Gemini 3.1 Pro and Grok 4 are two of the most capable non-OpenAI, non-Anthropic models in 2026 — and they match up closely. Both offer 2M token context windows. Gemini 3.1 Pro edges Grok on research benchmarks (ARC-AGI-2: 77.1%) and is tightly integrated with Google Workspace. Grok 4 counters with real-time X/Twitter data access and identical pricing at $2/1M input. For research and Google ecosystem users, Gemini wins. For real-time data and X integration, Grok has no rival.
GooglePremium
Gemini 3.1 Pro
Best for research and deep document analysis — 2M context at the best premium price.
Winner
VS
xAIBalanced
Grok 4
Strong coding value with 2M context — an underrated pick at this price.
At a glance
Gemini 3.1 Pro
Grok 4
Input cost / 1M tokens
$$2.00/1M
$$2.00/1M
Output cost / 1M tokens
$$12.00/1M
$$6.00/1M
Context window
2M tokens
2M tokens
Speed
Balanced
Fast
Price tier
Premium
Balanced
Benchmarks
SWE-bench (coding)
80.6%
54%
Arena Elo
1,380
1,305
MMLU
90%
87.5%
How they compare
Which model wins for each use case — and why.
ResearchGemini 3.1 Pro wins
Gemini 3.1 Pro leads reasoning benchmarks including ARC-AGI-2 at 77.1% and integrates natively with Google Search for deep research tasks.
Real-time DataGrok 4 wins
Grok 4 has exclusive access to real-time X/Twitter data — no other model can match this for social media analysis, trending topics, and current events.
Context WindowTie
Both Gemini 3.1 Pro and Grok 4 offer 2M token context windows — the largest available among frontier models. Neither has an advantage here.
CodingGemini 3.1 Pro wins
Gemini 3.1 Pro edges Grok 4 on coding benchmarks and has better integration with Google's developer tools and Vertex AI.
PriceTie
Both models are priced identically at $2/1M input. Gemini's output is $12/1M vs Grok's $6/1M — Grok is cheaper on output tokens.
Which should you pick?
Pick Gemini 3.1 Pro if…
You use Google Workspace, Docs, or Gmail and want native AI integration
Research quality and benchmark performance are your priority
You're already on Google Cloud or Vertex AI
You want the strongest model for document analysis and synthesis
For most workflows, Gemini 3.1 Pro is the stronger choice.
The best research and long-context model available. Handles entire codebases, legal documents, and large datasets in a single pass — at a lower price than GPT-5.4 or Claude Sonnet 4.6.
The case for each model
What each one is genuinely good at, where it falls down, and when we would steer you away from it.
Our overall pick in this comparison. Against Grok 4 it costs about 43% more per token.
Google's flagship with the largest context window of any frontier model at 2M tokens, Deep Think reasoning, and the best price-to-performance among premium models.
Input
$2.00/1M
Output
$12.00/1M
Context
2M tokens
Speed
Balanced
What people actually use it for
Analyzing entire contracts, codebases, or research corpora in a single 2M-token prompt
Due diligence synthesis across large sets of financial documents or legal agreements
Multi-step reasoning across dense technical specifications with Deep Think mode
Where it wins
2M token context window — the largest of any frontier model
Leads ARC-AGI-2 reasoning benchmark at 77.1%
Best price-to-performance among premium models at $2/$12 per 1M tokens
Where it falls down
Slower than Flash for everyday lightweight tasks
Claude Sonnet 4.6 is better for writing quality
Skip it if
Your primary use case is writing quality or agentic coding — Claude wins both.
Our verdict
The best research and long-context model available. Handles entire codebases, legal documents, and large datasets in a single pass — at a lower price than GPT-5.4 or Claude Sonnet 4.6.
The runner-up here, but not by a wide margin. Against Gemini 3.1 Pro it costs about 43% less per token and answers faster.
xAI's latest flagship with strong coding benchmark performance, a 2M token context window, and aggressive pricing at $2/$6 per million tokens.
Input
$2.00/1M
Output
$6.00/1M
Context
2M tokens
Speed
Fast
What people actually use it for
Early-stage research mapping — exploring a new topic before narrowing down
Analyzing large codebases or datasets within a 2M-token context window
Competitive intelligence and market research with broad, fast synthesis
Where it wins
75% SWE-bench score — strong coding performance close to top Claude models
2M token context window at $2/$6 per million tokens
Fast and responsive for exploration and open-ended research loops
Where it falls down
Claude Opus 4.6 and Sonnet 4.6 lead on pure coding benchmarks
Less established ecosystem and tooling than OpenAI or Anthropic
Skip it if
You need the highest writing quality or the most reliable production-grade output — Claude wins both.
Our verdict
Strong coding benchmark with excellent value. The $2/$6 pricing and 2M context make it competitive with more expensive alternatives.
Full pricing, benchmark table and release notes on the Grok 4 page.
Frequently asked questions
Is Gemini or Grok better in 2026?
Gemini 3.1 Pro leads on research benchmarks and Google ecosystem integration. Grok 4 is the only model with real-time X/Twitter data. For most users, Gemini is the stronger general-purpose choice.
Do Gemini and Grok have the same context window?
Yes — both Gemini 3.1 Pro and Grok 4 offer 2M token context windows, the largest among frontier models. For large document analysis, they're equally capable.
Which is cheaper — Gemini or Grok?
Input pricing is identical at $2/1M. Grok 4 is cheaper on output at $6/1M vs Gemini 3.1 Pro's $12/1M. For output-heavy workloads, Grok has a meaningful cost advantage.
Can Gemini access real-time data?
Gemini can integrate with Google Search for current information. Grok has exclusive real-time access to X/Twitter data. Both have real-time capabilities but from different sources.
Which is better for Google Workspace users?
Gemini 3.1 Pro is built for Google Workspace integration — it works natively in Gmail, Docs, Sheets, and Meet. Grok has no Google integration.