Llama 4 Scout 17B-16E Instruct vs Qwen3.6 Max Preview
Llama 4 Scout 17B-16E Instruct (2025) and Qwen3.6 Max Preview (2026) are frontier reasoning models from AI at Meta and Alibaba. Llama 4 Scout 17B-16E Instruct ships a 10m-token context window, while Qwen3.6 Max Preview ships a 256k-token context window. On MMLU PRO, Qwen3.6 Max Preview leads by 14.2 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 Qwen3.6 Max Preview for tighter calls.
Decision scorecard
Local evidence first| Signal | Llama 4 Scout 17B-16E Instruct | Qwen3.6 Max Preview |
|---|---|---|
| Best for | multimodal apps, long-context analysis, and provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 10m | 256k |
| Cheapest output | $0.30/1M tokens | $6.24/1M tokens |
| Provider routes | 12 tracked | 3 tracked |
| Shared benchmarks | 3 rows | 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 the lower cheapest tracked output price at $0.30/1M tokens.
- Llama 4 Scout 17B-16E Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 4 Scout 17B-16E Instruct for Coding, RAG, and Agents.
- Qwen3.6 Max Preview holds a shared-benchmark lead on MMLU PRO, ahead by 14.2 points.
- Qwen3.6 Max Preview uniquely exposes Reasoning, Function calling, and Tool use in local model data.
- Local decision data tags Qwen3.6 Max Preview for Coding, RAG, and Agents.
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
Qwen3.6 Max Preview
$2,392
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $2,253. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- Qwen3.6 Max Preview is $5.94/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.6 Max Preview adds Reasoning, Function calling, and Tool use in local capability data.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- Llama 4 Scout 17B-16E Instruct is $5.94/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning, Function calling, and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2026-04-20 |
| Context window | 10m | 256k |
| Parameters | 109B (17B active) | — |
| Architecture | mixture of experts | moe |
| License | Llama 4 Community | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2024-08 | - |
Pricing and availability
| Pricing attribute | Llama 4 Scout 17B-16E Instruct | Qwen3.6 Max Preview |
|---|---|---|
| Input price | $0.08/1M tokens |
|
| Output price | $0.30/1M tokens |
|
| Providers |
Capabilities
| Capability | Llama 4 Scout 17B-16E Instruct | Qwen3.6 Max Preview |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 4 Scout 17B-16E Instruct | Qwen3.6 Max Preview |
|---|---|---|
| MMLU PRO | 74.3 | 88.5 |
| LiveCodeBench | 32.8 | 87.1 |
| Massive Multi-discipline Multimodal Understanding | 69.4 | 82.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 4 Scout 17B-16E Instruct at 74.3 and Qwen3.6 Max Preview at 88.5, with Qwen3.6 Max Preview ahead by 14.2 points; LiveCodeBench has Llama 4 Scout 17B-16E Instruct at 32.8 and Qwen3.6 Max Preview at 87.1, with Qwen3.6 Max Preview ahead by 54.3 points; Massive Multi-discipline Multimodal Understanding has Llama 4 Scout 17B-16E Instruct at 69.4 and Qwen3.6 Max Preview at 82, with Qwen3.6 Max Preview ahead by 12.6 points. The largest visible gap is 54.3 points on LiveCodeBench, 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 reasoning mode: Qwen3.6 Max Preview, function calling: Qwen3.6 Max Preview, and tool use: Qwen3.6 Max Preview. Both models share vision, multimodal input, and structured outputs, 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 Qwen3.6 Max Preview lists tiered pricing: 0-128,000t is $1.30/1M input and $7.80/1M output; 128,000t+ is $2/1M input and $12/1M output. A 70/30 input-output blend puts Llama 4 Scout 17B-16E Instruct lower by about $2.45 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. 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 Qwen3.6 Max Preview when reasoning depth 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 Qwen3.6 Max Preview?
Llama 4 Scout 17B-16E Instruct supports 10m tokens, while Qwen3.6 Max Preview 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 Qwen3.6 Max Preview?
Llama 4 Scout 17B-16E Instruct lists $0.08/1M input and $0.30/1M output tokens on the cheapest tracked provider. Qwen3.6 Max Preview lists tiered pricing: 0-128,000t is $1.30/1M input and $7.80/1M output; 128,000t+ is $2/1M input and $12/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is Llama 4 Scout 17B-16E Instruct or Qwen3.6 Max Preview open source?
Llama 4 Scout 17B-16E Instruct is listed under Llama 4 Community. Qwen3.6 Max Preview 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 Qwen3.6 Max Preview?
Both Llama 4 Scout 17B-16E Instruct and Qwen3.6 Max Preview 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 Qwen3.6 Max Preview?
Both Llama 4 Scout 17B-16E Instruct and Qwen3.6 Max Preview 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 Qwen3.6 Max Preview?
Llama 4 Scout 17B-16E Instruct is available on Cloudflare Workers AI, OpenRouter, Together AI, Fireworks AI, and DeepInfra. Qwen3.6 Max Preview is available on OpenRouter, Alibaba Cloud PAI-EAS, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-07. Data sourced from public model cards and provider documentation.