Model comparison 2026

Gemini 3.1 Pro vs Grok 4.3

Gemini 3.1 Pro
Google · Frontier · Proprietary
$5.00/1M · 1.0M ctx
Grok 4.3
xAI · Frontier · Proprietary
$1.63/1M · 1M ctx

Community vote

Pick a winner in each dimension. You can change your vote any time.

Output Quality

Correctness and depth of what it produces

Agentic Ability

Tool calls, instruction-following, and multi-step tasks

Speed

Tokens per second and time-to-first-token

Value for Money

How much capability you get per dollar

Reliability

Consistent results: fewer refusals, loops and format breaks

Specs and pricing side by side

Spec
Gemini 3.1 Pro
Grok 4.3
Maker
Google
xAI
Blended price / 1M
$5.00
$1.63
Input / output
$2.00 in · $12 out / 1M tokens
$1.25 in · $2.50 out / 1M tokens
Context window
1.0M
1M
Open weights
No
No
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
6.4
5.7
Agentic Ability
5.2
4.4
Speed
8.5
8.0
Value for Money
4.3
4.4
Reliability
8.5
8.4

Pricing and capabilities synced from the OpenRouter catalogue. Scores are editorial (0–10).

Verdict: Gemini 3.1 Pro or Grok 4.3?

Updated 2026-10-17

Choose Gemini 3.1 Pro if you want long multimodal inputs and Gemini CLI setups that still pin 3.1 Pro. Choose Grok 4.3 if you want simple, long-context calls in existing Grok setups.

In our editorial scoring, Gemini 3.1 Pro leads in 4 of five dimensions (output quality, agentic ability, speed and reliability), while Grok 4.3 leads in 1. On price, Gemini 3.1 Pro runs about $5.00 per 1M tokens (blended) and is proprietary; Grok 4.3 is about $1.63 and proprietary.

Where Gemini 3.1 Pro falls short
  • Gemini 3.8 Flash scores higher and costs about half as much per request
  • Prompts over 200K tokens bill at $4/$18 per million
Full Gemini 3.1 Pro breakdown →
Where Grok 4.3 falls short
  • Superseded by Grok 4.7, which scores far higher
  • 0% in Artificial Analysis's Terminal-Bench 4.0 run
Full Grok 4.3 breakdown →

Setting it up? Gemini 3.1 Pro: model ID, providers and agent config · Grok 4.3: model ID, providers and agent config

The agent matters as much as the model. Compare AI agents →

Every model on this page runs on Standard Compute

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