LLM Reference

Magistral Small 2506 vs Amazon Nova Multimodal Embeddings

Magistral Small 2506 (2025) and Amazon Nova Multimodal Embeddings (2025) are frontier reasoning models from MistralAI and Amazon Web Services (AWS) AI. Magistral Small 2506 ships a 128k-token context window, while Amazon Nova Multimodal Embeddings ships a not-yet-sourced context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Amazon Nova Multimodal Embeddings is safer overall; choose Magistral Small 2506 when reasoning depth matters.

Decision scorecard

Local evidence first
SignalMagistral Small 2506Amazon Nova Multimodal Embeddings
Best forreasoning-heavy appsmultimodal apps
Decision fitLong contextGeneral
Context window128k
Cheapest output--
Provider routes1 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Magistral Small 2506 when...
  • Magistral Small 2506 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Magistral Small 2506 uniquely exposes Reasoning in local model data.
  • Local decision data tags Magistral Small 2506 for Long context.
Choose Amazon Nova Multimodal Embeddings when...
  • Amazon Nova Multimodal Embeddings uniquely exposes Multimodal in local model data.

Monthly cost at traffic

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

Magistral Small 2506

Unavailable

No complete token price in local provider data

Amazon Nova Multimodal Embeddings

Unavailable

No complete token price in local provider data

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

Switch friction

Magistral Small 2506 -> Amazon Nova Multimodal Embeddings
  • No overlapping tracked provider route is sourced for Magistral Small 2506 and Amazon Nova Multimodal Embeddings; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Reasoning before moving production traffic.
  • Amazon Nova Multimodal Embeddings adds Multimodal in local capability data.
Amazon Nova Multimodal Embeddings -> Magistral Small 2506
  • No overlapping tracked provider route is sourced for Amazon Nova Multimodal Embeddings and Magistral Small 2506; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Multimodal before moving production traffic.
  • Magistral Small 2506 adds Reasoning in local capability data.

Specs

Specification
Released2025-06-102025-12-01
Context window128k
Parameters24B
Architecturedecoder only-
LicenseProprietaryProprietary
Knowledge cutoff2025-06-

Pricing and availability

Pricing attributeMagistral Small 2506Amazon Nova Multimodal Embeddings
Input price--
Output price--
Providers

Pricing not yet sourced for either model.

Capabilities

CapabilityMagistral Small 2506Amazon Nova Multimodal Embeddings
VisionNoNo
MultimodalNoYes
ReasoningYesNo
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
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: Amazon Nova Multimodal Embeddings and reasoning mode: Magistral Small 2506. 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: Magistral Small 2506 has no token price sourced yet and Amazon Nova Multimodal Embeddings 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 Magistral Small 2506 when reasoning depth are central to the workload. Choose Amazon Nova Multimodal Embeddings when provider fit 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 Magistral Small 2506 or Amazon Nova Multimodal Embeddings open source?

Magistral Small 2506 is listed under Proprietary. Amazon Nova Multimodal Embeddings 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, Magistral Small 2506 or Amazon Nova Multimodal Embeddings?

Amazon Nova Multimodal Embeddings 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, Magistral Small 2506 or Amazon Nova Multimodal Embeddings?

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.

Where can I run Magistral Small 2506 and Amazon Nova Multimodal Embeddings?

Magistral Small 2506 is available on NVIDIA NIM. Amazon Nova Multimodal Embeddings is available on AWS Bedrock. 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.

When should I pick Magistral Small 2506 over Amazon Nova Multimodal Embeddings?

Amazon Nova Multimodal Embeddings is safer overall; choose Magistral Small 2506 when reasoning depth matters. If your workload also depends on reasoning depth, start with Magistral Small 2506; if it depends on provider fit, run the same evaluation with Amazon Nova Multimodal Embeddings.

Continue comparing

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