GPT-5 vs Grok 3 Mini

GPT-5 wins 5 benchmarks outright, ties 7, and loses none in our testing. Grok 3 Mini wins zero and ties those same 7. Here's what the score differences mean in practice:

Where GPT-5 wins:

• Agentic planning: GPT-5 scores 5/5 (tied for 1st of 54 with 14 others) vs Grok 3 Mini's 3/5 (rank 42 of 54). This is the biggest practical gap. Agentic planning tests goal decomposition and failure recovery — the core of multi-step AI pipelines. A 2-point gap here is meaningful for any workflow where an AI needs to orchestrate tools or recover from errors.

• Strategic analysis: GPT-5 scores 5/5 (tied for 1st of 54) vs Grok 3 Mini's 3/5 (rank 36 of 54). Strategic analysis tests nuanced tradeoff reasoning with real numbers — relevant for business analysis, decision support, and research synthesis.

• Creative problem solving: GPT-5 scores 4/5 (rank 9 of 54) vs Grok 3 Mini's 3/5 (rank 30 of 54). Grok 3 Mini sits solidly mid-pack here; GPT-5 generates more specific, non-obvious, and feasible ideas in our testing.

• Structured output: GPT-5 scores 5/5 (tied for 1st of 54) vs Grok 3 Mini's 4/5 (rank 26 of 54). JSON schema compliance and format adherence — important for developers relying on predictable API output.

• Multilingual: GPT-5 scores 5/5 (tied for 1st of 55) vs Grok 3 Mini's 4/5 (rank 36 of 55). If non-English output quality matters — customer support, localization, global products — GPT-5 has a clear edge.

Where they tie (7 benchmarks):

• Tool calling (both 5/5, tied for 1st of 54): Both models select functions accurately and sequence calls correctly. No reason to pay more for GPT-5 on tool-heavy pipelines where planning complexity is low.
• Faithfulness (both 5/5, tied for 1st of 55): Both stick closely to source material. Equal for RAG applications and summarization.
• Long context (both 5/5, tied for 1st of 55): Both handle 30K+ token retrieval accurately. Note that GPT-5 supports a 400K context window vs Grok 3 Mini's 131K — a structural advantage for extremely long documents even at equal scores.
• Persona consistency (both 5/5, tied for 1st of 53): Equal for chatbot and character applications.
• Classification (both 4/5, tied for 1st of 53): Equal routing and categorization accuracy.
• Constrained rewriting (both 4/5, rank 6 of 53): Equal performance compressing content within hard character limits.
• Safety calibration (both 2/5, rank 12 of 55): Both models score below the field median on this benchmark — this measures refusing harmful requests while permitting legitimate ones. Neither model differentiates here; both sit below the p50 of 2 in the broader model pool.

External benchmarks (Epoch AI):

GPT-5 carries external benchmark data worth noting. On SWE-bench Verified (real GitHub issue resolution), GPT-5 scores 73.6% — rank 6 of 12 models tested, above the field median of 70.8%. On MATH Level 5 (competition math), GPT-5 scores 98.1%, ranking 1st of 14 models tested — the sole holder of that score. On AIME 2025 (math olympiad), GPT-5 scores 91.4%, ranking 6th of 23 models tested, above the field median of 83.9%. Grok 3 Mini has no external benchmark scores in our data. These external results, sourced from Epoch AI (CC BY), reinforce GPT-5's strength in mathematical reasoning and suggest competitive coding capability — though Grok 3 Mini's absence from these tests means a direct external comparison isn't possible.

GPT-5 is priced at $1.25/M input tokens and $10.00/M output tokens. Grok 3 Mini runs at $0.30/M input and $0.50/M output — a 4.2x input gap and a 20x output gap.

At real-world volumes, that output gap is the one that matters most:

• 1M output tokens/month: GPT-5 costs $10.00 vs Grok 3 Mini's $0.50 — a $9.50 difference that's negligible for most use cases.
• 10M output tokens/month: GPT-5 costs $100.00 vs $5.00 — a $95 monthly delta. Still manageable for serious API users.
• 100M output tokens/month: GPT-5 costs $1,000.00 vs $50.00 — a $950/month gap. At this scale, you need GPT-5's benchmark advantages to justify the spend.

Who should care: developers building production pipelines with high token throughput, and anyone using a model primarily for logic, routing, or classification tasks where Grok 3 Mini scores identically to GPT-5. Consumer subscribers choosing between API tiers should weigh whether the 5 benchmarks GPT-5 wins — agentic planning, strategic analysis, multilingual, structured output, and creative problem solving — are central to their workflows. If they're not, Grok 3 Mini represents substantial savings.

Choose GPT-5 if:

• You're building agentic workflows requiring multi-step planning or failure recovery — it scores 5 vs Grok 3 Mini's 3 in our testing.
• Your application involves strategic analysis, business decision support, or complex tradeoff reasoning.
• You need reliable structured output (JSON schema compliance) from an API with minimal formatting errors.
• Your product serves non-English speakers — GPT-5 scores 5 vs 4 on multilingual output.
• You need to process very long documents: GPT-5's 400K context window is 3x Grok 3 Mini's 131K.
• Math-heavy tasks are core to your use case — GPT-5 scores 98.1% on MATH Level 5 and 91.4% on AIME 2025 (Epoch AI), the strongest external math signal in this comparison.
• Cost is secondary to capability at your usage volume.

Choose Grok 3 Mini if:

• Your workload is primarily tool calling, classification, faithfulness, or RAG — it matches GPT-5's scores on all seven of those benchmarks at 1/20th the output cost.
• You're running high-volume inference: at 100M output tokens/month, Grok 3 Mini saves ~$950 vs GPT-5 with identical results on more than half the benchmarks.
• You want accessible reasoning traces — Grok 3 Mini exposes raw thinking traces, which aids debugging and transparency.
• Your use case is logic-based and self-contained, not requiring deep domain knowledge or complex planning chains.
• Budget is a hard constraint and the five benchmarks GPT-5 wins aren't central to your application.