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Compare/GPT-5.6 Terra (low) vs Gemini 3 Pro Preview (high)

GPT-5.6 Terra (low)vsGemini 3 Pro Preview (high)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

OpenAI

GPT-5.6 Terra (low)

Input
$2/M
Output
$12/M
Speed
95 tok/s
TTFT
1.53s
Google

Gemini 3 Pro Preview (high)

Input
$2/M
Output
$12/M
Speed
—
TTFT
—

Winner by Category

Cheaper
Tie
Faster (tok/s)
GPT-5.6 Terra (low)
Lower Latency
GPT-5.6 Terra (low)
Benchmarks (1-1)
Tie

Pricing Comparison

MetricGPT-5.6 Terra (low)Gemini 3 Pro Preview (high)
Input ($/M tokens)$2$2
Output ($/M tokens)$12$12
Cost for 1M input + 100K output tokens:
GPT-5.6 Terra (low)$3.20
Gemini 3 Pro Preview (high)$3.20

Speed Comparison

Output Speed (tokens/s) — higher is better
GPT-5.6 Terra (low)
95 tok/s
Gemini 3 Pro Preview (high)
—
Time to First Token (seconds) — lower is better
GPT-5.6 Terra (low)
1.53s
Gemini 3 Pro Preview (high)
—

Editorial Analysis

Verdict. GPT-5.6 Terra (low) and Gemini 3 Pro Preview (high) split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.

Pricing. Both models sit in the mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, Gemini 3 Pro Preview (high) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Gemini 3 Pro Preview (high) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. GPT-5.6 Terra (low) is strongest on Coding Index (58.1), Intelligence Index (27.9). Gemini 3 Pro Preview (high) leads on Intelligence Index (28.0).

Speed. Speed data is incomplete for this pair; benchmark and price should decide.

Provider. OpenAI and Google sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Google often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): GPT-5.6 Terra (low) costs $240.00 ($2880/year); Gemini 3 Pro Preview (high) costs $240.00 ($2880/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5.6 Terra (low) ≈ $34.00/run, Gemini 3 Pro Preview (high) ≈ $34.00/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5.6 Terra (low) ≈ $1600/run, Gemini 3 Pro Preview (high) ≈ $1600/run.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Head-to-head deltas

  • Benchmark wins tie exactly at 1–1. The tiebreaker on raw benchmark parity will be price, speed, or capability coverage.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
27.928.0
Coding Index
58.1—
Math Index
——
GPQA Diamond
——
MMLU-Pro
——
LiveCodeBench
——
AIME 2025
——
MATH-500
——
Humanity's Last Exam
——
SciCode
——
IFBench
——
TerminalBench
——
GPT-5.6 Terra (low)1 wins
1 winsGemini 3 Pro Preview (high)

Frequently Asked Questions

Which is cheaper, GPT-5.6 Terra (low) or Gemini 3 Pro Preview (high)?

Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.

Which model performs better on benchmarks?

It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

GPT-5.6 Terra (low) generates tokens faster at 95 tok/s vs — tok/s. GPT-5.6 Terra (low) also has lower time-to-first-token (1.53s vs —s).

When should I use GPT-5.6 Terra (low) vs Gemini 3 Pro Preview (high)?

Choose based on your priorities: both are similarly priced, both perform similarly on benchmarks, and GPT-5.6 Terra (low) for faster generation. For latency-sensitive apps, check the TTFT comparison above.