Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | gpt-oss-120b (low) | Gemini 3 Pro Preview (high) |
|---|---|---|
| Input ($/M tokens) | $0.15 | $2 |
| Output ($/M tokens) | $0.54 | $12 |
Verdict. gpt-oss-120b (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 budget / mid-tier bracket for output-token pricing. At 0.0× the per-million-token cost, gpt-oss-120b (low) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). gpt-oss-120b (low) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. gpt-oss-120b (low) is strongest on Coding Index (21.2), Intelligence Index (14.9). Gemini 3 Pro Preview (high) leads on Intelligence Index (40.6).
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-oss-120b (low) costs $12.60 ($151/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-oss-120b (low) ≈ $1.83/run, Gemini 3 Pro Preview (high) ≈ $34.00/run. At agent/realtime scale (200M input / 100M output per million requests): gpt-oss-120b (low) ≈ $84/run, Gemini 3 Pro Preview (high) ≈ $1600/run. gpt-oss-120b (low) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
Recommendation. Benchmarks are too close to call (0-win swing) but Gemini 3 Pro Preview (high) is 22.2× more expensive per million output tokens. For most workloads the cheaper option (gpt-oss-120b (low)) wins on cost-quality tradeoff. Only pay the premium for Gemini 3 Pro Preview (high) if you have a measured lift on a task your product depends on.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
gpt-oss-120b (low) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.25/M tokens vs $4.50/M for Gemini 3 Pro Preview (high).
It's a tie — both models win 1 benchmarks each across 12 evaluated categories. See the detailed benchmark chart above for per-category results.
gpt-oss-120b (low) generates tokens faster at 227 tok/s vs — tok/s. gpt-oss-120b (low) also has lower time-to-first-token (0.91s vs —s).
Choose based on your priorities: gpt-oss-120b (low) for lower cost, both perform similarly on benchmarks, and gpt-oss-120b (low) for faster generation. For latency-sensitive apps, check the TTFT comparison above.