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Gemini 3.1 Pro vs LongCat 2.0
Gemini 3.1 Pro (Google DeepMind) and LongCat 2.0 (Meituan) compared on benchmarks, pricing, context window, and use-case rankings.
- Gemini 3.1 Pro ranks higher for coding (67th vs 12th percentile).
| Attribute | Gemini 3.1 Pro | LongCat 2.0 |
|---|---|---|
| Scores | ||
| Intelligence (ECI) | 155 | — |
| Coding | 67 | 12 |
| Math | 74 | — |
| Reasoning & Knowledge | 95 | 41 |
| Agentic & Tools | 88 | — |
| Specifications | ||
| Developer | Google DeepMind | Meituan |
| Family | Gemini | — |
| Released | Feb 19, 2026 | Jul 20, 2026 |
| Parameters | — | — |
| Availability | API access | — |
| Context window | — | 1M |
| Price — $/M input | — | $0.30 |
| Price — $/M output | — | $1.20 |
| Inputs | — | text |
| Outputs | — | text |
| Benchmarks | ||
| AIME 2024/2025 | 96% | — |
| APEX | 34% | — |
| ARC-AGI | 98% | — |
| ARC-AGI-2 | 77% | — |
| FrontierMath | 37% | — |
| FrontierMath Tier 4 | 17% | — |
| GPQA Diamond | 94% | 78% |
| GSO (code optimization) | 23% | — |
| Humanity's Last Exam | 46% | 32% |
| METR task horizon | 6.4 h | — |
| SimpleBench | 80% | — |
| SimpleQA Verified | 77% | — |
| SWE-bench Verified | 76% | — |
| Terminal-Bench | 80% | — |
| WebDev Arena | 1461 | — |
| WeirdML | 72% | — |
| SciCode | — | 35% |
Use-case scores are 0–100 percentile composites across each area’s benchmarks, ranked against every model from the past year. Highlighted cells lead each row. Open a model for the full picture.
Frequently asked questions
Which is better for coding, Gemini 3.1 Pro or LongCat 2.0?
Across coding benchmarks like SWE-bench Verified and Terminal-Bench, Gemini 3.1 Pro ranks higher — 67th vs 12th percentile among the models tracked on Model Beat.
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Benchmarks & model data from Epoch AI (CC BY); pricing & specs from OpenRouter. ECI = Epoch Capabilities Index.