GPT-4o vs Grok 4.1 Fast

Grok 4.1 Fast wins 7 of 12 internal benchmarks in our testing, GPT-4o wins 0, and they tie on 5. Here's the test-by-test breakdown:

Strategic Analysis: Grok 4.1 Fast scores 5/5 (tied for 1st of 54 models) vs GPT-4o's 2/5 (rank 44 of 54). This is the widest gap in the suite. Strategic analysis tests nuanced tradeoff reasoning with real numbers — the kind of work that shows up in business analysis, investment memos, and technical architecture decisions. A score of 2 puts GPT-4o well below the median of 4 for this benchmark.

Structured Output: Grok 4.1 Fast scores 5/5 (tied for 1st of 54) vs GPT-4o's 4/5 (rank 26 of 54). JSON schema compliance and format adherence are critical for API integrations and data pipelines. Grok 4.1 Fast is a tier above here.

Long Context: Grok 4.1 Fast scores 5/5 (tied for 1st of 55) vs GPT-4o's 4/5 (rank 38 of 55). This tests retrieval accuracy at 30K+ tokens. Combined with Grok 4.1 Fast's 2M context window vs GPT-4o's 128K, Grok 4.1 Fast has a commanding advantage for long-document work.

Faithfulness: Grok 4.1 Fast scores 5/5 (tied for 1st of 55) vs GPT-4o's 4/5 (rank 34 of 55). Faithfulness measures whether a model sticks to source material without hallucinating — critical for summarization, RAG, and any task where accuracy to a reference document matters.

Multilingual: Grok 4.1 Fast scores 5/5 (tied for 1st of 55) vs GPT-4o's 4/5 (rank 36 of 55). Both are above the median, but Grok 4.1 Fast hits the ceiling.

Constrained Rewriting: Grok 4.1 Fast scores 4/5 (rank 6 of 53) vs GPT-4o's 3/5 (rank 31 of 53). Compression within hard character limits — copy editing, headline writing, prompt compression — goes to Grok 4.1 Fast.

Creative Problem Solving: Grok 4.1 Fast scores 4/5 (rank 9 of 54) vs GPT-4o's 3/5 (rank 30 of 54). Non-obvious, specific, feasible idea generation favors Grok 4.1 Fast.

Ties (5 benchmarks): Tool calling (both 4/5, rank 18 of 54), classification (both 4/5, tied for 1st of 53), safety calibration (both 1/5, rank 32 of 55 — both models score poorly here, below the field median), persona consistency (both 5/5, tied for 1st of 53), and agentic planning (both 4/5, rank 16 of 54).

On third-party benchmarks (Epoch AI), GPT-4o scores 31% on SWE-bench Verified (rank 12 of 12 models tested — last place among those measured), 53.3% on MATH Level 5 (rank 12 of 14), and 6.4% on AIME 2025 (rank 22 of 23). Grok 4.1 Fast does not have external benchmark scores in our data. These third-party results suggest GPT-4o trails significantly on coding and math tasks relative to other models in the field — though Grok 4.1 Fast's absence from these benchmarks means a direct external comparison isn't possible.

The pricing gap here is extreme. GPT-4o costs $2.50/M input tokens and $10/M output tokens. Grok 4.1 Fast costs $0.20/M input and $0.50/M output — a 12.5x input gap and a 20x output gap. In practice, at 1M output tokens/month, GPT-4o costs $10 vs Grok 4.1 Fast's $0.50 — a $9.50 difference. At 10M output tokens, that's $100,000 vs $5,000 — a $95,000 gap. At 100M output tokens, GPT-4o runs $1,000,000 vs $50,000 for Grok 4.1 Fast. Developers building high-volume applications — customer support bots, document pipelines, research tools — will find the cost difference transformative. Even consumer users calling the API at moderate volumes should factor this in. The only scenario where GPT-4o's pricing is defensible is if you specifically need capabilities present in GPT-4o but absent in Grok 4.1 Fast, such as its extended parameter support (frequency_penalty, logit_bias, logprobs, web_search_options) or its 128K context window — though Grok 4.1 Fast's 2M context window is actually far larger.

Choose Grok 4.1 Fast if you need strong benchmark performance across strategic analysis, structured output, long-context retrieval, faithfulness, multilingual output, or constrained rewriting — which covers the majority of professional and enterprise use cases. Its 2M context window makes it the only reasonable choice for very long documents. At $0.50/M output tokens, it's also the right call for any high-volume deployment where cost compounds quickly. Choose GPT-4o if you need its specific extended parameter set (frequency_penalty, logit_bias, logprobs, web_search_options), if your workflow depends on a 128K context window integrated with image and file inputs in an existing OpenAI ecosystem, or if you have downstream tooling hardcoded to OpenAI's API format that you cannot migrate. On benchmark performance alone, GPT-4o does not have a winning argument in this comparison.