R1 0528 vs Grok 3 Mini

R1 0528 wins 5 tests; Grok 3 Mini wins none; 7 tests are tied.

Where R1 0528 wins outright:

• Safety calibration: R1 0528 scores 4/5 (rank 6 of 55, shared by 4 models) vs Grok 3 Mini's 2/5 (rank 12 of 55). This is a meaningful gap — Grok 3 Mini sits at the 50th percentile for this metric in our testing, while R1 0528 is well above it. In practice, this means R1 0528 is more reliably refusing genuinely harmful requests while permitting legitimate ones.
• Agentic planning: R1 0528 scores 5/5, tied for 1st with 14 other models out of 54 tested. Grok 3 Mini scores 3/5, ranking 42nd of 54. For multi-step goal decomposition and failure recovery — the foundation of agentic AI workflows — this is R1 0528's clearest practical advantage.
• Creative problem solving: R1 0528 scores 4/5 (rank 9 of 54) vs Grok 3 Mini's 3/5 (rank 30 of 54). Grok 3 Mini's description explicitly notes it's best for "logic-based tasks that do not require deep domain knowledge" — this score confirms that limitation.
• Strategic analysis: R1 0528 scores 4/5 (rank 27 of 54) vs Grok 3 Mini's 3/5 (rank 36 of 54). Both sit in the middle of the field, but R1 0528's advantage on nuanced tradeoff reasoning with real numbers is real.
• Multilingual: R1 0528 scores 5/5, tied for 1st of 55 tested. Grok 3 Mini scores 4/5 (rank 36 of 55). If your application serves non-English speakers, this gap has direct product impact.

Where they tie:

• Tool calling (both 5/5, tied for 1st of 54): Both models handle function selection, argument accuracy, and sequencing equally well in our testing.
• Faithfulness (both 5/5, tied for 1st of 55): Neither model hallucinates on top of source material.
• Structured output (both 4/5, rank 26 of 54): JSON schema compliance is equivalent.
• Long context (both 5/5, tied for 1st of 55): Retrieval accuracy at 30K+ tokens is identical.
• Persona consistency (both 5/5, tied for 1st of 53): Both maintain character and resist prompt injection.
• Classification (both 4/5, tied for 1st of 53): Categorization accuracy is the same.
• Constrained rewriting (both 4/5, rank 6 of 53): Compression within hard limits is matched.

External benchmarks (Epoch AI): R1 0528 scores 96.6% on MATH Level 5 (rank 5 of 14 models with this score) and 66.4% on AIME 2025 (rank 16 of 23). AIME 2025's p50 is 83.9% across models with this score — R1 0528 sits below the median on that harder olympiad test. Grok 3 Mini has no external benchmark scores in our data. R1 0528's MATH Level 5 score of 96.6% is near the p75 of 97.5%, placing it among the top competition math performers by that external measure.

One important caveat on R1 0528: The payload notes it returns empty responses on structured output, constrained rewriting, and agentic planning tasks when max_completion_tokens is set too low, because reasoning tokens consume the output budget. Despite this quirk, it still scored competitively on those tests — but production deployments must set high max_completion_tokens values to avoid silent failures.

R1 0528 costs $0.50/M input and $2.15/M output tokens. Grok 3 Mini costs $0.30/M input and $0.50/M output — making it 40% cheaper on input and 77% cheaper on output, a 4.3x overall price ratio. At 1M output tokens/month, you're spending $2,150 on R1 0528 vs $500 on Grok 3 Mini — a $1,650 difference. At 10M tokens/month that gap becomes $16,500; at 100M tokens/month it's $165,000. For high-volume applications — customer support pipelines, document processing, classification at scale — that cost difference is significant and Grok 3 Mini's matching scores on tool calling, faithfulness, structured output, and classification make it a rational choice. For lower-volume, higher-stakes work (legal analysis, multilingual deployments, agentic systems), the premium for R1 0528 is more easily justified.

Choose R1 0528 if:

• You're building agentic systems — its 5/5 agentic planning score (tied for 1st of 54) vs Grok 3 Mini's 3/5 (rank 42 of 54) is a substantial gap for multi-step workflows.
• Your application handles sensitive content and needs reliable safety calibration (4/5 vs 2/5).
• You serve non-English users and need consistent multilingual quality (5/5 vs 4/5).
• You need strong competition math performance — 96.6% on MATH Level 5 per Epoch AI.
• You're running moderate token volumes where the $1,650/M output token premium is manageable.
• You need the include_reasoning and broader parameter support (frequency_penalty, logit_bias, min_p, presence_penalty, repetition_penalty, seed, top_k) that R1 0528 offers.

Choose Grok 3 Mini if:

• You're running high-volume pipelines where tool calling, faithfulness, structured output, classification, or long-context retrieval are the primary tasks — Grok 3 Mini matches R1 0528 on all five at 77% lower output cost.
• Cost containment is a hard constraint: at $0.50/M output tokens vs $2.15/M, Grok 3 Mini saves $165,000 per 100M output tokens.
• Your workload fits Grok 3 Mini's design profile: logic-based tasks without deep domain knowledge requirements.
• You don't need the advanced parameter controls R1 0528 supports (no frequency_penalty, logit_bias, or top_k on Grok 3 Mini).
• You want logprobs and top_logprobs support, which Grok 3 Mini provides and R1 0528 does not.