LLM Reference

Gemma 4 12B IT vs Llama 4 Scout 17B-16E Instruct

Gemma 4 12B IT (2026) and Llama 4 Scout 17B-16E Instruct (2025) are frontier reasoning models from Google DeepMind and AI at Meta. Gemma 4 12B IT ships a 256k-token context window, while Llama 4 Scout 17B-16E Instruct ships a 328k-token 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.

Gemma 4 12B IT is safer overall; choose Llama 4 Scout 17B-16E Instruct when long-context analysis matters.

Decision scorecard

Local evidence first
SignalGemma 4 12B ITLlama 4 Scout 17B-16E Instruct
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentsprovider-routed production
Decision fitCoding, RAG, and AgentsRAG, Agents, and Long context
Context window256k328k
Cheapest output-$0.30/1M tokens
Provider routes2 tracked10 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Gemma 4 12B IT when...
  • Gemma 4 12B IT uniquely exposes Vision, Multimodal, and Reasoning in local model data.
  • Local decision data tags Gemma 4 12B IT for Coding, RAG, and Agents.
Choose Llama 4 Scout 17B-16E Instruct when...
  • Llama 4 Scout 17B-16E Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Llama 4 Scout 17B-16E Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Llama 4 Scout 17B-16E Instruct for RAG, Agents, and Long context.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Gemma 4 12B IT

Unavailable

No complete token price in local provider data

Llama 4 Scout 17B-16E Instruct

$139

Cheapest tracked route/tier: OpenRouter

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

Switch friction

Gemma 4 12B IT -> Llama 4 Scout 17B-16E Instruct
  • No overlapping tracked provider route is sourced for Gemma 4 12B IT and Llama 4 Scout 17B-16E Instruct; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
Llama 4 Scout 17B-16E Instruct -> Gemma 4 12B IT
  • No overlapping tracked provider route is sourced for Llama 4 Scout 17B-16E Instruct and Gemma 4 12B IT; plan for SDK, billing, or endpoint changes.
  • Gemma 4 12B IT adds Vision, Multimodal, and Reasoning in local capability data.

Specs

Specification
Released2026-06-032025-04-05
Context window256k328k
Parameters11.9B17B
Architectureencoder free unified multimodalmixture of experts
LicenseApache 2.0Open Source
Knowledge cutoff2025-012024-08

Pricing and availability

Pricing attributeGemma 4 12B ITLlama 4 Scout 17B-16E Instruct
Input price-$0.08/1M tokens
Output price-$0.30/1M tokens
Providers

Capabilities

CapabilityGemma 4 12B ITLlama 4 Scout 17B-16E Instruct
VisionYesNo
MultimodalYesNo
ReasoningYesNo
Function callingYesNo
Tool useYesNo
Structured outputsYesYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Gemma 4 12B IT, multimodal input: Gemma 4 12B IT, reasoning mode: Gemma 4 12B IT, function calling: Gemma 4 12B IT, and tool use: Gemma 4 12B IT. 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: Gemma 4 12B IT has no token price sourced yet and Llama 4 Scout 17B-16E Instruct has $0.08/1M input tokens. Provider availability is 2 tracked routes versus 10. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Gemma 4 12B IT when reasoning depth are central to the workload. Choose Llama 4 Scout 17B-16E Instruct when long-context analysis, larger context windows, 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.

FAQ

Which has a larger context window, Gemma 4 12B IT or Llama 4 Scout 17B-16E Instruct?

Llama 4 Scout 17B-16E Instruct supports 328k tokens, while Gemma 4 12B IT supports 256k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Gemma 4 12B IT or Llama 4 Scout 17B-16E Instruct open source?

Gemma 4 12B IT is listed under Apache 2.0. Llama 4 Scout 17B-16E 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 vision, Gemma 4 12B IT or Llama 4 Scout 17B-16E Instruct?

Gemma 4 12B IT 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.

Which is better for multimodal input, Gemma 4 12B IT or Llama 4 Scout 17B-16E Instruct?

Gemma 4 12B IT 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 reasoning mode, Gemma 4 12B IT or Llama 4 Scout 17B-16E Instruct?

Gemma 4 12B IT has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Gemma 4 12B IT and Llama 4 Scout 17B-16E Instruct?

Gemma 4 12B IT is available on Hugging Face Inference Endpoints and Kaggle Models. Llama 4 Scout 17B-16E Instruct is available on OpenRouter, Together AI, Fireworks AI, DeepInfra, and GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-03. Data sourced from public model cards and provider documentation.