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Gemini 1.5 Flash 8B vs Llama Guard 4 12B

Gemini 1.5 Flash 8B (2024) and Llama Guard 4 12B (2025) are general-purpose language models from Google DeepMind and AI at Meta. Gemini 1.5 Flash 8B ships a not-yet-sourced context window, while Llama Guard 4 12B ships a 164K-token context window. On pricing, Gemini 1.5 Flash 8B costs $0.04/1M input tokens versus $0.18/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Gemini 1.5 Flash 8B is ~380% cheaper at $0.04/1M; pay for Llama Guard 4 12B only for provider fit.

Specs

Specification
Released2024-10-032025-04-05
Context window164K
Parameters8B
Architecturedecoder onlydecoder only
LicenseUnknownOpen Source
Knowledge cutoff--

Pricing and availability

Pricing attributeGemini 1.5 Flash 8BLlama Guard 4 12B
Input price$0.04/1M tokens$0.18/1M tokens
Output price$0.15/1M tokens$0.18/1M tokens
Providers

Capabilities

CapabilityGemini 1.5 Flash 8BLlama Guard 4 12B
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on structured outputs: Llama Guard 4 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, Gemini 1.5 Flash 8B lists $0.04/1M input and $0.15/1M output tokens, while Llama Guard 4 12B lists $0.18/1M input and $0.18/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemini 1.5 Flash 8B lower by about $0.11 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.

Choose Gemini 1.5 Flash 8B when provider fit and lower input-token cost are central to the workload. Choose Llama Guard 4 12B 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 is cheaper, Gemini 1.5 Flash 8B or Llama Guard 4 12B?

Gemini 1.5 Flash 8B is cheaper on tracked token pricing. Gemini 1.5 Flash 8B costs $0.04/1M input and $0.15/1M output tokens. Llama Guard 4 12B costs $0.18/1M input and $0.18/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Gemini 1.5 Flash 8B or Llama Guard 4 12B open source?

Gemini 1.5 Flash 8B is listed under Unknown. Llama Guard 4 12B 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, Gemini 1.5 Flash 8B or Llama Guard 4 12B?

Llama Guard 4 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 Gemini 1.5 Flash 8B and Llama Guard 4 12B?

Gemini 1.5 Flash 8B is available on GCP Vertex AI. Llama Guard 4 12B is available on NVIDIA NIM, Replicate API, and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Gemini 1.5 Flash 8B over Llama Guard 4 12B?

Gemini 1.5 Flash 8B is ~380% cheaper at $0.04/1M; pay for Llama Guard 4 12B only for provider fit. If your workload also depends on provider fit, start with Gemini 1.5 Flash 8B; if it depends on provider fit, run the same evaluation with Llama Guard 4 12B.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.