Llama 4 Scout 17B-16E Instruct vs Mistral Small 4
Llama 4 Scout 17B-16E Instruct (2025) and Mistral Small 4 (2026) are general-purpose language models from AI at Meta and MistralAI. Llama 4 Scout 17B-16E Instruct ships a 10m-token context window, while Mistral Small 4 ships a 256k-token context window. On MMLU PRO, Mistral Small 4 leads by 3.7 pts. 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 39x more tokens; pick it for long-context work and Mistral Small 4 for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 4 Scout 17B-16E Instruct | Mistral Small 4 |
|---|---|---|
| Best for | multimodal apps, long-context analysis, and provider-routed production | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Agents, and Long context |
| Context window | 10m | 256k |
| Cheapest output | $0.30/1M tokens | $0.30/1M tokens |
| Provider routes | 12 tracked | 3 tracked |
| Shared benchmarks | 2 shared | MMLU PRO leader |
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 Structured outputs in local model data.
- Local decision data tags Llama 4 Scout 17B-16E Instruct for Coding, RAG, and Agents.
- Mistral Small 4 holds a shared-benchmark lead on MMLU PRO, ahead by 3.7 points.
- Mistral Small 4 uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Mistral Small 4 for RAG, Agents, and 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
Mistral Small 4
$155
Cheapest tracked route/tier: Mistral AI Studio
Estimated monthly gap: $16.00. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and NVIDIA NIM; start route-level A/B tests there.
- Cheapest tracked output pricing is tied, so migration risk shifts to quality, latency, and provider packaging.
- Check replacement coverage for Structured outputs before moving production traffic.
- Mistral Small 4 adds Function calling and Tool use in local capability data.
- Provider overlap exists on OpenRouter and NVIDIA NIM; start route-level A/B tests there.
- Cheapest tracked output pricing is tied, so migration risk shifts to quality, latency, and provider packaging.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- Llama 4 Scout 17B-16E Instruct adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2026-03-16 |
| Context window | 10m | 256k |
| Parameters | 109B (17B active) | 119B (6.5B active) |
| Architecture | Mixture of Experts | Mixture of Experts |
| 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 | Mistral Small 4 |
|---|---|---|
| Input price | $0.08/1M tokens | $0.10/1M tokens |
| Output price | $0.30/1M tokens | $0.30/1M tokens |
| Providers |
Capabilities
| Capability | Llama 4 Scout 17B-16E Instruct | Mistral Small 4 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 4 Scout 17B-16E Instruct | Mistral Small 4 |
|---|---|---|
| MMLU PRO | 74.3 | 78.0 |
| τ-bench | 62.3 | 65.8 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 4 Scout 17B-16E Instruct at 74.3 and Mistral Small 4 at 78, with Mistral Small 4 ahead by 3.7 points; τ-bench has Llama 4 Scout 17B-16E Instruct at 62.3 and Mistral Small 4 at 65.8, with Mistral Small 4 ahead by 3.5 points. The largest visible gap is 3.7 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on function calling: Mistral Small 4, tool use: Mistral Small 4, and structured outputs: Llama 4 Scout 17B-16E Instruct. Both models share vision and 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-16E Instruct lists $0.08/1M input and $0.30/1M output tokens on the cheapest tracked provider, while Mistral Small 4 lists $0.10/1M input and $0.30/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 4 Scout 17B-16E Instruct lower by about $0.01 per million blended tokens. Availability is 12 providers versus 3, so concentration risk also matters.
Choose Llama 4 Scout 17B-16E Instruct when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Mistral Small 4 when vision-heavy evaluation are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Llama 4 Scout 17B-16E Instruct or Mistral Small 4?
Llama 4 Scout 17B-16E Instruct 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-16E Instruct or Mistral Small 4?
Llama 4 Scout 17B-16E Instruct is cheaper on tracked token pricing. Llama 4 Scout 17B-16E Instruct costs $0.08/1M input and $0.30/1M output tokens. Mistral Small 4 costs $0.10/1M input and $0.30/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 4 Scout 17B-16E Instruct or Mistral Small 4 open source?
Llama 4 Scout 17B-16E Instruct is listed under Llama 4 Community. 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-16E Instruct or Mistral Small 4?
Both Llama 4 Scout 17B-16E Instruct and Mistral Small 4 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Llama 4 Scout 17B-16E Instruct or Mistral Small 4?
Both Llama 4 Scout 17B-16E Instruct 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-16E Instruct and Mistral Small 4?
Llama 4 Scout 17B-16E Instruct is available on Cloudflare Workers AI, OpenRouter, Together AI, Fireworks AI, and DeepInfra. Mistral Small 4 is available on OpenRouter, NVIDIA NIM, and Mistral AI Studio. 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.