 tokens, roughly 750 pages of text at 500 words per page: enough for a long report or several contracts at once. A single answer can run to 500,000 tokens.

It accepts as input: text, image and PDF. Its knowledge stops at May 2026: beyond that, it needs web search or your documents.

It can call tools (functions, APIs) and return structured JSON output, which makes it a possible foundation for an AI agent.

When to choose it

Given its category, Grok 4.7 is mainly aimed at a balance between quality and cost, for everyday uses that do not justify a frontier model.

Its FrontierCode result (47.6%, above the median of tracked models) makes it a serious candidate for coding agents.

Before adopting it, test it on your own examples: benchmarks measure standard tasks, not your job.

Alternatives

In the same category, the models closest to Grok 4.7 are:

• Mistral Large 4 (Mistral AI, index 79.7)
• Gemini 3 Flash Preview (Google DeepMind, index 80.3) — see the comparison
• Claude Sonnet 5 (Anthropic, index 79.3)
• Gemini 3.1 Pro Preview (Google DeepMind, index 79.3)