Gemma 3 vs Llama 2 7B
Gemma 3 (2025) and Llama 2 7B (2023) are compact production models from Google DeepMind and AI at Meta. Gemma 3 ships a not-yet-sourced context window, while Llama 2 7B ships a 4K-token context window. On pricing, Gemma 3 costs $0.04/1M input tokens versus $0.2/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Gemma 3 is ~400% cheaper at $0.04/1M; pay for Llama 2 7B only for provider fit.
Decision scorecard
Local evidence first| Signal | Gemma 3 | Llama 2 7B |
|---|---|---|
| Decision fit | Classification and JSON / Tool use | Coding and Classification |
| Context window | — | 4K |
| Cheapest output | $0.08/1M tokens | $0.2/1M tokens |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 3 has the lower cheapest tracked output price at $0.08/1M tokens.
- Gemma 3 has broader tracked provider coverage for fallback and procurement flexibility.
- Gemma 3 uniquely exposes Structured outputs in local model data.
- Local decision data tags Gemma 3 for Classification and JSON / Tool use.
- Llama 2 7B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Llama 2 7B for Coding and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Gemma 3
$52.00
Cheapest tracked route: OpenRouter
Llama 2 7B
$210
Cheapest tracked route: Fireworks AI
Estimated monthly gap: $158. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Gemma 3 and Llama 2 7B; plan for SDK, billing, or endpoint changes.
- Llama 2 7B is $0.12/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Llama 2 7B and Gemma 3; plan for SDK, billing, or endpoint changes.
- Gemma 3 is $0.12/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Gemma 3 adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-03-12 | 2023-07-18 |
| Context window | — | 4K |
| Parameters | — | 7B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | 2025-01 | 2022-09 |
Pricing and availability
| Pricing attribute | Gemma 3 | Llama 2 7B |
|---|---|---|
| Input price | $0.04/1M tokens | $0.2/1M tokens |
| Output price | $0.08/1M tokens | $0.2/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 3 | Llama 2 7B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on structured outputs: Gemma 3. Both models share the core language-model surface, 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, while Llama 2 7B lists $0.2/1M input and $0.2/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 3 lower by about $0.15 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.
Choose Gemma 3 when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Llama 2 7B when provider fit 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which is cheaper, Gemma 3 or Llama 2 7B?
Gemma 3 is cheaper on tracked token pricing. Gemma 3 costs $0.04/1M input and $0.08/1M output tokens. Llama 2 7B costs $0.2/1M input and $0.2/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemma 3 or Llama 2 7B open source?
Gemma 3 is listed under Open Source. Llama 2 7B is listed under Open Source. 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 structured outputs, Gemma 3 or Llama 2 7B?
Gemma 3 has the clearer documented structured outputs signal in this comparison. If structured outputs 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 Llama 2 7B?
Gemma 3 is available on OpenRouter, Google AI Studio, and GCP Vertex AI. Llama 2 7B is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 3 over Llama 2 7B?
Gemma 3 is ~400% cheaper at $0.04/1M; pay for Llama 2 7B only for provider fit. If your workload also depends on provider fit, start with Gemma 3; if it depends on provider fit, run the same evaluation with Llama 2 7B.
Continue comparing
Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.