Gemini 2.5 Pro vs Grok 4.20

Across our 12-test internal benchmark suite, Grok 4.20 wins 2 categories, Gemini 2.5 Pro wins 1, and 9 are tied. Neither model dominates — this is a close matchup at the top of the market.

Where Grok 4.20 wins:

• Strategic analysis: Grok 4.20 scores 5/5 (tied for 1st among 54 models with 25 others) vs Gemini 2.5 Pro's 4/5 (rank 27 of 54, tied with 8 others). For tasks involving nuanced tradeoff reasoning with real numbers — competitive analysis, financial modeling decisions, policy evaluation — Grok 4.20 has a meaningful edge.
• Constrained rewriting: Grok 4.20 scores 4/5 (rank 6 of 53) vs Gemini 2.5 Pro's 3/5 (rank 31 of 53). Compression within hard character limits — ad copy, headlines, social posts — is notably better on Grok 4.20. Gemini 2.5 Pro sits below the field median on this test.

Where Gemini 2.5 Pro wins:

• Creative problem-solving: Gemini 2.5 Pro scores 5/5 (tied for 1st among 54 models with 7 others) vs Grok 4.20's 4/5 (rank 9 of 54, tied with 20 others). For generating non-obvious, specific, and feasible ideas — brainstorming, design thinking, novel solution generation — Gemini 2.5 Pro is measurably stronger.

Where they tie (9 of 12 tests):

• Structured output: both 5/5, tied for 1st among 54 models. JSON schema compliance is a non-issue with either model.
• Tool calling: both 5/5, tied for 1st among 54 models. Both handle function selection, argument accuracy, and sequencing at the highest level — critical for agentic and API-connected workflows.
• Faithfulness: both 5/5, tied for 1st among 55 models. Neither model hallucinates away from source material in our tests.
• Long context: both 5/5, tied for 1st among 55 models. Retrieval accuracy at 30K+ tokens is maxed out on both — though Grok 4.20's 2M context window gives it more headroom in practice.
• Classification: both 4/5, tied for 1st among 53 models.
• Persona consistency: both 5/5, tied for 1st among 53 models.
• Multilingual: both 5/5, tied for 1st among 55 models.
• Agentic planning: both 4/5, rank 16 of 54.
• Safety calibration: both 1/5, rank 32 of 55. This is a shared weakness — both models score well below the field median (p50 = 2) on refusing harmful requests while permitting legitimate ones. Teams with strict safety requirements should factor this in.

External benchmarks (Epoch AI): Gemini 2.5 Pro has external benchmark data available. On SWE-bench Verified (real GitHub issue resolution), it scores 57.6% — ranking 10th of 12 models with this data in our set, below the p50 of 70.8% among scored models. On AIME 2025 (math olympiad problems), it scores 84.2% — ranking 11th of 23 models, near the p50 of 83.9%. These scores place Gemini 2.5 Pro as a capable but not leading model on autonomous coding and competition math by external measures. No SWE-bench or AIME data is available in our payload for Grok 4.20, so a direct external comparison cannot be made.

Gemini 2.5 Pro charges $1.25/M input tokens and $10.00/M output tokens. Grok 4.20 charges $2.00/M input tokens and $6.00/M output tokens. The crossover point matters enormously here.

At 1M tokens/month with a typical 1:3 input-to-output ratio (250K input, 750K output): Gemini 2.5 Pro costs roughly $0.31 (input) + $7.50 (output) = $7.81. Grok 4.20 costs roughly $0.50 (input) + $4.50 (output) = $5.00. Grok wins by ~$2.80.

At 10M tokens/month (same ratio): Gemini 2.5 Pro ≈ $78.13 vs Grok 4.20 ≈ $50.00 — a $28 monthly gap in Grok's favor.

At 100M tokens/month: Gemini 2.5 Pro ≈ $781 vs Grok 4.20 ≈ $500 — Grok saves ~$281/month.

However, flip the ratio: at 3:1 input-to-output (retrieval-heavy or classification pipelines), Gemini 2.5 Pro's cheaper input cost narrows or reverses the gap. Teams running classification, RAG, or document-triage pipelines where output is short will find Gemini 2.5 Pro more cost-efficient. Teams generating long completions — code, reports, summaries — will pay less with Grok 4.20 at scale.

One context-window note: Grok 4.20 supports a 2,000,000-token context window vs Gemini 2.5 Pro's 1,048,576. If you need to feed very large corpora in a single prompt, Grok 4.20 is the only option here, regardless of price.

Choose Gemini 2.5 Pro if:

• Creative problem-solving is your primary workload — brainstorming, ideation, novel solution generation. It's the only test where it outscores Grok 4.20 (5 vs 4).
• Your pipeline is input-heavy relative to output (e.g., classification, RAG, document routing). The $1.25/M input rate beats Grok 4.20's $2.00/M when you're ingesting far more than you're generating.
• You need multimodal input beyond images — Gemini 2.5 Pro supports audio and video ingestion in addition to text, images, and files, per our payload data.
• You want reasoning token transparency — Gemini 2.5 Pro's include_reasoning parameter with uses_reasoning_tokens: true quirk means you can inspect its thinking process.

Choose Grok 4.20 if:

• Strategic analysis and constrained rewriting are core to your use case — it outscores Gemini 2.5 Pro on both (5 vs 4, and 4 vs 3 respectively).
• Your workload is output-heavy (long code completions, reports, summaries). At a 1:3 input-to-output ratio and 10M tokens/month, Grok 4.20 saves roughly $28/month vs Gemini 2.5 Pro — and scales linearly from there.
• You need a context window larger than 1M tokens. Grok 4.20's 2M token context window is the only option in this matchup for very large document sets.
• You want logprobs and top_logprobs support for probabilistic output analysis — these parameters are available on Grok 4.20 but not listed for Gemini 2.5 Pro in our data.