Gemma 3 12B vs Llama 2 7B
Gemma 3 12B (2026) and Llama 2 7B (2023) are compact production models from Google DeepMind and AI at Meta. Gemma 3 12B ships a 33K-token context window, while Llama 2 7B ships a 4K-token context window. On pricing, Gemma 3 12B 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 12B is ~400% cheaper at $0.04/1M; pay for Llama 2 7B only for provider fit.
Decision scorecard
Local evidence first| Signal | Gemma 3 12B | Llama 2 7B |
|---|---|---|
| Decision fit | Classification and JSON / Tool use | Coding and Classification |
| Context window | 33K | 4K |
| Cheapest output | $0.13/1M tokens | $0.2/1M tokens |
| Provider routes | 3 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Gemma 3 12B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Gemma 3 12B has the lower cheapest tracked output price at $0.13/1M tokens.
- Gemma 3 12B has broader tracked provider coverage for fallback and procurement flexibility.
- Gemma 3 12B uniquely exposes Structured outputs in local model data.
- Local decision data tags Gemma 3 12B for Classification and JSON / Tool use.
- 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 12B
$64.50
Cheapest tracked route: OpenRouter
Llama 2 7B
$210
Cheapest tracked route: Fireworks AI
Estimated monthly gap: $146. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Gemma 3 12B and Llama 2 7B; plan for SDK, billing, or endpoint changes.
- Llama 2 7B is $0.07/1M 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 12B; plan for SDK, billing, or endpoint changes.
- Gemma 3 12B is $0.07/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Gemma 3 12B adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-01-01 | 2023-07-18 |
| Context window | 33K | 4K |
| Parameters | — | 7B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | 2024-08 | 2022-09 |
Pricing and availability
| Pricing attribute | Gemma 3 12B | Llama 2 7B |
|---|---|---|
| Input price | $0.04/1M tokens | $0.2/1M tokens |
| Output price | $0.13/1M tokens | $0.2/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 3 12B | 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 12B. 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 12B lists $0.04/1M input and $0.13/1M 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 12B lower by about $0.13 per million blended tokens. Availability is 3 providers versus 1, so concentration risk also matters.
Choose Gemma 3 12B when long-context analysis, larger context windows, and lower input-token cost 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 has a larger context window, Gemma 3 12B or Llama 2 7B?
Gemma 3 12B supports 33K tokens, while Llama 2 7B supports 4K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemma 3 12B or Llama 2 7B?
Gemma 3 12B is cheaper on tracked token pricing. Gemma 3 12B costs $0.04/1M input and $0.13/1M 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 12B or Llama 2 7B open source?
Gemma 3 12B 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 12B or Llama 2 7B?
Gemma 3 12B 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 12B and Llama 2 7B?
Gemma 3 12B is available on AWS Bedrock, OpenRouter, 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 12B over Llama 2 7B?
Gemma 3 12B is ~400% cheaper at $0.04/1M; pay for Llama 2 7B only for provider fit. If your workload also depends on long-context analysis, start with Gemma 3 12B; if it depends on provider fit, run the same evaluation with Llama 2 7B.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.