GPT-4.1 Nano vs Grok 4.20

Across our 12 internal benchmark tests, Grok 4.20 wins 7, GPT-4.1 Nano wins 1, and they tie on 4.

Where Grok 4.20 wins:

• Strategic analysis (5 vs 2): Grok 4.20 ties for 1st among 54 models tested; GPT-4.1 Nano ranks 44th. This is the largest absolute gap between them — two full points on nuanced tradeoff reasoning with real numbers. If your application involves decision support, business analysis, or research synthesis, this gap is operationally significant.
• Creative problem solving (4 vs 2): Grok 4.20 ranks 9th of 54; GPT-4.1 Nano ranks 47th. For ideation, brainstorming, or generating non-obvious solutions, GPT-4.1 Nano sits near the bottom of the field.
• Tool calling (5 vs 4): Grok 4.20 ties for 1st of 54; GPT-4.1 Nano ranks 18th (tied with 28 others). In our testing, function selection, argument accuracy, and sequencing — the backbone of agentic workflows — are stronger on Grok 4.20.
• Classification (4 vs 3): Grok 4.20 ties for 1st of 53; GPT-4.1 Nano ranks 31st. Routing tasks, intent detection, and categorization are meaningfully better.
• Long context (5 vs 4): Grok 4.20 ties for 1st of 55 on retrieval accuracy at 30K+ tokens; GPT-4.1 Nano ranks 38th. Grok 4.20 also has a larger context window (2M vs ~1M tokens).
• Persona consistency (5 vs 4): Grok 4.20 ties for 1st of 53; GPT-4.1 Nano ranks 38th.
• Multilingual (5 vs 4): Grok 4.20 ties for 1st of 55; GPT-4.1 Nano ranks 36th.

Where GPT-4.1 Nano wins:

• Safety calibration (2 vs 1): GPT-4.1 Nano ranks 12th of 55; Grok 4.20 ranks 32nd. Neither model scores well here — the field median is 2, so GPT-4.1 Nano is slightly above median while Grok 4.20 is below. This means GPT-4.1 Nano is marginally better at refusing harmful requests while permitting legitimate ones, which matters for consumer-facing deployments.

Ties (both models equal):

• Structured output (5/5): Both tie for 1st among 54 models. JSON schema compliance is a non-issue for either.
• Faithfulness (5/5): Both tie for 1st among 55 models. Neither hallucinates materially beyond source material.
• Constrained rewriting (4/4): Both rank in the top tier for compression within hard limits.
• Agentic planning (4/4): Both rank 16th of 54, tied with 25 other models.

External benchmarks (Epoch AI): GPT-4.1 Nano has external math scores in the payload — it scores 70% on MATH Level 5 (ranking 11th of 14 models with this data) and 28.9% on AIME 2025 (ranking 20th of 23). No external benchmark scores are present for Grok 4.20 in our data, so a direct external comparison cannot be made. GPT-4.1 Nano's AIME 2025 score of 28.9% sits well below the field median of 83.9% among models tested, indicating limited competition-math capability.

GPT-4.1 Nano is priced at $0.10/M input tokens and $0.40/M output tokens. Grok 4.20 is $2.00/M input and $6.00/M output — 20x more expensive on input and 15x on output. In practice:

• At 1M output tokens/month: GPT-4.1 Nano costs $0.40; Grok 4.20 costs $6.00.
• At 10M output tokens/month: GPT-4.1 Nano costs $4.00; Grok 4.20 costs $60.00.
• At 100M output tokens/month: GPT-4.1 Nano costs $400; Grok 4.20 costs $6,000.

That $5,600 monthly gap at 100M output tokens is material for most businesses. Developers running classification pipelines, chatbots, or document triage at scale should weigh that gap carefully — GPT-4.1 Nano tied Grok 4.20 on structured output, faithfulness, constrained rewriting, and agentic planning, meaning you're not giving up much on those specific tasks. The cost difference matters most when your workload skews toward strategic analysis, creative problem solving, or long-context retrieval, where Grok 4.20 genuinely outscores its cheaper rival.

Choose GPT-4.1 Nano if:

• Cost and throughput are primary constraints. At $0.40/M output tokens, it's 15x cheaper than Grok 4.20 and competitive on structured output, faithfulness, constrained rewriting, and agentic planning.
• Your use case is document Q&A, summarization, data extraction, or structured data pipelines — tasks where GPT-4.1 Nano ties or approaches Grok 4.20.
• You're running a consumer-facing product where safety calibration matters — GPT-4.1 Nano scores 2 vs Grok 4.20's 1 in our testing.
• You need high-volume classification or routing but can't absorb Grok 4.20's cost at scale.

Choose Grok 4.20 if:

• You're building agentic workflows with complex tool calling — Grok 4.20 scores 5/5 (tied 1st of 54) vs GPT-4.1 Nano's 4/5 (18th of 54).
• Strategic analysis is core to your product — Grok 4.20's 5 vs 2 advantage here is the defining gap between these models.
• You need reliable performance on very long documents (2M context window, tied 1st on long context in our tests).
• Your application requires strong multilingual output or consistent persona maintenance — Grok 4.20 scores 5/5 on both, GPT-4.1 Nano scores 4/4.
• Token volume is moderate enough that the $5.60/M output cost difference is manageable relative to quality gains.