Grok 4.6 vs Gemini 3.1 Pro

Grok 4.6 vs Gemini 3.1 Pro: Quick Verdict

Grok 4.6 is the stronger default for agentic coding, research and professional knowledge work. Gemini 3.1 Pro is better for long-context and multimodal workloads involving large documents, audio or video.

As of August 2026, Artificial Analysis scores Grok 4.6 High at 61 and Gemini 3.1 Pro Preview at 48 on its current Intelligence Index. Grok also has substantial leads on shared professional-agent benchmarks including APEX-Agents and GDPval-AA.

Gemini fights back in areas that the aggregate score does not capture well. It supports a 1,048,576-token context window, compared with Grok's 500K, accepts text, images, audio, video and PDFs, and currently generates tokens considerably faster in Artificial Analysis' first-party API measurements.

Pricing also favors Grok for output-heavy workloads. Both models charge $2 per million input tokens below 200K context, but Grok charges $6 per million output tokens compared with Gemini's $12.

Grok 4.6 vs Gemini 3.1 Pro at a Glance

Grok's specifications come from SpaceXAI's current API documentation, while Google's Gemini API lists Gemini 3.1 Pro Preview with text, image, audio, video and PDF inputs, a 1,048,576-token input limit and a 65,536-token output limit.

Benchmark Comparison

The headline benchmark currently favors Grok.

Artificial Analysis' current Intelligence Index gives:

*The HLE figures come from different published evaluation sources, so they should not be treated as a perfectly controlled head-to-head experiment.

The biggest differences appear on agentic and professional work.

APEX-Agents tests long-horizon professional tasks. Grok 4.6 scores 57.5% versus Gemini 3.1 Pro's 33.5%. On GDPval-AA, which evaluates economically valuable expert work, Grok reaches 1753 Elo versus Gemini's 1317.

Gemini remains extremely capable on traditional reasoning benchmarks. Google reports 77.1% on ARC-AGI-2, 94.3% on GPQA Diamond, 44.4% on Humanity's Last Exam without tools and 51.4% with search and code.

Benchmark winner: Grok 4.6

The current evidence favors Grok overall, particularly when evaluations involve extended agentic work rather than isolated reasoning questions.

Grok 4.6 vs Gemini 3.1 Pro for Coding

Both models are built for serious software engineering.

SpaceXAI trained Grok 4.6 across agentic coding environments including general software engineering, web development, kernel optimization and other technical tasks. It also received longer training trajectories intended to improve persistence, self-testing and verification across multi-step work.

Grok's published results include:

Gemini 3.1 Pro also has a strong software-engineering record. Google's model card reports 80.6% on SWE-bench Verified, 54.2% on SWE-bench Pro, 68.5% on Terminal-Bench 2.0 and 2887 Elo on LiveCodeBench Pro.

Those numbers should not be placed into one winner-takes-all table without qualification because several benchmarks, harnesses and versions differ.

The more useful distinction is workload.

Grok 4.6 is better suited to:

Gemini 3.1 Pro is better suited to:

Google specifically describes Gemini 3.1 Pro as optimized for software-engineering behavior, reliable tool usage and multi-step execution, while Cursor highlights its 1M context and visual-code capabilities for UI and frontend work.

Coding verdict: Grok 4.6 for agents, Gemini for massive multimodal codebases

There is not enough clean shared benchmark evidence to declare one model universally better at every kind of coding.

For autonomous coding agents, Grok has the stronger current case.

For large-context and visually grounded development, Gemini has advantages Grok cannot match.

AI Agents and Knowledge Work

This is Grok 4.6's strongest category.

SpaceXAI says Grok 4.6 was specifically developed to remain effective across long sequences of actions such as researching unfamiliar topics, analyzing information, modifying codebases and building complete applications. Its training included reinforcement learning across knowledge work and agentic environments.

The benchmark results support that focus.

APEX-Agents

GDPval-AA

These benchmarks are especially useful because they move beyond answering isolated questions and test whether a model can complete longer professional tasks.

That makes Grok attractive for:

Gemini is not weak at agents. Google reports 69.2% on MCP Atlas, 85.9% on BrowseComp and major improvements over Gemini 3 Pro on APEX-Agents.

The difference is that Grok 4.6 currently performs substantially better on some of the most directly comparable professional-agent evaluations.

Agent winner: Grok 4.6

Reasoning and Research

Pure reasoning gives Gemini a stronger argument than its current aggregate score might suggest.

Google reports Gemini 3.1 Pro at:

Grok remains formidable. Artificial Analysis currently records a 94.9% GPQA Diamond result and gives Grok the much higher overall Intelligence Index score of 61.

For research, the model itself is only half the story.

Grok has first-party access to both web search and X search, which gives it a useful advantage for research involving live social conversations, breaking topics and information circulating on X.

Gemini provides Google Search grounding, URL context, file search, code execution and Google Maps grounding, making its surrounding research toolset unusually broad.

Research verdict

Context Window: 500K vs 1M

Gemini wins this category decisively.

Gemini can process roughly twice as much context in a single request.

That becomes useful for:

Google's model card explicitly describes Gemini 3.1 Pro as capable of processing large multimodal information sources including entire code repositories.

A larger context window does not automatically guarantee better reasoning over every token, but it removes a practical constraint when the workload genuinely exceeds Grok's 500K limit.

