Llama 4 Maverick 17B Instruct FP8 vs Qwen3.6-Max
Llama 4 Maverick 17B Instruct FP8 (2025) and Qwen3.6-Max (2026) are general-purpose language models from AI at Meta and Alibaba. Llama 4 Maverick 17B Instruct FP8 ships a 1M-token context window, while Qwen3.6-Max ships a 262K-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.
Qwen3.6-Max is safer overall; choose Llama 4 Maverick 17B Instruct FP8 when long-context analysis matters.
Decision scorecard
Local evidence first| Signal | Llama 4 Maverick 17B Instruct FP8 | Qwen3.6-Max |
|---|---|---|
| Decision fit | RAG, Agents, and Long context | Long context and Vision |
| Context window | 1M | 262K |
| Cheapest output | $0.6/1M tokens | - |
| Provider routes | 7 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.
- Qwen3.6-Max uniquely exposes Multimodal in local model data.
- Local decision data tags Qwen3.6-Max for Long context and Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Llama 4 Maverick 17B Instruct FP8
$270
Cheapest tracked route: OpenRouter
Qwen3.6-Max
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Llama 4 Maverick 17B Instruct FP8 and Qwen3.6-Max; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- Qwen3.6-Max adds Multimodal in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.6-Max and Llama 4 Maverick 17B Instruct FP8; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Multimodal before moving production traffic.
- Llama 4 Maverick 17B Instruct FP8 adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2026-04-13 |
| Context window | 1M | 262K |
| Parameters | 17B | — |
| Architecture | mixture of experts | - |
| License | Open Source | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Llama 4 Maverick 17B Instruct FP8 | Qwen3.6-Max |
|---|---|---|
| Input price | $0.15/1M tokens | - |
| Output price | $0.6/1M tokens | - |
| Providers |
Capabilities
| Capability | Llama 4 Maverick 17B Instruct FP8 | Qwen3.6-Max |
|---|---|---|
| Vision | No | No |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | No |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: Qwen3.6-Max 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 Qwen3.6-Max has no token price sourced yet. Provider availability is 7 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 Qwen3.6-Max when provider fit 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 Qwen3.6-Max?
Llama 4 Maverick 17B Instruct FP8 supports 1M tokens, while Qwen3.6-Max supports 262K 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 Qwen3.6-Max open source?
Llama 4 Maverick 17B Instruct FP8 is listed under Open Source. Qwen3.6-Max 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 multimodal input, Llama 4 Maverick 17B Instruct FP8 or Qwen3.6-Max?
Qwen3.6-Max 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 structured outputs, Llama 4 Maverick 17B Instruct FP8 or Qwen3.6-Max?
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 Qwen3.6-Max?
Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Qwen3.6-Max is available on Alibaba Cloud PAI-EAS. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
When should I pick Llama 4 Maverick 17B Instruct FP8 over Qwen3.6-Max?
Qwen3.6-Max is safer overall; choose Llama 4 Maverick 17B Instruct FP8 when long-context analysis matters. If your workload also depends on long-context analysis, start with Llama 4 Maverick 17B Instruct FP8; if it depends on provider fit, run the same evaluation with Qwen3.6-Max.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.