Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | GPT-5.6 Terra (medium) | Gemini 3.1 Pro Preview |
|---|---|---|
| Input ($/M tokens) | $2 | $2 |
| Output ($/M tokens) | $12 | $12 |
Verdict. Gemini 3.1 Pro Preview takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, Gemini 3.1 Pro Preview is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Gemini 3.1 Pro Preview makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. GPT-5.6 Terra (medium) is strongest on Coding Index (64.7), Intelligence Index (46.8). Gemini 3.1 Pro Preview leads on Coding Index (68.8), Intelligence Index (47.7).
Speed. Throughput is comparable — 98 tok/s vs 108 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.
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 (medium) costs $240.00 ($2880/year); Gemini 3.1 Pro Preview costs $240.00 ($2880/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5.6 Terra (medium) ≈ $34.00/run, Gemini 3.1 Pro Preview ≈ $34.00/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5.6 Terra (medium) ≈ $1600/run, Gemini 3.1 Pro Preview ≈ $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.
Gemini 3.1 Pro Preview wins 2 out of 12 benchmarks compared to 0 for GPT-5.6 Terra (medium). See the detailed benchmark chart above for per-category results.
Gemini 3.1 Pro Preview generates tokens faster at 108 tok/s vs 98 tok/s. GPT-5.6 Terra (medium) also has lower time-to-first-token (1.98s vs 32.45s).
Choose based on your priorities: both are similarly priced, Gemini 3.1 Pro Preview for stronger benchmark performance, and Gemini 3.1 Pro Preview for faster generation. For latency-sensitive apps, check the TTFT comparison above.