Gemma 3 vs GPT-4 Turbo Preview
Gemma 3 (2025) and GPT-4 Turbo Preview (2023) are compact production models from Google DeepMind and OpenAI. Gemma 3 ships a not-yet-sourced context window, while GPT-4 Turbo Preview ships a 128K-token context window. On pricing, Gemma 3 costs $0.04/1M input tokens versus $10/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.
Gemma 3 is ~24900% cheaper at $0.04/1M; pay for GPT-4 Turbo Preview only for coding workflow support.
Decision scorecard
Local evidence first| Signal | Gemma 3 | GPT-4 Turbo Preview |
|---|---|---|
| Best for | provider-routed production | multimodal apps and provider-routed production |
| Decision fit | Classification and JSON / Tool use | Coding, RAG, and Agents |
| Context window | — | 128K |
| Cheapest output | $0.08/1M tokens | $30/1M tokens |
| Provider routes | 3 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 3 has the lower cheapest tracked output price at $0.08/1M tokens.
- Local decision data tags Gemma 3 for Classification and JSON / Tool use.
- GPT-4 Turbo Preview has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-4 Turbo Preview uniquely exposes Vision and Code execution in local model data.
- Local decision data tags GPT-4 Turbo Preview for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemma 3
$52.00
Cheapest tracked route/tier: OpenRouter
GPT-4 Turbo Preview
$15,500
Cheapest tracked route/tier: OpenAI API
Estimated monthly gap: $15,448. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-4 Turbo Preview is $29.92/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-4 Turbo Preview adds Vision and Code execution in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Gemma 3 is $29.92/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision and Code execution before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-03-12 | 2023-11-06 |
| Context window | — | 128K |
| Parameters | — | 1.76T (8x222B MoE)* |
| Architecture | decoder only | mixture of experts |
| License | Open Source | Proprietary |
| Knowledge cutoff | 2025-01 | 2023-12 |
Pricing and availability
| Pricing attribute | Gemma 3 | GPT-4 Turbo Preview |
|---|---|---|
| Input price | $0.04/1M tokens | $10/1M tokens |
| Output price | $0.08/1M tokens | $30/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 3 | GPT-4 Turbo Preview |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | Yes |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GPT-4 Turbo Preview and code execution: GPT-4 Turbo Preview. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Gemma 3 lists $0.04/1M input and $0.08/1M output tokens on the cheapest tracked provider, while GPT-4 Turbo Preview lists $10/1M input and $30/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 3 lower by about $15.95 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.
Choose Gemma 3 when provider fit and lower input-token cost are central to the workload. Choose GPT-4 Turbo Preview when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which is cheaper, Gemma 3 or GPT-4 Turbo Preview?
Gemma 3 is cheaper on tracked token pricing. Gemma 3 costs $0.04/1M input and $0.08/1M output tokens. GPT-4 Turbo Preview costs $10/1M input and $30/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemma 3 or GPT-4 Turbo Preview open source?
Gemma 3 is listed under Open Source. GPT-4 Turbo Preview is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Gemma 3 or GPT-4 Turbo Preview?
GPT-4 Turbo Preview has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for structured outputs, Gemma 3 or GPT-4 Turbo Preview?
Both Gemma 3 and GPT-4 Turbo Preview expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for code execution, Gemma 3 or GPT-4 Turbo Preview?
GPT-4 Turbo Preview has the clearer documented code execution signal in this comparison. If code execution is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Gemma 3 and GPT-4 Turbo Preview?
Gemma 3 is available on OpenRouter, Google AI Studio, and GCP Vertex AI. GPT-4 Turbo Preview is available on OpenAI API, Azure OpenAI, and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.