Llama 4 Maverick 17B Instruct FP8 vs Qwen3.5-4B
Llama 4 Maverick 17B Instruct FP8 (2025) and Qwen3.5-4B (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 Qwen3.5-4B 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.
Qwen3.5-4B 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 | Qwen3.5-4B |
|---|---|---|
| Best for | long-context analysis and provider-routed production | multimodal apps |
| Decision fit | RAG, Agents, and Long context | Long context and Vision |
| Context window | 1m | 262k |
| Cheapest output | $0.60/1M tokens | - |
| Provider routes | 8 tracked | 0 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.
- Qwen3.5-4B uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Qwen3.5-4B for Long context and Vision.
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
Qwen3.5-4B
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 Qwen3.5-4B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- Qwen3.5-4B adds Vision and Multimodal in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-4B and Llama 4 Maverick 17B Instruct FP8; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- Llama 4 Maverick 17B Instruct FP8 adds Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2026-03-02 |
| Context window | 1m | 262k |
| Parameters | 17B | 4B |
| Architecture | mixture of experts | - |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | 2024-08 | - |
Pricing and availability
| Pricing attribute | Llama 4 Maverick 17B Instruct FP8 | Qwen3.5-4B |
|---|---|---|
| Input price | $0.15/1M tokens | - |
| Output price | $0.60/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Llama 4 Maverick 17B Instruct FP8 | Qwen3.5-4B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| 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 vision: Qwen3.5-4B, multimodal input: Qwen3.5-4B, 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 Qwen3.5-4B has no token price sourced yet. Provider availability is 8 tracked routes versus 0. 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 Qwen3.5-4B 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. 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 Qwen3.5-4B?
Llama 4 Maverick 17B Instruct FP8 supports 1m tokens, while Qwen3.5-4B 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 Qwen3.5-4B open source?
Llama 4 Maverick 17B Instruct FP8 is listed under Open Source. Qwen3.5-4B 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 Maverick 17B Instruct FP8 or Qwen3.5-4B?
Qwen3.5-4B 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. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Llama 4 Maverick 17B Instruct FP8 or Qwen3.5-4B?
Qwen3.5-4B 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 Qwen3.5-4B?
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 Qwen3.5-4B?
Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Qwen3.5-4B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.