GPT-5 Nano vs Grok 4.1 Fast

Across our 12-test benchmark suite, Grok 4.1 Fast wins 6 categories outright, ties 5, and loses 1. GPT-5 Nano wins only safety calibration. Here's the breakdown:

Where Grok 4.1 Fast wins:

• Strategic analysis: Grok 4.1 Fast scores 5/5 (tied for 1st among 54 models with 25 others) vs GPT-5 Nano's 4/5 (rank 27 of 54). For nuanced tradeoff reasoning with real numbers — competitive intelligence, financial analysis, decision memos — Grok 4.1 Fast has a clear edge.
• Faithfulness: Grok 4.1 Fast scores 5/5 (tied for 1st among 55 models) vs GPT-5 Nano's 4/5 (rank 34 of 55). Grok 4.1 Fast is less likely to hallucinate or drift from source material, which matters for summarization, RAG pipelines, and document QA.
• Classification: Grok 4.1 Fast scores 4/5 (tied for 1st among 53 models) vs GPT-5 Nano's 3/5 (rank 31 of 53). More accurate routing and categorization — relevant for support ticket triage, content moderation, intent detection.
• Creative problem solving: Grok 4.1 Fast scores 4/5 (rank 9 of 54) vs GPT-5 Nano's 3/5 (rank 30 of 54). Grok 4.1 Fast generates more non-obvious and feasible solutions in our testing.
• Constrained rewriting: Grok 4.1 Fast scores 4/5 (rank 6 of 53) vs GPT-5 Nano's 3/5 (rank 31 of 53). Compression to hard character limits — ad copy, UI strings, summaries — is substantially better.
• Persona consistency: Grok 4.1 Fast scores 5/5 (tied for 1st among 53 models) vs GPT-5 Nano's 4/5 (rank 38 of 53). Grok 4.1 Fast maintains character and resists prompt injection more reliably in our tests.

Where GPT-5 Nano wins:

• Safety calibration: GPT-5 Nano scores 4/5 (rank 6 of 55, one of only 4 models at this score) vs Grok 4.1 Fast's 1/5 (rank 32 of 55). This is a decisive win. GPT-5 Nano correctly refuses harmful requests while permitting legitimate ones at a level well above the median (p50 = 2/5 across all 55 models). Grok 4.1 Fast's score of 1/5 places it in the bottom quarter of the field — a significant concern for consumer-facing or compliance-sensitive deployments.

Ties (both models perform equally):

• Structured output (both 5/5, tied for 1st among 54 models): Both reliably produce valid JSON and schema-compliant responses.
• Tool calling (both 4/5, rank 18 of 54): Both perform comparably on function selection, argument accuracy, and sequencing — adequate but not top-tier.
• Agentic planning (both 4/5, rank 16 of 54): Goal decomposition and failure recovery are equivalent.
• Long context (both 5/5, tied for 1st among 55 models): Both handle retrieval accuracy at 30K+ tokens with top-tier performance. Note that Grok 4.1 Fast's 2M context window vs GPT-5 Nano's 400K means Grok 4.1 Fast can process much longer inputs at that quality level.
• Multilingual (both 5/5, tied for 1st among 55 models): Both deliver equivalent quality in non-English languages.

External benchmark data (Epoch AI): GPT-5 Nano has scores from two third-party math benchmarks. On MATH Level 5 (competition math), it scores 95.2% — ranking 7th of 14 models with data, above the field median of 94.15%. On AIME 2025 (math olympiad), it scores 81.1% — ranking 14th of 23 models with data, just below the field median of 83.9%. No external benchmark scores are available for Grok 4.1 Fast in the payload, so a direct external comparison cannot be made. These scores suggest GPT-5 Nano has solid math reasoning capability, above or near the median of models with external benchmark data.

GPT-5 Nano charges $0.05 per million input tokens and $0.40 per million output tokens. Grok 4.1 Fast charges $0.20 input and $0.50 output — 4× more expensive on input, 25% more on output.

At 1M tokens/month (light usage): the input cost gap is just $0.15, essentially irrelevant. At 10M tokens/month: you're paying $1.50 vs $6.00 on input alone — still modest, but the delta is real. At 100M tokens/month: input costs run $5,000 for GPT-5 Nano vs $20,000 for Grok 4.1 Fast — a $15,000/month difference that demands justification.

Output tokens matter too. At 100M output tokens/month, GPT-5 Nano costs $40,000 vs Grok 4.1 Fast's $50,000 — a $10,000 gap. For most production workloads where output volume is high, the combined savings with GPT-5 Nano are substantial.

Developers running classification pipelines, document routing, or chat interfaces at scale should weigh the $0.15-per-MTok output gap carefully. For infrequent or low-volume use cases, the cost difference is negligible and quality should dominate the decision. Note also that Grok 4.1 Fast offers a 2M-token context window vs GPT-5 Nano's 400K — if you need to process very long documents in a single call, Grok 4.1 Fast's context advantage may alone justify the price.

Choose GPT-5 Nano if:

• Safety and content moderation are non-negotiable — its 4/5 safety calibration score (rank 6 of 55) is far above Grok 4.1 Fast's 1/5 and makes it the clear choice for consumer-facing apps, healthcare, legal, or any compliance-sensitive context.
• You're processing at high volume (tens of millions of tokens/month) and the 4× input cost gap becomes a real budget line item.
• Your workload is math-heavy — external benchmark data (Epoch AI) shows a 95.2% MATH Level 5 score and 81.1% AIME 2025 score, with no comparable external data available for Grok 4.1 Fast.
• You need structured output or long-context retrieval at the lowest price — both models tie at 5/5, but GPT-5 Nano gets there for $0.05/MTok input.
• Latency and speed are priorities — GPT-5 Nano is described as optimized for rapid interactions and ultra-low latency environments.

Choose Grok 4.1 Fast if:

• Output quality across analysis, writing, and classification is the primary driver — it wins 6 of 12 benchmarks including strategic analysis, faithfulness, classification, constrained rewriting, creative problem solving, and persona consistency.
• You're building agentic workflows involving customer support or deep research — Grok 4.1 Fast is described as xAI's best agentic tool calling model for these use cases.
• You need to process documents longer than 400K tokens — its 2M context window is 5× larger than GPT-5 Nano's.
• You need reliable persona maintenance for chatbots or role-based agents — its 5/5 persona consistency score (tied for 1st) vs GPT-5 Nano's 4/5 (rank 38 of 53) is a meaningful gap.
• The $0.10/MTok output premium is acceptable relative to the quality gains you need — at moderate volumes, the cost difference is manageable.