GPT-5.4 Mini vs Grok 4.20
For most teams balancing performance and cost, GPT-5.4 Mini is the better pick: it ties Grok 4.20 on 10 of 12 benchmarks while costing less. Grok 4.20 is the choice when tool calling and agentic function selection are primary requirements (tool calling: 5 vs 4). GPT-5.4 Mini holds the edge on safety calibration (2 vs 1) and reduces per-token spend.
openai
GPT-5.4 Mini
Benchmark Scores
External Benchmarks
Pricing
Input
$0.750/MTok
Output
$4.50/MTok
modelpicker.net
xai
Grok 4.20
Benchmark Scores
External Benchmarks
Pricing
Input
$2.00/MTok
Output
$6.00/MTok
modelpicker.net
Benchmark Analysis
Across our 12-test suite the models mostly tie: 10 metrics are identical in our testing. Ties (both models) at top scores include structured output (5/5 — both tied for 1st of 54, reliable JSON/schema compliance), strategic analysis (5/5 — tied for 1st of 54, strong tradeoff reasoning), faithfulness (5/5 — tied for 1st of 55, low hallucination), long context (5/5 — tied for 1st of 55, accurate retrieval at 30K+ tokens), persona consistency (5/5 — tied for 1st of 53), multilingual (5/5 — tied for 1st of 55), classification (4/4 — tied for 1st), creative problem solving (4/4), constrained rewriting (4/4), and agentic planning (4/4). Where they differ: Grok 4.20 wins tool calling in our testing (5 vs 4), and Grok ranks tied for 1st on tool calling out of 54 models (tied with 16 others) — this matters for systems that must select functions, produce precise arguments, and orchestrate sequences of tools. GPT-5.4 Mini wins safety calibration in our testing (2 vs 1); GPT-5.4 Mini ranks 12 of 55 (20 models share that score) while Grok ranks 32 of 55 (24 models share), so GPT-5.4 Mini is better at refusing harmful requests and allowing legitimate ones. Practical meaning: pick Grok for highest-confidence function/agent workflows; pick GPT-5.4 Mini for a lower-cost, safer default that matches Grok on most core capabilities (formatting, reasoning, long context, multilingual output).
Pricing Analysis
Costs per thousand output tokens: GPT-5.4 Mini $4.50/mtok, Grok 4.20 $6.00/mtok; input costs are $0.75/mtok (GPT) vs $2.00/mtok (Grok). Per million output tokens alone that is $4,500 (GPT) vs $6,000 (Grok). With a 1:1 input:output token split, total monthly cost per 1M tokens is $5,250 (GPT) vs $8,000 (Grok). Scale effects: 10M output tokens = $45,000 (GPT) vs $60,000 (Grok); with 1:1 split totals are $52,500 vs $80,000. At 100M output tokens the outputs cost $450,000 vs $600,000 (totals with equal input = $525,000 vs $800,000). Who should care: high-volume API customers, startups, and cost-sensitive production deployments — the ~25% lower output rate and much lower input rate on GPT-5.4 Mini materially reduce monthly bills at 10M+ tokens.
Real-World Cost Comparison
Bottom Line
Choose GPT-5.4 Mini if you want the best cost-to-performance balance: it ties Grok on 10 of 12 benchmarks, costs $4.50/mtok output (vs $6.00), and scores higher on safety calibration (2 vs 1). Choose Grok 4.20 if your product depends on agentic tool-calling and function orchestration (tool calling 5 vs 4, tied for 1st), and you can absorb the higher input ($2.00/mtok) and output ($6.00/mtok) rates. Specifics: use GPT-5.4 Mini for high-volume chat, long-context retrieval, and multilingual apps that need safer refusals; use Grok 4.20 for tool-heavy developer tooling, automation, and systems that prioritize flawless function selection.
How We Test
We test every model against our 12-benchmark suite covering tool calling, agentic planning, creative problem solving, safety calibration, and more. Each test is scored 1–5 by an LLM judge. Read our full methodology.