Context winner: Gemini 3.1 Pro

Pricing and Real API Cost

Below 200K prompt tokens, both models charge the same amount for input:

$2 per million tokens.

Output is where they separate.

Below 200K tokens

For a workload using 10 million input tokens and 2 million output tokens:

Grok is about 27% cheaper in that example.

Above 200K prompt tokens

Both providers increase their rates.

Grok therefore retains its output-price advantage even with long prompts.

But price per token does not tell the whole story

Artificial Analysis currently reports something counterintuitive.

During its Intelligence Index evaluation:

Gemini also produced 56 million output tokens compared with Grok's 72 million across that evaluation.

That does not prove Gemini is cheaper for equivalent production work. Grok achieved a significantly higher Intelligence Index score, and evaluation cost is not the same thing as cost per successful business task.

It does prove one useful point:

Lower token prices do not automatically mean a lower final bill.

Reasoning length, caching, number of attempts and task-success rate all matter.

Pricing winner: Grok on list price

For output-heavy production workloads, Grok's pricing is clearly more attractive.

Speed: Gemini Is Faster

This is one area where the current independent data may surprise people.

Artificial Analysis measures:

Gemini generates output about 72% faster in those first-party measurements.

Time to first token is also slightly better:

Google Vertex is even faster in Artificial Analysis' provider testing, reaching about 126.9 tokens per second, compared with 113.3 through AI Studio.

Latency can change substantially depending on provider, reasoning effort, prompt size and traffic, so these numbers should be treated as current measurements rather than permanent properties.

Speed winner: Gemini 3.1 Pro

Multimodal Capabilities: Gemini Has a Major Advantage

Grok 4.6 accepts:

Gemini 3.1 Pro accepts:

This is not a small difference.

Gemini can directly support workflows such as:

Google positions Gemini 3.1 Pro specifically around advanced reasoning across multimodal information, including text, audio, images, video and entire code repositories.

Multimodal winner: Gemini 3.1 Pro

Web Search, X Search and Tools

Both models offer serious tool-use capabilities, but their ecosystems differ.

Grok 4.6 tools

SpaceXAI lists:

Native X search is Grok's unique advantage.

It is useful for:

Gemini 3.1 Pro tools

Google lists support for:

Google also provides a separate gemini-3.1-pro-preview-customtools endpoint designed specifically for agentic workflows using custom tools and bash.

Tools verdict

Where Grok 4.6 Wins

Agentic performance.

Grok leads by a wide margin on APEX-Agents and GDPval-AA in the shared published results.

Current overall intelligence score.

Artificial Analysis gives Grok 61 versus Gemini 48 on its current Intelligence Index.

Output pricing.

Grok costs $6/M output below 200K context versus $12/M for Gemini.

Long-running agents.

Grok 4.6 was explicitly trained for longer trajectories, self-testing and multi-step work.

X search.

Native X search is built into SpaceXAI's tool stack.

Professional knowledge work.

Its GDPval-AA and APEX-Agents results give it a strong case for business-oriented agent workflows.

Where Gemini 3.1 Pro Wins

1M context window.

Gemini supports more than twice as much context as Grok.

Generation speed.

Artificial Analysis currently measures 113.3 tok/s for Gemini versus 65.8 for Grok.

Video and audio.

Gemini natively accepts both, while Grok 4.6 does not.

Multimodal workflows.

Gemini can reason across documents, images, video and audio inside the same model family.

Large repository analysis.

The 1M-token context makes Gemini better suited to repositories that cannot fit comfortably inside Grok's 500K window.

Google ecosystem.

Gemini is available through the Gemini API, AI Studio, Vertex AI, Gemini Enterprise, Gemini CLI, Antigravity, Android Studio, the Gemini app and NotebookLM.

Which Should You Choose?

Choose Grok 4.6 if:

Your workload mainly consists of coding agents, research agents, business automation or other multi-step tasks and you want stronger current agentic performance with lower output-token pricing.

Choose Gemini 3.1 Pro if:

You need to process extremely large contexts or combine text with images, video, audio and PDFs. Its 1M context window and broader input support make it considerably more flexible for multimodal applications.

Final Verdict

Grok 4.6 wins the overall Grok 4.6 vs Gemini 3.1 Pro comparison for agentic and professional workloads, while Gemini 3.1 Pro is the stronger multimodal and long-context model.

The strongest argument for Grok is not simply its newer release date.

Its current performance on professional-agent benchmarks is materially stronger. Grok scores 57.5% versus 33.5% on APEX-Agents and 1753 versus 1317 Elo on GDPval-AA. Artificial Analysis also currently gives Grok a 61 Intelligence Index score compared with 48 for Gemini.

Grok also offers better headline economics for output-heavy workloads. Both models start at $2 per million input tokens, but Grok charges $6 per million output tokens versus Gemini's $12 for requests below 200K tokens.

But Gemini has several advantages that cannot be dismissed by a leaderboard score.

Its 1M context window is more than twice Grok's 500K, and it accepts audio, video and PDFs in addition to text and images. Gemini is also substantially faster in current Artificial Analysis first-party API measurements, reaching about 113.3 tokens per second versus Grok's 65.8.

So the useful verdict is:

The winner depends less on which company has the larger benchmark number and more on whether your workload is fundamentally agentic or multimodal.