Llama 4 Scout 17B-16E Instruct vs Magistral Small 2506
Llama 4 Scout 17B-16E Instruct (2025) and Magistral Small 2506 (2025) are frontier reasoning models from AI at Meta and MistralAI. Llama 4 Scout 17B-16E Instruct ships a 10m-token context window, while Magistral Small 2506 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.
Llama 4 Scout 17B-16E Instruct fits 78x more tokens; pick it for long-context work and Magistral Small 2506 for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 4 Scout 17B-16E Instruct | Magistral Small 2506 |
|---|---|---|
| Best for | multimodal apps, long-context analysis, and provider-routed production | reasoning-heavy apps |
| Decision fit | Coding, RAG, and Agents | Long context |
| Context window | 10m | 128k |
| Cheapest output | $0.30/1M tokens | - |
| Provider routes | 12 tracked | 1 tracked |
| Shared benchmarks | 0 shared | 0 shared |
Decision tradeoffs
- 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.
- Llama 4 Scout 17B-16E Instruct uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
- Local decision data tags Llama 4 Scout 17B-16E Instruct for Coding, RAG, and Agents.
- 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-16E Instruct
$139
Cheapest tracked route/tier: OpenRouter
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
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Vision, Multimodal, and Structured outputs before moving production traffic.
- Magistral Small 2506 adds Reasoning in local capability data.
- Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
- Check replacement coverage for Reasoning before moving production traffic.
- Llama 4 Scout 17B-16E Instruct adds Vision, Multimodal, and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2025-06-10 |
| Context window | 10m | 128k |
| Parameters | 109B (17B active) | 24B |
| Architecture | Mixture of Experts | Decoder Only |
| License | Llama 4 Community | Apache 2.0OSI-approved |
| Openness | Open weights | Open source |
| Commercial use | Commercial use: conditional | Commercial use: permitted |
| Knowledge cutoff | 2024-08 | 2025-06 |
Pricing and availability
| Pricing attribute | Llama 4 Scout 17B-16E Instruct | Magistral Small 2506 |
|---|---|---|
| Input price | $0.08/1M tokens | - |
| Output price | $0.30/1M tokens | - |
| Providers |
Capabilities
| Capability | Llama 4 Scout 17B-16E Instruct | Magistral Small 2506 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | Yes |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark scores are currently available for this pair.
Deep dive
The capability footprint differs most on vision: Llama 4 Scout 17B-16E Instruct, multimodal input: Llama 4 Scout 17B-16E Instruct, reasoning mode: Magistral Small 2506, and structured outputs: Llama 4 Scout 17B-16E Instruct. 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-16E Instruct has $0.08/1M input tokens and Magistral Small 2506 has no token price sourced yet. Provider availability is 12 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-16E Instruct when long-context analysis, larger context windows, and broader provider choice 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.
FAQ
Which has a larger context window, Llama 4 Scout 17B-16E Instruct or Magistral Small 2506?
Llama 4 Scout 17B-16E Instruct 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-16E Instruct or Magistral Small 2506 open source?
Llama 4 Scout 17B-16E Instruct is listed under Llama 4 Community. Magistral Small 2506 is listed under Apache 2.0. 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 4 Scout 17B-16E Instruct or Magistral Small 2506?
Llama 4 Scout 17B-16E Instruct 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, Llama 4 Scout 17B-16E Instruct or Magistral Small 2506?
Llama 4 Scout 17B-16E Instruct 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-16E Instruct 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.
Where can I run Llama 4 Scout 17B-16E Instruct and Magistral Small 2506?
Llama 4 Scout 17B-16E Instruct is available on Cloudflare Workers AI, OpenRouter, Together AI, Fireworks AI, and DeepInfra. Magistral Small 2506 is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.