AI Flash Report

DeepSeek V3.2 vs Gemini 3.1 Pro: Benchmarks, Pricing & Capabilities Compared

TL;DR — DeepSeek V3.2 wins for cost · Gemini 3.1 Pro wins for reasoning + long-context.

DeepSeek V3.2 DeepSeek
Released
2026-02-12
Context window
1M tokens
Input price
$0.27 / Mtok
Output price
$1.10 / Mtok
Key features
  • 1M+ token context window (10x expansion)
  • Improved reasoning capabilities
  • Open source release
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

Benchmark comparison

Benchmark DeepSeek V3.2 Gemini 3.1 Pro
LiveCodeBench 72.1% 78.9%
MATH 85.6% 89.4%

Pricing comparison

Metric DeepSeek V3.2 Gemini 3.1 Pro
Input ($/Mtok) $0.27 $2.50
Output ($/Mtok) $1.10 $10.00
Cached input ($/Mtok) $0.07 $0.25
Cost per 1M-token roundtrip (1M in + 1M out) $1.37 $12.50

Context window & modalities

Attribute DeepSeek V3.2 Gemini 3.1 Pro
Context window 1M tokens 2M tokens
Input modalities text text, image, audio, video, PDF
Output modalities text text
Knowledge cutoff 2025-09 2025-12

Verdict by use case

Coding
→ Gemini 3.1 Pro
Basis: LiveCodeBench

DeepSeek V3.2 72.1% vs Gemini 3.1 Pro 78.9% on LiveCodeBench.

Reasoning
→ Gemini 3.1 Pro
Basis: GPQA Diamond

DeepSeek V3.2 68.4% vs Gemini 3.1 Pro 84.2% on GPQA Diamond.

Math
→ Gemini 3.1 Pro
Basis: MATH

DeepSeek V3.2 85.6% vs Gemini 3.1 Pro 89.4% on MATH.

Long context
→ Gemini 3.1 Pro
Basis: Context window

DeepSeek V3.2 1M tokens vs Gemini 3.1 Pro 2M tokens.

Cost
→ DeepSeek V3.2
Basis: Input $/Mtok

DeepSeek V3.2 $0.27/Mtok vs Gemini 3.1 Pro $2.5/Mtok input.

Changelog & releases

DeepSeek V3.2
Released 2026-02-12
Predecessor: deepseek-deepseek-v3
  • 10x context window expansion (128K → 1M+ tokens)
  • Sliding-window attention for long-context throughput
  • Improved chain-of-thought reasoning
  • Native FP8 inference support
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

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