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Gemma 3 12B (free) vs Llama 3.1 8B Instruct

Gemma 3 12B (free) (2026) and Llama 3.1 8B Instruct (2024) are compact production models from Google DeepMind and AI at Meta. Gemma 3 12B (free) ships a 33K-token context window, while Llama 3.1 8B Instruct ships a 128K-token context window. On pricing, Llama 3.1 8B Instruct costs $0.02/1M input tokens versus $0.04/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Llama 3.1 8B Instruct is ~100% cheaper at $0.02/1M; pay for Gemma 3 12B (free) only for provider fit.

Decision scorecard

Local evidence first
SignalGemma 3 12B (free)Llama 3.1 8B Instruct
Decision fitClassification and JSON / Tool useRAG, Long context, and Classification
Context window33K128K
Cheapest output$0.13/1M tokens$0.05/1M tokens
Provider routes3 tracked12 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Gemma 3 12B (free) when...
  • Local decision data tags Gemma 3 12B (free) for Classification and JSON / Tool use.
Choose Llama 3.1 8B Instruct when...
  • Llama 3.1 8B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Llama 3.1 8B Instruct has the lower cheapest tracked output price at $0.05/1M tokens.
  • Llama 3.1 8B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Llama 3.1 8B Instruct for RAG, Long context, and Classification.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output prices on this page.

Lower estimate Llama 3.1 8B Instruct

Gemma 3 12B (free)

$64.50

Cheapest tracked route: OpenRouter

Llama 3.1 8B Instruct

$28.50

Cheapest tracked route: OpenRouter

Estimated monthly gap: $36.00. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

Gemma 3 12B (free) -> Llama 3.1 8B Instruct
  • Provider overlap exists on OpenRouter and AWS Bedrock; start route-level A/B tests there.
  • Llama 3.1 8B Instruct is $0.08/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
Llama 3.1 8B Instruct -> Gemma 3 12B (free)
  • Provider overlap exists on AWS Bedrock and OpenRouter; start route-level A/B tests there.
  • Gemma 3 12B (free) is $0.08/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.

Specs

Specification
Released2026-01-012024-07-23
Context window33K128K
Parameters8B
Architecturedecoder onlydecoder only
LicenseOpen SourceOpen Source
Knowledge cutoff--

Pricing and availability

Pricing attributeGemma 3 12B (free)Llama 3.1 8B Instruct
Input price$0.04/1M tokens$0.02/1M tokens
Output price$0.13/1M tokens$0.05/1M tokens
Providers

Capabilities

CapabilityGemma 3 12B (free)Llama 3.1 8B Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsYesYes
Code executionNoNo

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 (free) lists $0.04/1M input and $0.13/1M output tokens, while Llama 3.1 8B Instruct lists $0.02/1M input and $0.05/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.1 8B Instruct lower by about $0.04 per million blended tokens. Availability is 3 providers versus 12, so concentration risk also matters.

Choose Gemma 3 12B (free) when provider fit are central to the workload. Choose Llama 3.1 8B Instruct when long-context analysis, larger context windows, and lower input-token cost 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 (free) or Llama 3.1 8B Instruct?

Llama 3.1 8B Instruct supports 128K tokens, while Gemma 3 12B (free) supports 33K 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 (free) or Llama 3.1 8B Instruct?

Llama 3.1 8B Instruct is cheaper on tracked token pricing. Gemma 3 12B (free) costs $0.04/1M input and $0.13/1M output tokens. Llama 3.1 8B Instruct costs $0.02/1M input and $0.05/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Gemma 3 12B (free) or Llama 3.1 8B Instruct open source?

Gemma 3 12B (free) is listed under Open Source. Llama 3.1 8B Instruct 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 (free) or Llama 3.1 8B Instruct?

Both Gemma 3 12B (free) and Llama 3.1 8B Instruct 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 (free) and Llama 3.1 8B Instruct?

Gemma 3 12B (free) is available on AWS Bedrock, OpenRouter, and GCP Vertex AI. Llama 3.1 8B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, NVIDIA NIM, and GroqCloud. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Gemma 3 12B (free) over Llama 3.1 8B Instruct?

Llama 3.1 8B Instruct is ~100% cheaper at $0.02/1M; pay for Gemma 3 12B (free) only for provider fit. If your workload also depends on provider fit, start with Gemma 3 12B (free); if it depends on long-context analysis, run the same evaluation with Llama 3.1 8B Instruct.

Continue comparing

Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.