Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Gemma 4 26B A4B (Non-reasoning) | GPT-4.1 nano |
|---|---|---|
| Input ($/M tokens) | $0.13 | $0.1 |
| Output ($/M tokens) | $0.4 | $0.4 |
Verdict. Gemma 4 26B A4B (Non-reasoning) and GPT-4.1 nano 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 bracket for output-token pricing. At 1.0× the per-million-token cost, GPT-4.1 nano is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-4.1 nano makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Gemma 4 26B A4B (Non-reasoning) is strongest on Intelligence Index (13.1). GPT-4.1 nano leads on Coding Index (11.1), Intelligence Index (7.8).
Speed. On throughput, GPT-4.1 nano generates tokens at 187 tok/s versus 49 tok/s — about 74% faster. On time-to-first-token, GPT-4.1 nano responds in 720ms vs 1390ms, 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): Gemma 4 26B A4B (Non-reasoning) costs $9.90 ($119/year); GPT-4.1 nano costs $9.00 ($108/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Gemma 4 26B A4B (Non-reasoning) ≈ $1.45/run, GPT-4.1 nano ≈ $1.30/run. At agent/realtime scale (200M input / 100M output per million requests): Gemma 4 26B A4B (Non-reasoning) ≈ $66/run, GPT-4.1 nano ≈ $60/run. GPT-4.1 nano becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
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
GPT-4.1 nano is cheaper overall. Its blended price (3:1 input/output ratio) is $0.17/M tokens vs $0.20/M for Gemma 4 26B A4B (Non-reasoning).
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-4.1 nano generates tokens faster at 187 tok/s vs 49 tok/s. However, GPT-4.1 nano has lower time-to-first-token (0.72s vs 1.39s).
Choose based on your priorities: GPT-4.1 nano for lower cost, both perform similarly on benchmarks, and GPT-4.1 nano for faster generation. For latency-sensitive apps, check the TTFT comparison above.