Gemini 3.1 Pro vs Kimi K2: Benchmarks, Pricing & Capabilities Compared
TL;DR — Gemini 3.1 Pro wins for coding + reasoning · Kimi K2 wins for cost.
Gemini 3.1 Pro Google
- Released
- 2026-02-19
- Context window
- 2M tokens
- Input price
- $2.50 / Mtok
- Output price
- $10.00 / Mtok
Key features
- 2x reasoning improvement
- ARC-AGI-2 score of 77.1%
- Enhanced multimodal understanding
Kimi K2 Moonshot AI
- Released
- 2026-01-20
- Context window
- 2M tokens
- Input price
- $0.15 / Mtok
- Output price
- $2.50 / Mtok
Key features
- First open-weight model #1 on LMSYS Chatbot Arena
- 1.04 trillion parameters
- K2.5 agent swarms with up to 100 sub-agents
Benchmark comparison
| Benchmark | Gemini 3.1 Pro | Kimi K2 |
|---|---|---|
| GPQA Diamond | 84.2% ✓ | 74.1% |
| LiveCodeBench | 78.9% ✓ | 68.9% |
| SWE-bench Verified | 72.3% ✓ | 65.8% |
Pricing comparison
| Metric | Gemini 3.1 Pro | Kimi K2 |
|---|---|---|
| Input ($/Mtok) | $2.50 | $0.15 |
| Output ($/Mtok) | $10.00 | $2.50 |
| Cached input ($/Mtok) | $0.25 | — |
| Cost per 1M-token roundtrip (1M in + 1M out) | $12.50 | $2.65 |
Context window & modalities
| Attribute | Gemini 3.1 Pro | Kimi K2 |
|---|---|---|
| Context window | 2M tokens | 2M tokens |
| Input modalities | text, image, audio, video, PDF | text, image |
| Output modalities | text | text |
| Knowledge cutoff | 2025-12 | 2025-10 |
Verdict by use case
Coding
→ Gemini 3.1 Pro
Basis: SWE-bench
Gemini 3.1 Pro 72.3% vs Kimi K2 65.8% on SWE-bench.
Reasoning
→ Gemini 3.1 Pro
Basis: GPQA Diamond
Gemini 3.1 Pro 84.2% vs Kimi K2 74.1% on GPQA Diamond.
Math
Insufficient data
Basis: MATH / AIME
No shared math benchmark.
Long context
Tie
Basis: Context window
Gemini 3.1 Pro 2M tokens vs Kimi K2 2M tokens.
Cost
→ Kimi K2
Basis: Input $/Mtok
Gemini 3.1 Pro $2.5/Mtok vs Kimi K2 $0.15/Mtok input.
Changelog & releases
Gemini 3.1 Pro
Released 2026-02-19
Predecessor: google-gemini-3-pro
- 2x reasoning score on ARC-AGI-2 vs Gemini 3 Pro
- Context window expanded to 2M tokens
- Deep Think mode enabled by default on the Pro tier
- Lower latency on first-token despite larger context
Kimi K2
Released 2026-01-20
Predecessor: moonshot-ai-moonshot-kimi
- 2M token context window (20x vs first Kimi)
- Agentic tool-use tuning via MuonClip optimizer
- Open weights under modified MIT