LLM Reference

Llama 4 Scout 17B vs Magistral Small 2506

Llama 4 Scout 17B (2025) and Magistral Small 2506 (2025) are frontier reasoning models from AI at Meta and MistralAI. Llama 4 Scout 17B ships a 10m-token context window, while Magistral Small 2506 ships a 128k-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.

Llama 4 Scout 17B fits 78x more tokens; pick it for long-context work and Magistral Small 2506 for tighter calls.

Decision scorecard

Local evidence first
SignalLlama 4 Scout 17BMagistral Small 2506
Best formultimodal apps and long-context analysisreasoning-heavy apps
Decision fitRAG, Long context, and VisionLong context
Context window10m128k
Cheapest output$0.66/1M tokens-
Provider routes1 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Llama 4 Scout 17B when...
  • Llama 4 Scout 17B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Llama 4 Scout 17B uniquely exposes Multimodal and Structured outputs in local model data.
  • Local decision data tags Llama 4 Scout 17B for RAG, Long context, and Vision.
Choose Magistral Small 2506 when...
  • Magistral Small 2506 uniquely exposes Reasoning in local model data.
  • Local decision data tags Magistral Small 2506 for Long context.

Monthly cost at traffic

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

Llama 4 Scout 17B

$301

Cheapest tracked route/tier: AWS Bedrock

Magistral Small 2506

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 4 Scout 17B -> Magistral Small 2506
  • No overlapping tracked provider route is sourced for Llama 4 Scout 17B and Magistral Small 2506; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Multimodal and Structured outputs before moving production traffic.
  • Magistral Small 2506 adds Reasoning in local capability data.
Magistral Small 2506 -> Llama 4 Scout 17B
  • No overlapping tracked provider route is sourced for Magistral Small 2506 and Llama 4 Scout 17B; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Reasoning before moving production traffic.
  • Llama 4 Scout 17B adds Multimodal and Structured outputs in local capability data.

Specs

Specification
Released2025-10-012025-06-10
Context window10m128k
Parameters1724B
Architecture-decoder only
LicenseOpen SourceProprietary
Knowledge cutoff2024-082025-06

Pricing and availability

Pricing attributeLlama 4 Scout 17BMagistral Small 2506
Input price$0.17/1M tokens-
Output price$0.66/1M tokens-
Providers

Capabilities

CapabilityLlama 4 Scout 17BMagistral Small 2506
VisionNoNo
MultimodalYesNo
ReasoningNoYes
Function callingNoNo
Tool useNoNo
Structured outputsYesNo
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 multimodal input: Llama 4 Scout 17B, reasoning mode: Magistral Small 2506, and structured outputs: Llama 4 Scout 17B. 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: Llama 4 Scout 17B has $0.17/1M input tokens and Magistral Small 2506 has no token price sourced yet. Provider availability is 1 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 4 Scout 17B when long-context analysis and larger context windows are central to the workload. Choose Magistral Small 2506 when reasoning depth 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, Llama 4 Scout 17B or Magistral Small 2506?

Llama 4 Scout 17B supports 10m tokens, while Magistral Small 2506 supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Llama 4 Scout 17B or Magistral Small 2506 open source?

Llama 4 Scout 17B is listed under Open Source. Magistral Small 2506 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 multimodal input, Llama 4 Scout 17B or Magistral Small 2506?

Llama 4 Scout 17B 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, Llama 4 Scout 17B or Magistral Small 2506?

Magistral Small 2506 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.

Which is better for structured outputs, Llama 4 Scout 17B or Magistral Small 2506?

Llama 4 Scout 17B 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 Llama 4 Scout 17B and Magistral Small 2506?

Llama 4 Scout 17B is available on AWS Bedrock. Magistral Small 2506 is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.