Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Gemma 3 12B Instruct | GLM-4.5V (Non-reasoning) |
|---|---|---|
| Input ($/M tokens) | $0 | $0.6 |
| Output ($/M tokens) | $0 | $1.8 |
Verdict. Gemma 3 12B Instruct and GLM-4.5V (Non-reasoning) split the benchmark comparison evenly at 1–1. The tiebreaker here is price, speed, and what you actually run them on.
Pricing. Pricing varies significantly between these models — check the table above for the exact per-token rates. Many production workloads actually surface input-token cost (retrieval-augmented prompts, code-context windows), so factor both directions.
Strengths. Gemma 3 12B Instruct is strongest on Coding Index (5.8), Intelligence Index (5.5). GLM-4.5V (Non-reasoning) leads on Intelligence Index (6.8).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. Google and Z AI sell to overlapping but distinct developer audiences: Google tends to ship frontier reasoning models with premium positioning, while Z AI 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 3 12B Instruct costs $0.00 ($0/year); GLM-4.5V (Non-reasoning) costs $45.00 ($540/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Gemma 3 12B Instruct ≈ $0.00/run, GLM-4.5V (Non-reasoning) ≈ $6.60/run. At agent/realtime scale (200M input / 100M output per million requests): Gemma 3 12B Instruct ≈ $0/run, GLM-4.5V (Non-reasoning) ≈ $300/run. Gemma 3 12B Instruct 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
Gemma 3 12B Instruct is cheaper overall. Its blended price (3:1 input/output ratio) is $0.00/M tokens vs $0.90/M for GLM-4.5V (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.
GLM-4.5V (Non-reasoning) generates tokens faster at 92 tok/s vs — tok/s. However, GLM-4.5V (Non-reasoning) has lower time-to-first-token (1.85s vs —s).
Choose based on your priorities: Gemma 3 12B Instruct for lower cost, both perform similarly on benchmarks, and GLM-4.5V (Non-reasoning) for faster generation. For latency-sensitive apps, check the TTFT comparison above.