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Llama 3.1 405B Instruct vs ShieldGemma 2

Llama 3.1 405B Instruct (2024) and ShieldGemma 2 (2024) are compact production models from AI at Meta and Google DeepMind. Llama 3.1 405B Instruct ships a 128K-token context window, while ShieldGemma 2 ships a not-yet-sourced context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.

ShieldGemma 2 is safer overall; choose Llama 3.1 405B Instruct when provider fit matters.

Decision scorecard

Local evidence first
SignalLlama 3.1 405B InstructShieldGemma 2
Decision fitRAG, Long context, and ClassificationAgents, Vision, and Classification
Context window128K
Cheapest output$2.4/1M tokens-
Provider routes11 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Llama 3.1 405B Instruct when...
  • Llama 3.1 405B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Llama 3.1 405B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Llama 3.1 405B Instruct for RAG, Long context, and Classification.
Choose ShieldGemma 2 when...
  • ShieldGemma 2 uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags ShieldGemma 2 for Agents, Vision, and Classification.

Monthly cost at traffic

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

Llama 3.1 405B Instruct

$2,520

Cheapest tracked route: AWS Bedrock

ShieldGemma 2

Unavailable

No complete token price in local provider data

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Llama 3.1 405B Instruct -> ShieldGemma 2
  • Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
  • ShieldGemma 2 adds Vision, Multimodal, and Function calling in local capability data.
ShieldGemma 2 -> Llama 3.1 405B Instruct
  • Provider overlap exists on GCP Vertex AI; start route-level A/B tests there.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.

Specs

Specification
Released2024-07-232024-09-01
Context window128K
Parameters405B
Architecturedecoder onlydecoder only
LicenseOpen SourceProprietary
Knowledge cutoff--

Pricing and availability

Pricing attributeLlama 3.1 405B InstructShieldGemma 2
Input price$2.4/1M tokens-
Output price$2.4/1M tokens-
Providers

Capabilities

CapabilityLlama 3.1 405B InstructShieldGemma 2
VisionNoYes
MultimodalNoYes
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsYesYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: ShieldGemma 2, multimodal input: ShieldGemma 2, function calling: ShieldGemma 2, and tool use: ShieldGemma 2. Both models share structured outputs, 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: Llama 3.1 405B Instruct has $2.4/1M input tokens and ShieldGemma 2 has no token price sourced yet. Provider availability is 11 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Llama 3.1 405B Instruct when provider fit and broader provider choice are central to the workload. Choose ShieldGemma 2 when vision-heavy evaluation 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

Is Llama 3.1 405B Instruct or ShieldGemma 2 open source?

Llama 3.1 405B Instruct is listed under Open Source. ShieldGemma 2 is listed under Proprietary. 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 vision, Llama 3.1 405B Instruct or ShieldGemma 2?

ShieldGemma 2 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, Llama 3.1 405B Instruct or ShieldGemma 2?

ShieldGemma 2 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for function calling, Llama 3.1 405B Instruct or ShieldGemma 2?

ShieldGemma 2 has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for tool use, Llama 3.1 405B Instruct or ShieldGemma 2?

ShieldGemma 2 has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Llama 3.1 405B Instruct and ShieldGemma 2?

Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. ShieldGemma 2 is available on GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

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