GPT-5.4 vs Grok 4.20

Across our 12-test internal benchmark suite, GPT-5.4 and Grok 4.20 are remarkably close, with 8 of 12 tests ending in a tie. Here's the test-by-test breakdown:

GPT-5.4 wins:

• Safety calibration: GPT-5.4 scores 5/5; Grok 4.20 scores 1/5. This is the largest gap in the entire comparison. GPT-5.4 is tied for 1st with just 4 other models out of 55 tested — meaning it sits at the top of a very selective group on this metric. Grok 4.20 ranks 32nd of 55. In practice, this means GPT-5.4 is substantially more reliable at refusing clearly harmful requests while still permitting legitimate ones. For any public-facing or regulated deployment, this difference is not cosmetic.

• Agentic planning: GPT-5.4 scores 5/5 (tied for 1st with 14 others out of 54 tested); Grok 4.20 scores 4/5 (ranked 16th of 54). Goal decomposition and failure recovery are the core of agentic planning — GPT-5.4's edge here means it handles multi-step task orchestration more reliably in our testing.

Grok 4.20 wins:

• Tool calling: Grok 4.20 scores 5/5 (tied for 1st with 16 others out of 54 tested); GPT-5.4 scores 4/5 (ranked 18th of 54). Function selection, argument accuracy, and sequencing — the mechanics of agentic tool use — favor Grok 4.20. This is a meaningful gap for API developers building tool-augmented workflows.

• Classification: Grok 4.20 scores 4/5 (tied for 1st with 29 others out of 53 tested); GPT-5.4 scores 3/5 (ranked 31st of 53). Accurate categorization and routing is critical for triage systems, content moderation pipelines, and intent detection. GPT-5.4's 3/5 here is below the median (p50 = 4) across all 52 models, while Grok 4.20 sits at the top tier.

Tied (8 of 12 tests): Both models score identically on structured output (5/5), strategic analysis (5/5), constrained rewriting (4/5), creative problem solving (4/5), faithfulness (5/5), long context (5/5), persona consistency (5/5), and multilingual (5/5). These ties are genuine — the scores are the same, and in most cases both models share the top rank with a large field.

External benchmarks (Epoch AI): GPT-5.4 scores 76.9% on SWE-bench Verified (rank 2 of 12 models tested, sole holder of that score), placing it among the top coding models by this third-party measure of real GitHub issue resolution. On AIME 2025 competition math, GPT-5.4 scores 95.3% (rank 3 of 23 tested, sole holder). No external benchmark scores are available in the payload for Grok 4.20, so a direct external comparison cannot be made. GPT-5.4's SWE-bench score of 76.9% sits above the p75 of 75.25% across models with this score, and its AIME 2025 score of 95.3% sits well above the p50 of 83.9%.

GPT-5.4 costs $2.50/M input tokens and $15.00/M output tokens. Grok 4.20 costs $2.00/M input and $6.00/M output tokens. The input gap is modest ($0.50/M), but the output gap is where real costs accumulate.

At 1M output tokens/month: GPT-5.4 costs $15.00 vs Grok 4.20's $6.00 — a $9 difference that barely matters for most teams.

At 10M output tokens/month: $150 vs $60 — a $90/month gap that starts to register for mid-size API users.

At 100M output tokens/month: $1,500 vs $600 — a $900/month difference that is a real budget line item for high-volume production systems.

Who should care: Developers running document pipelines, chatbots, or agentic loops that generate large outputs at scale will feel Grok 4.20's $6/M output cost meaningfully. Enterprises running lower-volume, higher-stakes workflows — where safety calibration and agentic planning are critical — will likely find GPT-5.4's premium worth it. If your workload is primarily tool-calling-heavy automation (where Grok 4.20 scores 5/5 vs GPT-5.4's 4/5) at high volume, Grok 4.20 is both the better performer and the cheaper option.

Choose GPT-5.4 if:

• Safety calibration is non-negotiable. Its 5/5 score (top 5 of 55 models in our testing) versus Grok 4.20's 1/5 is a decisive gap for public-facing products, regulated industries, or any deployment where refusal behavior is audited.
• You need strong agentic planning (5/5 vs 4/5) for complex multi-step task orchestration.
• Coding quality matters at the frontier level: GPT-5.4's 76.9% on SWE-bench Verified (Epoch AI, rank 2 of 12) is a strong external signal for software engineering tasks.
• Your output volume is low-to-medium and the $15/M output cost is acceptable for the capability premium.

Choose Grok 4.20 if:

• Tool calling is your primary use case. Grok 4.20 scores 5/5 (tied for 1st) versus GPT-5.4's 4/5, and at $6/M output tokens it's both better on this metric and significantly cheaper.
• You need accurate classification or routing: Grok 4.20 scores 4/5 (tied for 1st) versus GPT-5.4's 3/5 — a below-median result.
• You're running high-output-volume workloads where the $9/M output cost savings compounds to hundreds of dollars monthly.
• You need a larger context window: Grok 4.20 offers a 2M token context window versus GPT-5.4's 1.05M — relevant for very long document processing.
• Safety calibration is not a primary concern for your deployment context.