R1 vs Grok 4.1 Fast

Across our 12 internal tests, Grok 4.1 Fast wins 3, R1 wins 1, and they tie on 8.

Where Grok 4.1 Fast wins:

• Structured output (5/5 vs 4/5): Grok 4.1 Fast ties for 1st among 54 models; R1 ranks 26th. For JSON schema compliance and API integrations, this is a meaningful edge.
• Classification (4/5 vs 2/5): Grok 4.1 Fast ties for 1st among 53 models; R1 ranks 51st out of 53 — near the bottom. This is R1's clearest weakness. Routing, tagging, and categorization tasks should not go to R1 based on our testing.
• Long context (5/5 vs 4/5): Grok 4.1 Fast ties for 1st among 55 models; R1 ranks 38th. Grok 4.1 Fast's 2M context window dwarfs R1's 64K, and the scores back up its ability to use that context — retrieval accuracy at 30K+ tokens is top-tier.

Where R1 wins:

• Creative problem-solving (5/5 vs 4/5): R1 ties for 1st with 7 other models out of 54; Grok 4.1 Fast ranks 9th. R1 generates more non-obvious, specific, feasible ideas in our testing. If brainstorming, ideation, or lateral thinking is central to your use case, R1 has a real edge here.

Where they tie (8 tests): Strategic analysis, constrained rewriting, tool calling, faithfulness, safety calibration, persona consistency, agentic planning, and multilingual all come in tied — both models score identically on these. Neither model distinguishes itself on tool calling (both rank 18th of 54) or agentic planning (both rank 16th of 54), so neither has a structural advantage for autonomous agent pipelines based on our internal benchmarks.

External benchmarks (Epoch AI): R1 scores 93.1% on MATH Level 5 (rank 8 of 14 models tested) and 53.3% on AIME 2025 (rank 17 of 23). Grok 4.1 Fast has no external benchmark scores in our data. R1's MATH Level 5 score is above the median (94.15% median among tested models, so R1 sits just below the midpoint), and its AIME 2025 score of 53.3% falls well below the median of 83.9%. These third-party results suggest R1's math reasoning, while solid, is not at the top of the field by those external measures. Developers building math-heavy applications should weigh these numbers alongside our internal creative problem-solving score.

Key structural differences: R1 requires a minimum of 1,000 max completion tokens and benefits from high max completion token settings — both quirks reflect its chain-of-thought reasoning architecture. Grok 4.1 Fast supports reasoning toggling (enable/disable), logprobs, and structured outputs as a parameter, giving developers more control. R1 supports a broader set of sampling parameters including top_k, repetition_penalty, and frequency_penalty, which matters for fine-grained generation control.

Grok 4.1 Fast costs $0.20/M input and $0.50/M output. R1 costs $0.70/M input and $2.50/M output — a 3.5x input gap and 5x output gap. In practice: at 1M output tokens/month, R1 costs $2.50 vs $0.50 for Grok 4.1 Fast, a $2/month difference that's negligible for most teams. At 10M output tokens, the gap becomes $25 vs $5 — $20/month, still minor. At 100M output tokens, R1 runs $250/month vs Grok 4.1 Fast's $50, a $200/month difference that starts to matter for high-volume pipelines. The cost gap is most relevant for developers running document processing, classification, or structured extraction at scale — exactly the tasks where Grok 4.1 Fast also scores equal or better. Grok 4.1 Fast also accepts image and file inputs (text+image+file->text), while R1 is text-only, which could eliminate the need for a separate vision model and further shift the cost calculus for multimodal workflows.

Choose Grok 4.1 Fast if you need structured output, classification, or long-context retrieval — it outscores R1 on all three in our testing while costing 5x less per output token. It's also the better fit for multimodal workflows (image and file inputs), high-volume pipelines where the $0.50 vs $2.50/M output cost adds up, and any use case requiring a context window beyond 64K tokens (its 2M window vs R1's 64K is a hard constraint difference).

Choose R1 if creative problem-solving is your primary task — it scores 5/5 vs Grok 4.1 Fast's 4/5 in our testing and ties for 1st with 7 models out of 54. It also exposes full reasoning tokens and offers more granular sampling parameters (top_k, repetition_penalty), which matters for research applications or workflows where transparency into the model's reasoning chain is required. R1's open reasoning token access is a structural differentiator that Grok 4.1 Fast does not offer in the same way.