LLM Reference

Magistral Small 2506 vs Stockmark 2 100B Instruct

Magistral Small 2506 (2025) and Stockmark 2 100B Instruct (2025) are frontier reasoning models from MistralAI and Stockmark. Magistral Small 2506 ships a 128k-token context window, while Stockmark 2 100B Instruct ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.

Magistral Small 2506 is safer overall; choose Stockmark 2 100B Instruct when provider fit matters.

Decision scorecard

Local evidence first
SignalMagistral Small 2506Stockmark 2 100B Instruct
Best forreasoning-heavy appsgeneral production evaluation
Decision fitLong contextLong context
Context window128k128k
Cheapest output--
Provider routes1 tracked1 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

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.
Choose Stockmark 2 100B Instruct when...
  • Local decision data tags Stockmark 2 100B Instruct for Long context.

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

Stockmark 2 100B Instruct

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 -> Stockmark 2 100B Instruct
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • Check replacement coverage for Reasoning before moving production traffic.
Stockmark 2 100B Instruct -> Magistral Small 2506
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • Magistral Small 2506 adds Reasoning in local capability data.

Specs

Specification
Released2025-06-102025-06-01
Context window128k128k
Parameters24B100B
ArchitectureDecoder OnlyDecoder Only
LicenseApache 2.0OSI-approvedOpen Weights
OpennessOpen sourceOpen weights
Commercial useCommercial use: permitted-
Knowledge cutoff2025-06-

Pricing and availability

Pricing attributeMagistral Small 2506Stockmark 2 100B Instruct
Input price--
Output price--
Providers

Pricing not yet sourced for either model.

Capabilities

CapabilityMagistral Small 2506Stockmark 2 100B Instruct
VisionNoNo
MultimodalNoNo
ReasoningYesNo
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on 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 Stockmark 2 100B Instruct 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 Stockmark 2 100B Instruct 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

Which has a larger context window, Magistral Small 2506 or Stockmark 2 100B Instruct?

Magistral Small 2506 supports 128k tokens, while Stockmark 2 100B Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Magistral Small 2506 or Stockmark 2 100B Instruct open source?

Magistral Small 2506 is listed under Apache 2.0. Stockmark 2 100B Instruct is listed under Open Weights. 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 reasoning mode, Magistral Small 2506 or Stockmark 2 100B Instruct?

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 Stockmark 2 100B Instruct?

Magistral Small 2506 is available on NVIDIA NIM. Stockmark 2 100B Instruct 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.

When should I pick Magistral Small 2506 over Stockmark 2 100B Instruct?

Magistral Small 2506 is safer overall; choose Stockmark 2 100B Instruct when provider fit 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 Stockmark 2 100B Instruct.

Continue comparing

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