Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Gemini 3.1 Pro Preview | GPT-5.6 Terra (high) |
|---|---|---|
| Input ($/M tokens) | $2 | $2 |
| Output ($/M tokens) | $12 | $12 |
Verdict. Gemini 3.1 Pro Preview and GPT-5.6 Terra (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, GPT-5.6 Terra (high) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-5.6 Terra (high) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Gemini 3.1 Pro Preview is strongest on Coding Index (68.8), Intelligence Index (47.7). GPT-5.6 Terra (high) leads on Coding Index (67.1), Intelligence Index (50.1).
Speed. On throughput, Gemini 3.1 Pro Preview generates tokens at 111 tok/s versus 84 tok/s — about 24% faster. On time-to-first-token, GPT-5.6 Terra (high) responds in 2920ms vs 27320ms, which matters most for chat-style UIs.
Provider. Google and OpenAI sell to overlapping but distinct developer audiences: Google tends to ship frontier reasoning models with premium positioning, while OpenAI 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): Gemini 3.1 Pro Preview costs $240.00 ($2880/year); GPT-5.6 Terra (high) costs $240.00 ($2880/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Gemini 3.1 Pro Preview ≈ $34.00/run, GPT-5.6 Terra (high) ≈ $34.00/run. At agent/realtime scale (200M input / 100M output per million requests): Gemini 3.1 Pro Preview ≈ $1600/run, GPT-5.6 Terra (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
Data from Artificial Analysis API — 12 benchmarks
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
Gemini 3.1 Pro Preview generates tokens faster at 111 tok/s vs 84 tok/s. However, GPT-5.6 Terra (high) has lower time-to-first-token (2.92s vs 27.32s).
Choose based on your priorities: both are similarly priced, both perform similarly on benchmarks, and Gemini 3.1 Pro Preview for faster generation. For latency-sensitive apps, check the TTFT comparison above.