Gemma 3 12B vs Llama 2 13B Chat
Gemma 3 12B (2026) and Llama 2 13B Chat (2023) are compact production models from Google DeepMind and AI at Meta. Gemma 3 12B ships a 33K-token context window, while Llama 2 13B Chat ships a 4K-token context window. On pricing, Gemma 3 12B costs $0.04/1M input tokens versus $0.1/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Gemma 3 12B is ~150% cheaper at $0.04/1M; pay for Llama 2 13B Chat only for provider fit.
Decision scorecard
Local evidence first| Signal | Gemma 3 12B | Llama 2 13B Chat |
|---|---|---|
| Decision fit | Classification and JSON / Tool use | Coding, Classification, and JSON / Tool use |
| Context window | 33K | 4K |
| Cheapest output | $0.13/1M tokens | $0.5/1M tokens |
| Provider routes | 3 tracked | 12 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.
- Local decision data tags Gemma 3 12B for Classification and JSON / Tool use.
- Llama 2 13B Chat has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 2 13B Chat for Coding, Classification, and JSON / Tool use.
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 13B Chat
$205
Cheapest tracked route: Replicate API
Estimated monthly gap: $141. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on AWS Bedrock and GCP Vertex AI; start route-level A/B tests there.
- Llama 2 13B Chat is $0.37/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Provider overlap exists on AWS Bedrock and GCP Vertex AI; start route-level A/B tests there.
- Gemma 3 12B is $0.37/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-01-01 | 2023-07-18 |
| Context window | 33K | 4K |
| Parameters | — | 13B |
| 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 13B Chat |
|---|---|---|
| Input price | $0.04/1M tokens | $0.1/1M tokens |
| Output price | $0.13/1M tokens | $0.5/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 3 12B | Llama 2 13B Chat |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint is close: both models cover structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.
For cost, Gemma 3 12B lists $0.04/1M input and $0.13/1M output tokens, while Llama 2 13B Chat lists $0.1/1M input and $0.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 3 12B lower by about $0.15 per million blended tokens. Availability is 3 providers versus 12, 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 13B Chat when provider fit and broader provider choice 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 has a larger context window, Gemma 3 12B or Llama 2 13B Chat?
Gemma 3 12B supports 33K tokens, while Llama 2 13B Chat 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 13B Chat?
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 13B Chat costs $0.1/1M input and $0.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemma 3 12B or Llama 2 13B Chat open source?
Gemma 3 12B is listed under Open Source. Llama 2 13B Chat 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 13B Chat?
Both Gemma 3 12B and Llama 2 13B Chat expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Gemma 3 12B and Llama 2 13B Chat?
Gemma 3 12B is available on AWS Bedrock, OpenRouter, and GCP Vertex AI. Llama 2 13B Chat is available on Alibaba Cloud PAI-EAS, AWS Bedrock, Microsoft Foundry, GCP Vertex AI, and Cloudflare Workers AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 3 12B over Llama 2 13B Chat?
Gemma 3 12B is ~150% cheaper at $0.04/1M; pay for Llama 2 13B Chat 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 13B Chat.
Continue comparing
Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.