Gemma 3 vs Llama 2 70B Chat
Gemma 3 (2025) and Llama 2 70B Chat (2023) are compact production models from Google DeepMind and AI at Meta. Gemma 3 ships a not-yet-sourced context window, while Llama 2 70B Chat ships a 4K-token context window. On pricing, Gemma 3 costs $0.04/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Gemma 3 is ~1150% cheaper at $0.04/1M; pay for Llama 2 70B Chat only for provider fit.
Decision scorecard
Local evidence first| Signal | Gemma 3 | Llama 2 70B Chat |
|---|---|---|
| Decision fit | Classification and JSON / Tool use | Classification and JSON / Tool use |
| Context window | — | 4K |
| Cheapest output | $0.08/1M tokens | $1.5/1M tokens |
| Provider routes | 3 tracked | 14 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.
- Llama 2 70B Chat has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 2 70B Chat has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 2 70B Chat for 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
$52.00
Cheapest tracked route: OpenRouter
Llama 2 70B Chat
$775
Cheapest tracked route: Databricks Foundation Model Serving
Estimated monthly gap: $723. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- Llama 2 70B Chat is $1.42/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
- Gemma 3 is $1.42/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-03-12 | 2023-07-18 |
| Context window | — | 4K |
| Parameters | — | 70B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | 2025-01 | - |
Pricing and availability
| Pricing attribute | Gemma 3 | Llama 2 70B Chat |
|---|---|---|
| Input price | $0.04/1M tokens | $0.5/1M tokens |
| Output price | $0.08/1M tokens | $1.5/1M tokens |
| Providers |
Capabilities
| Capability | Gemma 3 | Llama 2 70B 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 lists $0.04/1M input and $0.08/1M output tokens, while Llama 2 70B Chat lists $0.5/1M input and $1.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 3 lower by about $0.75 per million blended tokens. Availability is 3 providers versus 14, so concentration risk also matters.
Choose Gemma 3 when provider fit and lower input-token cost are central to the workload. Choose Llama 2 70B 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. 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 70B Chat?
Gemma 3 is cheaper on tracked token pricing. Gemma 3 costs $0.04/1M input and $0.08/1M output tokens. Llama 2 70B Chat costs $0.5/1M input and $1.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemma 3 or Llama 2 70B Chat open source?
Gemma 3 is listed under Open Source. Llama 2 70B 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 or Llama 2 70B Chat?
Both Gemma 3 and Llama 2 70B 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 and Llama 2 70B Chat?
Gemma 3 is available on OpenRouter, Google AI Studio, and GCP Vertex AI. Llama 2 70B Chat is available on Databricks Foundation Model Serving, Microsoft Foundry, GCP Vertex AI, Alibaba Cloud PAI-EAS, and AWS Bedrock. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 3 over Llama 2 70B Chat?
Gemma 3 is ~1150% cheaper at $0.04/1M; pay for Llama 2 70B Chat 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 70B Chat.
Continue comparing
Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.