Gemini 2.5 Pro vs Grok 4

Across our 12-test internal suite, Gemini 2.5 Pro wins 4 tests, Grok 4 wins 3, and they tie on 5. Here's the test-by-test breakdown:

Where Gemini 2.5 Pro wins:

• Tool calling (5 vs 4): Gemini 2.5 Pro scores 5/5, tied for 1st among 17 models out of 54 tested. Grok 4 scores 4, ranked 18th of 54. This gap matters directly for agentic workflows — function selection accuracy and argument sequencing are where Gemini 2.5 Pro pulls ahead.
• Creative problem solving (5 vs 3): A two-point gap is meaningful. Gemini 2.5 Pro ties for 1st among 8 models out of 54; Grok 4 ranks 30th of 54. For tasks requiring non-obvious, feasible ideas, this is a clear Gemini 2.5 Pro advantage.
• Structured output (5 vs 4): Gemini 2.5 Pro ties for 1st among 25 models out of 54; Grok 4 ranks 26th of 54. JSON schema compliance and format adherence are critical for production API integrations.
• Agentic planning (4 vs 3): Gemini 2.5 Pro ranks 16th of 54; Grok 4 ranks 42nd of 54 — a significant drop. Goal decomposition and failure recovery favor Gemini 2.5 Pro in multi-step autonomous workflows.

Where Grok 4 wins:

• Strategic analysis (5 vs 4): Grok 4 ties for 1st among 26 models out of 54; Gemini 2.5 Pro ranks 27th of 54. For nuanced tradeoff reasoning with real numbers, Grok 4 has a genuine edge.
• Constrained rewriting (4 vs 3): Grok 4 ranks 6th of 53; Gemini 2.5 Pro ranks 31st of 53. Compression within hard character limits is a clear Grok 4 strength — relevant for editorial, copywriting, and summarization tasks.
• Safety calibration (2 vs 1): Grok 4 scores 2, ranking 12th of 55; Gemini 2.5 Pro scores 1, ranking 32nd of 55. Both scores are below the field median of 2 — neither model excels here — but Grok 4 is meaningfully better at refusing harmful requests while permitting legitimate ones.

Tied tests (both score identically):

• Long context (5/5), faithfulness (5/5), persona consistency (5/5), multilingual (5/5), and classification (4/4) are all ties. Both models handle long-context retrieval at 30K+ tokens and maintain character/source fidelity at the top of the field.

External benchmarks (Epoch AI): Gemini 2.5 Pro scores 57.6% on SWE-bench Verified (real GitHub issue resolution), ranking 10th of 12 models with external scores in our dataset — below the field median of 70.8% among models with that score. On AIME 2025 (math olympiad), it scores 84.2%, ranking 11th of 23 models, near the field median of 83.9%. These external scores suggest Gemini 2.5 Pro is competitive on advanced math but trails leading models on autonomous code repair. No external benchmark scores are available for Grok 4 in our dataset.

Gemini 2.5 Pro costs $1.25/M input tokens and $10/M output tokens. Grok 4 costs $3/M input and $15/M output — 2.4× more expensive on input and 1.5× more on output. In practice, output cost dominates most workloads. At 1M output tokens/month, you're paying $10 vs $15 — a $5 gap that's negligible. At 10M tokens/month, that gap is $50 vs $150 on input plus $100 vs $150 on output, totaling roughly $162.50 vs $180 — still manageable. At 100M tokens/month, the difference becomes $1,625 vs $1,800 total, or roughly $175/month in savings for Gemini 2.5 Pro. The input cost gap matters more at high-volume RAG or long-context workloads: pumping 100M input tokens through Grok 4 costs $300 vs $125 for Gemini 2.5 Pro — a $175 monthly difference on input alone. Developers building agentic pipelines with large context windows should weigh this carefully, especially since Gemini 2.5 Pro also offers a 1,048,576-token context window versus Grok 4's 256,000 tokens, compounding the cost advantage on long-context tasks.

Choose Gemini 2.5 Pro if you're building agentic pipelines, API integrations, or multi-step automation — its 5/5 on tool calling and agentic planning, plus superior structured output compliance, make it the stronger engineering platform. It's also the right call for creative ideation tasks (5 vs 3 on creative problem solving) and for workloads with very long context requirements, where its 1,048,576-token window and lower cost per token compound into real savings. On AIME 2025, it scores 84.2% (Epoch AI), placing it near the median for math-capable models.

Choose Grok 4 if your work centers on strategic analysis, financial or business reasoning, or editorial tasks that demand tight constrained rewriting. Its 5/5 on strategic analysis (tied for 1st among 26 models) and stronger constrained rewriting score (4 vs 3, ranked 6th of 53) make it the better tool for analyst workflows and high-precision copy tasks. The $5/M output token premium is justifiable if those are your primary use cases. Grok 4 also scores higher on safety calibration, which may matter in regulated or consumer-facing deployments.