Llama 4 Maverick 17B Instruct FP8 vs Magistral Small 2506
Llama 4 Maverick 17B Instruct FP8 (2025) and Magistral Small 2506 (2025) are frontier reasoning models from AI at Meta and MistralAI. Llama 4 Maverick 17B Instruct FP8 ships a 1m-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 Maverick 17B Instruct FP8 fits 8x more tokens; pick it for long-context work and Magistral Small 2506 for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 4 Maverick 17B Instruct FP8 | Magistral Small 2506 |
|---|---|---|
| Best for | long-context analysis and provider-routed production | reasoning-heavy apps |
| Decision fit | RAG, Agents, and Long context | Long context |
| Context window | 1m | 128k |
| Cheapest output | $0.60/1M tokens | - |
| Provider routes | 8 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama 4 Maverick 17B Instruct FP8 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 4 Maverick 17B Instruct FP8 has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 4 Maverick 17B Instruct FP8 uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 4 Maverick 17B Instruct FP8 for RAG, Agents, and Long context.
- 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 Maverick 17B Instruct FP8
$270
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 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 Maverick 17B Instruct FP8 adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2025-06-10 |
| Context window | 1m | 128k |
| Parameters | 17B | 24B |
| Architecture | mixture of experts | decoder only |
| License | Open Source | Proprietary |
| Knowledge cutoff | 2024-08 | 2025-06 |
Pricing and availability
| Pricing attribute | Llama 4 Maverick 17B Instruct FP8 | Magistral Small 2506 |
|---|---|---|
| Input price | $0.15/1M tokens | - |
| Output price | $0.60/1M tokens | - |
| Providers |
Capabilities
| Capability | Llama 4 Maverick 17B Instruct FP8 | Magistral Small 2506 |
|---|---|---|
| Vision | No | No |
| Multimodal | No | 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 rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: Magistral Small 2506 and structured outputs: Llama 4 Maverick 17B Instruct FP8. 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 Maverick 17B Instruct FP8 has $0.15/1M input tokens and Magistral Small 2506 has no token price sourced yet. Provider availability is 8 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 Maverick 17B Instruct FP8 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. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Llama 4 Maverick 17B Instruct FP8 or Magistral Small 2506?
Llama 4 Maverick 17B Instruct FP8 supports 1m 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 Maverick 17B Instruct FP8 or Magistral Small 2506 open source?
Llama 4 Maverick 17B Instruct FP8 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 reasoning mode, Llama 4 Maverick 17B Instruct FP8 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 Maverick 17B Instruct FP8 or Magistral Small 2506?
Llama 4 Maverick 17B Instruct FP8 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 Maverick 17B Instruct FP8 and Magistral Small 2506?
Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Magistral Small 2506 is available on NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 4 Maverick 17B Instruct FP8 over Magistral Small 2506?
Llama 4 Maverick 17B Instruct FP8 fits 8x more tokens; pick it for long-context work and Magistral Small 2506 for tighter calls. If your workload also depends on long-context analysis, start with Llama 4 Maverick 17B Instruct FP8; if it depends on reasoning depth, run the same evaluation with Magistral Small 2506.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.