Grok 4.20 vs o4 Mini

Across our 12-test internal benchmark suite, Grok 4.20 and o4 Mini produce nearly identical results — Grok 4.20 wins one test outright, o4 Mini wins none, and they tie on all 11 remaining categories.

Where Grok 4.20 wins:

• Constrained rewriting (4 vs 3): Grok 4.20 scores 4/5 (rank 6 of 53, tied with 24 models) while o4 Mini scores 3/5 (rank 31 of 53, tied with 21 models). This test measures compression within hard character limits — relevant for UI copy, SMS, tweet-length outputs, and any task where exceeding a length constraint breaks downstream systems. The gap here is real and meaningful for those use cases.

Where they tie (11 of 12 tests):

• Tool calling (5/5 each): Both rank tied for 1st with 16 other models out of 54 tested. At the top of the field, neither has an edge for agentic tool use.
• Strategic analysis (5/5 each): Both tied for 1st with 25 others out of 54. Nuanced tradeoff reasoning is equally strong.
• Structured output (5/5 each): Both tied for 1st with 24 others out of 54. JSON schema compliance is a non-issue for either model.
• Faithfulness (5/5 each): Both tied for 1st with 32 others out of 55. Neither hallucinates against source material in our testing.
• Long context (5/5 each): Both tied for 1st with 36 others out of 55. Both retrieve accurately at 30K+ tokens in our tests — though Grok 4.20's 2M-token context window vs o4 Mini's 200K window is a structural advantage that goes beyond what this test captures.
• Multilingual (5/5 each): Both tied for 1st with 34 others out of 55.
• Persona consistency (5/5 each): Both tied for 1st with 36 others out of 53.
• Classification (4/5 each): Both tied for 1st with 29 others out of 53.
• Agentic planning (4/5 each): Both rank 16 of 54, tied with 25 others.
• Creative problem solving (4/5 each): Both rank 9 of 54, tied with 20 others.
• Safety calibration (1/5 each): Both rank 32 of 55, tied with 23 others. This is below the field median of 2/5 — neither model distinguishes itself on refusing harmful requests while permitting legitimate ones in our testing.

External benchmarks (o4 Mini only): The payload includes third-party scores for o4 Mini from Epoch AI. On MATH Level 5, o4 Mini scores 97.8% — rank 2 of 14 models tested, tied with 2 others, above the field median of 94.15%. On AIME 2025, it scores 81.7% — rank 13 of 23 models, sole holder of that score, and near the field median of 83.9%. These place o4 Mini solidly in the upper tier for competition math. No equivalent external benchmark data is present in the payload for Grok 4.20, so a direct external comparison cannot be made.

Grok 4.20 costs $2.00 per million input tokens and $6.00 per million output tokens. o4 Mini costs $1.10 input and $4.40 output — roughly 45% cheaper on output, which is typically the larger cost driver. At 1M output tokens/month, that gap is $1.60 ($6.00 vs $4.40) — negligible for most teams. At 10M output tokens it becomes $16,000 vs $44,000 — a $28,000 annual difference that starts to matter for product teams with real traffic. At 100M output tokens/month, you're looking at $440,000 vs $600,000 — a $160,000 annual gap that is a serious budget line item. Developers running high-volume pipelines, automated classification, or batch summarization should weight this gap heavily. Those using the model interactively or in low-volume agentic workflows will barely notice it. One important caveat for o4 Mini: the payload flags that it uses reasoning tokens, requires a minimum of 1,000 max completion tokens, and needs high max_completion_tokens set — meaning real-world output costs may run higher than the base rate suggests if reasoning token consumption is significant.

Choose Grok 4.20 if:

• Your workflow involves constrained rewriting — copy that must hit exact character or word limits
• You need to process documents or contexts exceeding 200K tokens; Grok 4.20's 2M-token window is the only option between these two
• You want access to logprobs and top_logprobs parameters, which Grok 4.20 supports and o4 Mini does not per the payload
• Output cost is not a primary constraint at your current usage volume

Choose o4 Mini if:

• Math reasoning is central to your use case — 97.8% on MATH Level 5 and 81.7% on AIME 2025 (Epoch AI) make it a strong pick for STEM, tutoring, or quantitative analysis
• You're running at high output volume (10M+ tokens/month) and the $1.60/MTok output savings materially affect your budget
• Your context needs fit within 200K tokens, which covers the vast majority of applications
• You need temperature parameter control — note that o4 Mini does NOT list temperature in its supported parameters per the payload, while Grok 4.20 does; if temperature control matters to your prompting strategy, factor that in
• You're already in the OpenAI ecosystem and want to minimize integration overhead

The honest summary: On 11 of 12 internal benchmarks these models are indistinguishable. The decision comes down to constrained rewriting quality, context window size, math performance, and price.