Gemini 3.1 Pro vs Grok 4
Compare pricing, context windows, and strengths for Gemini 3.1 Pro by Google and Grok 4 by xAI - and see how to put either to work in Appaca.
Gemini 3.1 Pro
Google's most advanced reasoning Gemini model, built for complex multimodal problem-solving, software engineering, and long-horizon agentic workflows.
View Gemini 3.1 ProGrok 4
A flagship multimodal model excelling in natural language, math, and deep reasoning with unmatched all-around performance.
View Grok 4Gemini 3.1 Pro vs Grok 4 at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | Gemini 3.1 Pro | Grok 4 |
|---|---|---|
| Provider | xAI | |
| Model type | Text | Text |
| Context window | 1.05M tokens | 256K tokens |
| Input price | $4 / 1M tokens | $3 / 1M tokens |
| Output price | $18 / 1M tokens | $15 / 1M tokens |
| Status | Current | Current |
How Gemini 3.1 Pro and Grok 4 differ
What the numbers mean in practice when choosing between Gemini 3.1 Pro and Grok 4.
Our take
Gemini 3.1 Pro brings a million-token context and strong multimodal reasoning; Grok 4 brings cheaper input pricing and a reputation for current knowledge. For document-heavy analysis and retrieval workloads Gemini is the natural pick, while Grok 4 suits research and monitoring tools where recency matters more than raw context size.
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Gemini 3.1 Pro's 1.05M-token context is roughly four times Grok 4's 256K.
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Grok 4 input is $3 per million tokens versus $4 for Gemini 3.1 Pro; output is $15 versus $18.
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Both are strong reasoners - the choice usually follows the shape of your data rather than benchmark deltas.
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Grok 4 is 25% cheaper on input tokens ($3 vs $4 per million), which adds up quickly in document-heavy workloads.
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Grok 4 is 17% cheaper on output tokens ($15 vs $18 per million) - the bigger factor for tools that generate long documents.
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Gemini 3.1 Pro's 1.05M tokens context window is roughly 4.1x larger than Grok 4's 256K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
Gemini 3.1 Pro
1. Google's most advanced reasoning Gemini model
- Designed to solve complex problems across multimodal inputs, including text, audio, images, video, PDFs, and full code repositories.
- Google highlights improved software engineering behavior, better agentic performance, and stronger usability in domains like finance and spreadsheets.
2. Large multimodal context with substantial output room
- Supports a 1,048,576 token input context window for large repositories, long documents, and multi-source workflows.
- Allows up to 65,536 output tokens for longer answers, plans, and code generations.
3. More efficient thinking with expanded controls
- Improves token efficiency and reasoning performance across use cases.
- Adds the
MEDIUMthinking_leveloption to better balance cost, speed, and quality.
4. Strong support for production agents
- Supports grounding with Google Search, code execution, function calling, structured outputs, context caching, RAG, and chat completions.
- Also offers a custom-tools endpoint tuned for agentic workflows that mix bash-like tools with custom code tools.
Grok 4
1. Flagship-level reasoning and math performance
- Designed for world-class reasoning depth, precision, and multi-step logical chains.
- Excels at STEM, mathematics, symbolic operations, proofs, and analytical workloads.
2. Powerful multimodal understanding
- Supports text, images, and other modalities.
- Handles cross-modal reasoning tasks requiring context synthesis.
3. Extreme capability across diverse tasks
- Positioned as a top-tier 'jack of all trades' model.
- Strong in natural language, coding, knowledge retrieval, and structured generation.
4. Large 256K context window
- Enables analysis of long documents, entire codebases, multi-document packs, and extensive agent sessions.
- Supports workloads that require persistent reasoning across large inputs.
5. Advanced developer tooling support
- Function calling for tool-augmented workflows.
- Structured outputs for predictable, schema-controlled generation.
- Integrates smoothly with agents and complex automation pipelines.
6. Efficient caching for cost reduction
- Cached input tokens discounted to $0.75 / 1M tokens.
- Encourages RAG, retrieval pipelines, and multi-step conversational workflows.
7. Production-ready performance
- Stable rate limits: 480 requests per minute.
- High token throughput: 2,000,000 tokens per minute.
- Available across multiple xAI regional clusters.
8. Optional Live Search augmentation
- Add-on: $25 per 1K sources.
- Enhances factual accuracy and real-time information retrieval.
Use Gemini 3.1 Pro or Grok 4 - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by Gemini 3.1 Pro or Grok 4 - connected to your real data and ready for your whole team. No code, no deployment.
Describe it, and it's built
Tell the Appaca agent the internal tool you need and it builds a working app powered by Gemini 3.1 Pro or Grok 4. No code, no API keys, no deployment.
Switch models without rebuilding
Start on Gemini 3.1 Pro, test the same tool on Grok 4, and keep whichever performs better - the rest of your app stays exactly as it is.
Automated for the whole team
Schedule tools to run on autopilot - daily digests, weekly reports, real-time triggers - and share them with your whole team from one workspace.
Describe it, and it's built
Tell the Appaca agent what your team needs and it builds a working app powered by Gemini 3.1 Pro or Grok 4 - connected to the tools you already use.
Related comparisons
See how Gemini 3.1 Pro and Grok 4 stack up against other models in the directory.
FAQs
Grok 4 is generally cheaper: $3 input / $15 output per million tokens, versus $4 / $18 for Gemini 3.1 Pro. Actual cost depends on how many tokens your workload reads and writes.
Gemini 3.1 Pro has the larger context window at 1.05M tokens, compared to 256K tokens for Grok 4. A larger window means the model can consider more text at once - useful for long contracts, codebases, or months of records.
Gemini 3.1 Pro brings a million-token context and strong multimodal reasoning; Grok 4 brings cheaper input pricing and a reputation for current knowledge. For document-heavy analysis and retrieval workloads Gemini is the natural pick, while Grok 4 suits research and monitoring tools where recency matters more than raw context size.
Yes. Appaca is a no-code AI workspace: describe the internal tool your team needs and the Appaca agent builds it as a working app powered by Gemini 3.1 Pro, Grok 4, or any other model in the directory - with a built-in database, team access, and integrations. No API keys to wire up and nothing to deploy.
Build AI tools with Gemini 3.1 Pro or Grok 4
Describe the tool your team needs and get a working app powered by the model you choose - with a built-in database, team access, and integrations. No code, no deployment.