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Llama 4 Scout 17B vs Mistral Small 4

Llama 4 Scout 17B (2025) and Mistral Small 4 (2026) are general-purpose language models from AI at Meta and MistralAI. Llama 4 Scout 17B ships a 10M-token context window, while Mistral Small 4 ships a 256k-token context window. On pricing, Mistral Small 4 costs $0.15/1M input tokens versus $0.17/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Llama 4 Scout 17B fits 39x more tokens; pick it for long-context work and Mistral Small 4 for tighter calls.

Specs

Specification
Released2025-10-012026-03-16
Context window10M256k
Parameters17119B (6.5B active)
Architecture-moe
LicenseOpen SourceApache 2.0
Knowledge cutoff--

Pricing and availability

Pricing attributeLlama 4 Scout 17BMistral Small 4
Input price$0.17/1M tokens$0.15/1M tokens
Output price$0.66/1M tokens$0.6/1M tokens
Providers

Capabilities

CapabilityLlama 4 Scout 17BMistral Small 4
VisionNoYes
MultimodalYesYes
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsYesNo
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on vision: Mistral Small 4, function calling: Mistral Small 4, tool use: Mistral Small 4, and structured outputs: Llama 4 Scout 17B. Both models share multimodal input, 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.

For cost, Llama 4 Scout 17B lists $0.17/1M input and $0.66/1M output tokens, while Mistral Small 4 lists $0.15/1M input and $0.6/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mistral Small 4 lower by about $0.03 per million blended tokens. Availability is 1 providers versus 2, so concentration risk also matters.

Choose Llama 4 Scout 17B when long-context analysis and larger context windows are central to the workload. Choose Mistral Small 4 when vision-heavy evaluation, lower input-token cost, and broader provider choice 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 or Mistral Small 4?

Llama 4 Scout 17B supports 10M tokens, while Mistral Small 4 supports 256k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Llama 4 Scout 17B or Mistral Small 4?

Mistral Small 4 is cheaper on tracked token pricing. Llama 4 Scout 17B costs $0.17/1M input and $0.66/1M output tokens. Mistral Small 4 costs $0.15/1M input and $0.6/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Llama 4 Scout 17B or Mistral Small 4 open source?

Llama 4 Scout 17B is listed under Open Source. Mistral Small 4 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 or Mistral Small 4?

Mistral Small 4 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 or Mistral Small 4?

Both Llama 4 Scout 17B and Mistral Small 4 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.

Where can I run Llama 4 Scout 17B and Mistral Small 4?

Llama 4 Scout 17B is available on AWS Bedrock. Mistral Small 4 is available on OpenRouter and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.