Gemma 3 12B vs Llama 3.1 Swallow 70B Instruct
Gemma 3 12B (2026) and Llama 3.1 Swallow 70B Instruct (2025) are compact production models from Google DeepMind and Tokyo Institute of Technology. Gemma 3 12B ships a 33k-token context window, while Llama 3.1 Swallow 70B Instruct ships a 4k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Gemma 3 12B fits 8x more tokens; pick it for long-context work and Llama 3.1 Swallow 70B Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | Gemma 3 12B | Llama 3.1 Swallow 70B Instruct |
|---|---|---|
| Best for | provider-routed production | general production evaluation |
| Decision fit | Classification and JSON / Tool use | General |
| Context window | 33k | 4k |
| Cheapest output | $0.13/1M tokens | - |
| Provider routes | 5 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 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.
- Use Llama 3.1 Swallow 70B Instruct when your own prompt tests beat the comparison signals; the local data does not show a decisive standalone advantage yet.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Gemma 3 12B
$64.50
Cheapest tracked route/tier: OpenRouter
Llama 3.1 Swallow 70B Instruct
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Gemma 3 12B and Llama 3.1 Swallow 70B Instruct; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- No overlapping tracked provider route is sourced for Llama 3.1 Swallow 70B Instruct and Gemma 3 12B; plan for SDK, billing, or endpoint changes.
- Gemma 3 12B adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-01-01 | 2025-01-01 |
| Context window | 33k | 4k |
| Parameters | 12B | 70B |
| Architecture | decoder only | decoder only |
| License | Gemma | Llama 2 Community |
| Openness | Open weights | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2024-08 | 2023 |
Pricing and availability
| Pricing attribute | Gemma 3 12B | Llama 3.1 Swallow 70B Instruct |
|---|---|---|
| Input price | $0.04/1M tokens | - |
| Output price | $0.13/1M tokens | - |
| Providers |
Capabilities
| Capability | Gemma 3 12B | Llama 3.1 Swallow 70B Instruct |
|---|---|---|
| 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 |
| 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 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.
Pricing coverage is uneven: Gemma 3 12B has $0.04/1M input tokens and Llama 3.1 Swallow 70B Instruct has no token price sourced yet. Provider availability is 5 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Gemma 3 12B when long-context analysis, larger context windows, and broader provider choice are central to the workload. Choose Llama 3.1 Swallow 70B Instruct 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 3.1 Swallow 70B Instruct?
Gemma 3 12B supports 33k tokens, while Llama 3.1 Swallow 70B Instruct supports 4k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Gemma 3 12B or Llama 3.1 Swallow 70B Instruct open source?
Gemma 3 12B is listed under Gemma. Llama 3.1 Swallow 70B Instruct is listed under Llama 2 Community. 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 3.1 Swallow 70B Instruct?
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 3.1 Swallow 70B Instruct?
Gemma 3 12B is available on Cloudflare Workers AI, AWS Bedrock, OpenRouter, GCP Vertex AI, and Novita AI. Llama 3.1 Swallow 70B Instruct is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Gemma 3 12B over Llama 3.1 Swallow 70B Instruct?
Gemma 3 12B fits 8x more tokens; pick it for long-context work and Llama 3.1 Swallow 70B Instruct for tighter calls. 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 3.1 Swallow 70B Instruct.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.