Google DeepMind

Gemini 3.1 Pro

Released Feb 11, 2026 · knowledge cutoff 2025-01

Status: Superseded
Location: United States / United Kingdom
Modality: Multimodal
Context window: 1M
Max output: 66K
Speed: —
Price ($/MTok in / out): $2 / $12
Cost per task: $0.29
Open weights: No

Benchmarks6 of 8 reported

GPQA Diamond

94.3%

SWE-bench Verified

80.6%

AIME (latest)

98.1%

Humanity's Last Exam

44.4%

LMArena Elo

1486

ARC-AGI-2

77.1%

MMLU-Pro

—

Terminal-Bench 2.1

—

Strengths & weaknesses

Strengths

Strong on genuinely novel problems rather than recalled ones
Coordinates several tools in one turn without losing track of which returned what
Direct and efficient by default — no preamble, no filler

Weaknesses

Wants the question placed after the data in long prompts, or it under-uses the context
Elaborate prompt scaffolding backfires — it over-analyses the prompt itself
Creative prose is competent but flat

Preview Feb 11, 2026; ARC-AGI-2 reported as 77.1 (76.5 in some sources). Knowledge cutoff Jan 2025 per DeepMind model page. AIME 98.1 is vals.ai-measured (third-party); MMLU-Pro not publicly reported.

For developers

API model strings

Not researched

Licence

Proprietary — weights not released

Retirement

No retirement announced

Lineage

No recorded predecessor